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USC MICROGRID DEVELOPMENT CONCEPTUAL PLAN

By
MENGNA DING

A thesis submitted in partial fulfillment of
The requirement for the degree of

MASTER OF SCIENCE IN ELECTRICAL ENGINEERING

UNIVERSITY OF SOUTHERN CALIFORNIA
Viterbi School of Engineering

MARCH 2014

II

ACKNOWLEDGMENTS
I would like to express my sincere gratitude to the supervision of Dr. Mohammed Beshir. He
offered me this great opportunity to participate in USC Smart Grid Regional Demonstration
Project. His invaluable assistance and guidance helped me in completing the project in time. I
sincerely thank to Carol Fern who rendered her help during the period of my project work. My
special thanks to Zeming Jiang and Laith Shalalfeh for their guidance and to Jiaji Hu for his help.
Finally, I am deeply indebted to my beloved parents for their understanding, encouragement, and
endless support.

III

USC MICROGRID DEVELOPMENT CONCEPTUAL PLAN
Abstract
By Mengna Ding. M.S.
University of Southern California
March 2014

Chair: Mohammed Beshir
Comparing with traditional unidirectional energy flow from utilities, microgrid is based on
distributed energy resources, effectively realizes environmental friendly energy cascade
utilization as a promising method to enhance electric power reliability, security, flexibility and
economical efficiency. At present, there is a need to develop the existing distribution system in
University of Southern California for fitting the new technology and offer Smart Grid research
conditions for faculty, staff and students.
To accommodate the high demand of system development, the assess and plan of microgrid
has been studied using Distribution Engineering Workstation and HOMER. Photovoltaic and
microturbines are chosen to be microsources. Simulation results for both power flow and general
analysis show case studies of existing, planned and islanded microgrid configuration of
University Park Campus. The capability, economy and emissions are discussed.
This study put up with an outline for energy plan in USC when developing the distribution
system. It will help with the design and construction as a applicable reference.

IV

TABLE OF CONTENTS

ACKNOWLEDGMENTS ................................................................................ II
Abstract ........................................................................................................... III
CHAPTER 1 INTRODUCTION........................................................................ 1
1.1 Background .......................................................................................................... 1
1.2 Purposes and Significance .................................................................................... 3
1.3 Organization of This Thesis .................................................................................. 4
CHAPTER 2 AN OVERVIEW OF MICROGRID ............................................. 5
2.1 Historical Development ........................................................................................ 5
2.2 Microgrid Concept and Basic Structure ................................................................ 6
2.3 Main Microsources ............................................................................................... 9
2.3.1 Microturbine .............................................................................................. 9
2.3.2 Fuel Cell .................................................................................................. 10
2.3.3 Solar Photovoltaic .................................................................................... 12
2.3.4 Wind ........................................................................................................ 13
2.3.5 Microsource Summary ............................................................................. 14
2.4 Storage Technologies.......................................................................................... 14

V

2.4.1 Battery[13] ............................................................................................... 14
2.4.2 Flywheel .................................................................................................. 16
2.4.3 Supercapacitor ......................................................................................... 16
2.5 System Issue ...................................................................................................... 16
2.5.1 Current Integration Standard .................................................................... 16
2.5.2 System Protection .................................................................................... 17
2.5.3 Voltage Regulation ................................................................................... 18
2.5.4 Microgrid Monitoring and Control ........................................................... 18
2.5.5 Imbalance................................................................................................. 20
2.5.6 Power Electronic Interactions ................................................................... 21
2.5.7 Voltage Profile ......................................................................................... 22
CHAPTER 3 UNIVERSITY PARK CAMPUS DISTRIBUTION SYSTEM
REVIEW AND ANALYSIS ............................................................................. 23
3.1 Energy Infrastructure and Usage ......................................................................... 23
3.2 Electrical Infrastructure ...................................................................................... 28
3.3 Load Profile ....................................................................................................... 29
CHAPTER 4 USC MICROGRID CONCEPTUAL PLAN AND MODELING32
4.1 Plan Objective .................................................................................................... 32

VI

4.2 Critical Load in UPC .......................................................................................... 32
4.3 Resource for USC Microgrid .............................................................................. 33
4.3.1 Solar ........................................................................................................ 33
4.3.2 Other Resources ....................................................................................... 37
4.4 UPC Modeling ................................................................................................... 39
4.4.1 DEW Software ......................................................................................... 39
4.4.2 UPC Model .............................................................................................. 40
4.5 System Analysis ................................................................................................. 45
4.6 Microgrid Model and Analysis ........................................................................... 47
CHAPTER 5 OPERATION ANALYSIS .......................................................... 49
5.1 HOMER Software .............................................................................................. 49
5.2 Modeling ............................................................................................................ 49
5.3 Analysis ............................................................................................................. 56
5.3.1 Original System Analysis Result .............................................................. 56
5.3.2 System with DG Analysis Result .............................................................. 56
5.3.3 Comparison .............................................................................................. 57
CHAPTER 6 CONCLUSIONS ........................................................................ 60
APPENDIX ..................................................................................................... 61

VII

REFERENCES ................................................................................................ 69
BIBLIOGRAPHY ............................................................................................ 71

1

CHAPTER 1 INTRODUCTION
1.1 Background
Microgrid has experienced a long history since Thomas Edison’s Manhattan Pearl Street
Station Project built as the first power plant in the world. Because there was no centralized grid
at that time, this project creates a microgrid. Until year of 1886, Edison’s firm has installed 58
direct current (DC) microgrids. Later, the electric service industry became a monopoly market
regulated by state, striking enthusiastic for developing microgrids.
In recent time, there are various indicators showing demand for creating promising markets
for microgrids, especially in the US. It turns out that today’s electricity grid fundamental
architecture, the style of a top-down system basing on one direction energy flow is too old. After
the election of Barack Obama as president in 2008, the government stimulus funding packages to
the economic recession in 2009 started a promising trend of investing smart grid. The US now is
on its way to become microgrids leader in the global market.
Main elements in microgrid concept include: integrated energy system, distributed energy
resources (DER), electrical loads, in mode of parallel or islanded from the existing utility power
grid. In the most common configuration, DERs are tied together on their own feeder, after which
is the link to the grid through a single point of common coupling.
The most difficult and challenging feature of a microgrid is the islanding, which is to isolate
from the grid, when there is brownouts or blackouts in the utility’s system. DERs in microgrid
can provide power to the microgrid for operation.
Unintentional islanding used to be the concern from utilities letting customer have
microgrids since the local control is not sufficiently reliable. As new inverter technologies bring

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a new prospect, utilities may no longer stall wide spread growth of microgrids throughout the
United States.
There are five primary microgrid applications: community/utility microgrid,
commercial/industrial, institutional/campus, remote off-grid systems, military microgrids.
Because of the advantage of common ownership, campus cases of microgrids offer the best
near-term development opportunity. At present, 322 MW of college campus microgrids are up
and running in the United States, with more sophisticated state-of-the-art microgrids on the
drawing boards. In the U.S., 40% of future microgrids will be developed in this market segment,
adding 940 MW of new capacity valued at $2.76 billion by 2015.

Figure 1. Microgrid Capacity, World Markets: 2010-2015[1]

3

Figure 2. Market Sector Revenue Breakdown, North America: 2015[1]
1.2 Purposes and Significance
The primary significance of a microgrid is to ensure local, reliable, and affordable energy
security for consumers, which is USC in this case. Benefits that extend to utilities and the
community are large include lowering greenhouse gas (GHG) emissions and lowering stress on
the transmission and distribution system. For USC, a microgrid provides power quality,
reliability and security within the campus. Meanwhile it enhances the integration of distributed
and renewable energy source since the sufficient solar energy in the area where USC locates has
a large energy potential. There will be a competitive cost and efficient in a long run. In the
perspective of technology, a microgrid enables smart grid technology’s integration, which is able
to effectively support research in related area in USC.
Purpose of this project is to assess the potential of developing USC distributed grid into a
microgrid and design a conceptual plan from energy perspective. This will be a practical and
effective reference when a real microgrid project is starting up.

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1.3 Organization of This Thesis
The organization of the remaining chapters is as follows: Chapter 2 describes the concept of
microgrid. Microsources, energy storage technology and system issues are discussed also. In
Chapter 3, the University Park Campus of University of Southern California electric distribution
system is reviewed and analyzed. In Chapter 4, the UPC campus distribution system is planned
into a microgrid serving critical load. Then the system is modeled and simulated using
Distribution Engineering Workstation (DEW) and the conceptual plan is analyzed. In Chapter 5,
the planned system economical model is built in software HOMER and utilized for analysis. The
conclusion of this project is given in Chapter 6.

5

CHAPTER 2 AN OVERVIEW OF MICROGRID
2.1 Historical Development
The fundamental transition experienced by US electric power system changed the system
from a centrally planned and controlled structure to one that is decided by competition in market
regarding investment, operations and reliability management. With evolving of market rules and
structure of the whole industry changes, there is a critical challenge to maintain the reliability of
the grid and support economic transfers of power. New technologies were needed to prevent
major outages such as those experienced on the Western grid on August 10, 1996, which left 12
million people without electricity for up to eight hours and cost an estimated $2 billion.

The Consortium for Electric Reliability Technology Solutions (CERTS) founded in 1999
serves as a main role in researching, developing, and disseminating new methods, tools, and
technologies to protect and enhance the reliability of the U.S. electric power system and
functioning of a competitive electricity market. Evolutionary changes in the regulatory and
operational climate of traditional electric utilities and the emergence of smaller generating
systems such as microturbines have opened new opportunities for on-site power generation by
electricity users. In this context, distributed energy resources (DER) - small power generators
typically located at users’ sites where the energy (both electric and thermal) they generate is used
- have emerged as a promising option to meet growing customer needs for electric power with an
emphasis on reliability and power quality. The portfolio of DER includes generators, energy
storage, load control, and, for certain classes of systems, advanced power electronic interfaces
between the generators and the bulk power provider. The concept microgrid was put forward by
CERTS in 2002.[2]

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2.2 Microgrid Concept and Basic Structure
The term Microgrid has been used for a decade and varied among different organizations.
The first and most traditional definition is published by Lasseter, R. through Consortium for
Electric Reliability Technology Solutions (CERTS). The statement is as below:
The Consortium for Electric Reliability Technology Solutions (CERTS) MicroGrid concept
assumes an aggregation of loads and microsources operating as a single system providing both
power and heat. The majority of the microsources must be power electronic based to provide the
required flexibility to insure operation as a single aggregated system. This control flexibility
allows the CERTS MicroGrid to present itself to the bulk power system as a single controlled
unit that meets local needs for reliability and security.[2]
Compared with Institute of Electrical and Electronics Engineers (IEEE) Standard 1547 at
that time, which focuses on turning off generators inside distribution grid automatically if
emergency situations occurs on the bulk power grid,[3] the CERTS microgrid is designed to
seamlessly separate or island from the grid and reconnect to the grid if emergencies are resolved.
The Smart Grid R&D Program, within the U.S. Department of Energy (DOE) Office of
Electricity Delivery and Energy Reliability (OE), convened this second Microgrid Workshop on
July 30-31, 2012, in Chicago, Illinois. The Smart Grid R&D Program adopts the definition of the
microgrid by the Microgrid Exchange Group (MEG); namely, “A microgrid is a group of
interconnected loads and distributed energy resources within clearly defined electrical
boundaries that acts as a single controllable entity with respect to the grid. A microgrid can
connect and disconnect from the grid to enable it to operate in both grid-connected or
island-mode.”[4]

7

This concept regulated a more broad definition which stresses electrical boundaries,
controllable and having the ability of connecting and isolating from the grid.
For one of the most important features, a microgrid serves as a single self-controlled entity
to a large grid, which is indistinguishable from other customer sites. To keep this characteristic,
flexibility of advanced power electronics that control the interface between microsources and
their surrounding AC system is a must. So all Distributed Energy Resources (DER) are supposed
to be supported by flexible power electronics technology in order to get approached with
eliminating dominant existing concerns such as intermittency and unpredictability.
From the point of a grid, a microgrid is regarded as a single aggregated load being a
controlled entity within the power system. What’s more, a microgrid can guarantee a pattern of
usage which is regulated as strict as other common customers.
From the customer’s perspective, a microgrid can meet local energy need for both
electricity, heat and cooling as well as provide uninterruptible power, enhance local reliability,
reduce feeder losses, and support local voltages/correct voltage sag.
A typical microgrid structure is shown as below:

8

Figure 3. CERTS Microgrid
From the above structure, the two essential components are the Separation Device and the
microsources. The static switch is the breaker to island the microgrid from grid emergencies like
faults, IEEE 1547 events and power quality events. During the transition to islanding state, real
and reactive power flow is regulated by droop control between microsources and loads.[5]-[9]
Under islanding status, every microsource takes charge of balance the power on the islanded
microgrid using a power versus frequency droop controller. The reconnection of microgrid to the
utility grid is achieved autonomously when the tripping event is no longer present.
Besides, the typical structure consists of a group of radial feeders which can be a part of a
distribution system or a building electrical system. There is a single point of connection to the
utility that is called the point of common coupling[2]. Feeder A to C have sensitive loads which
require local generation. The microgrid of Fig.1 has four microsources at nodes 8, 11, 16 and 22.
The microsources control the microgrid operation using only local voltage and current
measurements. Because Feeder D doesn’t connect to a sensitive load, there is no local resource
connect to it directly.
When there is a problem with the utility supply, the static switch isolates the sensitive loads

9

(Feeders A to C) from the utility grid in less than a cycle. Nonsensitive loads (Feeder D) ride
through the event. So the microsources within the inter grid provide sufficient generation which
meets the power demands of Feeder A, B and C.

2.3 Main Microsources
2.3.1 Microturbine
Microturbines (MTs) running on natural gas represent an important and emerging
technology in distributed generation (DG) systems. Natural gas MTs has the advantage of
relatively high efficiency comparing with other DG sources (approximately 33% or even 80% in
some cases). Also microturbines have the advantage that they can be used as backup resource for
other microsource, wind farm for instance. If wind speed is less than 6m/s, there needs to avoid
blackouts for the grid stability. Microturbine is one of the options.
Within a microturbine there are three key components: the engine driven either on liquid
fuel or gas; the fuel system, comprising the gas boost compressors to feed the MT with gas at the
appropriate pressure, and the generator, which produce electricity at 50 Hz or 60 Hz.[10]
This cutaway view below of a Capstone C65 turbogenerator illustrates the arrangement of
all the gas turbine components, including the generator. Ambient air is compressed in the
compressor, fuel is burned in the combustor to raise the temperature of the compressed air, and
the high-pressure hot gases expand through the radial turbine to produce shaft power for the
generator. The recuperator recovers heat from the hot gases to heat the compressed air before
entering the combustor to reduce the amount of fuel consumed, thereby increasing the thermal
efficiency of the turbogenerator system.

10

Figure 4. Microturbine Cutaway View
2.3.2 Fuel Cell
Fuel cells generate electricity from hydrogen and oxygen—without any harmful missions
and therefore in an extremely environmentally friendly way. Heat is produced in varying
amounts, as well as the by-product water.
Figure below shows how the fuel cell works. A proton exchange membrane is coated with a
thin platinum catalyzer layer and a gas-permeable electrode made of graphite paper. Hydrogen
fed to the anode side ionizes into protons and electrons at the catalyzer. The protons pass the
catalyzer layer, while the electrons remaining behind give a negative charge to the hydrogen-side
electrode. During the proton migration, a volt age difference builds up between the electrodes.
When these are connected, this difference produces a direct current that can drive an engine, for

11

example.

Figure 5. How Fuel Cell Works
Finally, the protons recombine with the electrons and oxygen into water at the cathode.
Besides the recovered electric energy, the only reaction product is water. Additionally, heat is
produced by the electrochemical reactions and the contact resistances in the fuel cell, which can
be used for space or service water heating. The voltage of a single non-operated cell is about 1.23
V. In operation, this level falls to about 0.6–0.7 V under load. As this level is too low for practical
applications; a sufficient number of cells are connected in series to obtain a usable voltage. They
may add up to 800 cells in larger-sized plants. The line-up of cells is equivalent to a stack; this
word has become a technical term generally used for this arrangement. It is characteristic of fuel
cells that they generate DC voltage. To allow practical use, it has to be transformed into an AC
signal. This is done by downstream DC/AC converters [11] .

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2.3.3 Solar Photovoltaic
PV cells are solid-state, semiconductor-based devices which convert radiant energy directly
into electricity. It does not rely on moving parts. This technology has the features of no emission,
no conventional fuels and minimal maintenance. These make PV technology ideal for portable or
remote applications.
PV cells consist of several layers of different materials. The primary layer is a
semiconductor material where the photoelectric effect takes place. The semiconductors used
these days are typically composed of silicon. It is in middle of two metallic layers that provide a
steady flow of electrons through the semiconductor and connect the cell to an external electrical
circuit. These layers are sealed in encapsulant like glass for protection. Between the glass and
photoactive surface there is an anti-reflective film utilized in order to have larger light
absorption.
Today’s commercially available solar cells consist of five basic materials, each with its own
trade-offs between manufacturing costs and efficiency:
a) Single-crystal, large-area planar silicon cells yield high efficiencies under normal light
conditions;
b) Single-crystal, small-area concentrator silicon cells yield higher efficiencies under
concentrated light (from 20-1000 suns);
c) Polycrystalline silicon cells are less expensive, but also less efficient than single crystal
cells;
d) Various thin film semiconductor materials are available including amorphous silicon
(a-Si), cadmium telluride (CdTe) and copper-indium-diselenide (CIS).

13

Amorphous silicon modules are a commercial product, but are less efficient than
polycrystalline materials. The severe performance degradation that plagued early versions of a-Si
have been resolved, although they still suffer from an initial performance loss. CdTe also has
stability and manufacturing challenges, in addition to potential environmental concerns over the
use of cadmium. CIS echnologies have potentially high efficiencies, but face manufacturing
challenges.
Multi-junction cells consisting of several layers of different semi-conducting laterals are
being produced primarily for space applications. These PV cells have achieved record-setting
efficiencies as high as 35% under concentrated light, but are more complex to manufacture.
Tandem-junction devices made of layers of amorphous silicon are currently available primarily
for the terrestrial market.[12]

2.3.4 Wind
From perspective of energy conversion, a wind power generator can be divided into two
parts: the wind turbine and the generator. Wind speed work on blades to produce rotation torque,
which drives rotation of hub. Then through gearboxes, brake discs and coupler, the turbine is
connected with asynchronous generator to produce electricity. The most promising prospect is
application in remote areas such as pasturing area or islands for electricity of living and industry
there. Utilization of wind power generation is mature in renewable energy field and the economic
level is close to gas based generation.

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2.3.5 Microsource Summary
Properties shown by wind microsource include:
Some microsources produce electricity with frequency much higher than 60 Hz or produce
DC electricity. These kinds of microsources have to cooperate with power electronic devices like
converters before connecting to loads.
Comparing with traditional system resources, mcrosources are of less inertia, which means
when load demand changes in the system microgrids need long responding time (10-200s). They
cannot track the load change so there need energy storage devices to balance load when there is
change.
Uncontrollable resources (solar and wind) operate mainly based on natural condition.

2.4 Storage Technologies
2.4.1 Battery[13]
2.4.1.1 Advanced Lead-Acid Batteries
These are improved versions of the 100 year old battery used to provide power for starting
vehicle engines. These batteries use lead as the anode, lead dioxide as the cathode, and a sulfuric
acid electrolyte. Advanced lead-acid batteries are considered suitable for stationary storage uses.
They are commercially available but also are being researched to, among other goals, improve
the amount of time they can be usefully discharged and recharged.
2.4.1.2 Flow Batteries

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Flow batteries—such as vanadium redox and zinc-bromide—store energy in electrolyte
solutions that are contained in external tanks. They are candidates for use in stationary storage
systems. Some flow batteries are commercially available or being demonstrated. Most types are
also being researched.
2.4.1.3 Lithium-Ion Batteries
These are batteries in which lithium ions move from the cathode to the anode during the
discharging and charging processes. These batteries are the most popular type of rechargeable
battery for use in personal electronics and increasingly for electric vehicles and stationary
storage systems. Research efforts aim to improve their energy capacity, safety, and reduce their
cost.
2.4.1.4 Lithium-Metal Aatteries
These are batteries that use lithium as the anode. They hold the potential for providing
greater energy stored per unit weight compared with lithium-ion batteries. These batteries are
currently being researched primarily for electric vehicles, although they have other potential uses.
Research aims to, among other goals, develop new materials and battery cell designs.
2.4.1.5 Sodium batteries
This is batteries that use sodium, or sodium compounds as electrodes. They are primarily
considered suited for use in stationary storage systems. Some sodium batteries are commercially
available, but others are being researched. Currently, research aims to, among other goals,
develop new materials and battery cell designs.

16

2.4.2 Flywheel
These are devices that store electricity in the form of mechanical energy in a spinning wheel
or tube. To recover power, the flywheel drives a generator. Flywheels provide high power and
quick release of energy over short durations. Flywheels are commercially available; however,
research is being done to, among other goals, find new and improved device materials.

2.4.3 Supercapacitor
These are devices that store energy in an electrostatic charge that can withstand hundreds of
thousands of charge and discharge cycles without degrading. Capacitors have been used for
small, primarily consumer electronic devices and are increasingly being developed for
high-power weaponry and commercial electric vehicles. Currently, research aims to, among other
goals, increase their energy density.

2.5 System Issue
2.5.1 Current Integration Standard
Local interconnection standards for current integration vary considerably from utility to
utility. The IEEE SC21 working group is drafting a nationwide standard. ANSI standard P1547
(Draft)Standard for Distributed Resources Interconnected with Electric Power Systems addresses
a group of DER as a Local Electric Power System (LEPS).The standard accounts for the issue of
a LEPS connecting to the utility grid (Area Electric Power System or AEPS) by focusing on the
aggregate DER rating of the LEPS. So the rules applied to a Microgrid containing many small
DER are the same as for a single large distributed energy source. P1547 applies only to single or

17

aggregate DER of 10 MVA or smaller. IEEE draft Standard P1547 applies only for safe and
reliable integration of DER into radial distribution systems with minimal immediate economic
costs, when it comes to DER operating separately from the utility grid, it does not provide the
mean.

2.5.2 System Protection
DER are always assumed to be integrated with a typical radial distribution system in
accordance with IEEE draftP1547. There will need to be several changes in existing protection
schemes. As for transformer protection, because connecting the Microgrid to a utility grid would
not affect the ability of the utility's differential protection scheme to detect and isolate a
transformer fault, no adjustments to this protection would be necessary. But for line protection,
changes are needed regarding feeder ground fault and feeder line to line fault.
DER connecting to the faulted phase would contribute to the fault and thus reduce the fault
current seen by the AEPS. However, when the fault initially happens, all but the lowest rated
DER (on all phases) would detect the fault and separate from the system. After the DER separate,
the fault current contribution from the AEPS would increase and feeder protection would be
enabled, just like the case DER is independent from the feeder. The fault detection time might be
prolonged due to the presence of DER, but the protection scheme would not need to change.
IEEE P1547 would require DER to comply with local rules regarding reclosing coordination. A
reasonable approach for utilities to perform this coordination is to set the DER units a extra time
delay after tripping off line, to make it remain off line until all disturbance and reclosing events
are done.
For DER connected to the faulted line, the voltage seen at the DER terminals would

18

probably be out of the allowable range specified inP1547, causing the DER to trip off the line.
DER operating on the unfaulted phase during a line-to-line fault would, in most cases, also
exhibit voltage outside of this range and trip off line. The detection of the fault by the utility
would not be impeded by operation of DER if the unfaulted phase voltage did not move outside
the allowable operating range. Thus all phases of the feeder would be tripped per the utility’s
normal protection scheme. At that point, all DER that remained connected would sense under
voltage or overvoltage and would immediately disconnect.

2.5.3 Voltage Regulation
Load Tap Changers (LTCs) is adopted by most distribution transformers, which can adjust
the transformer's turns ratio based on the load current to influence voltage regulation. The LTC
would see more or less current in different situations, and adjust the transformer's voltage output
to compensate for the voltage drop of the feeder. However, in a special case, if DER were located
very close to the LTC, they would have an undesirable effect on the feeder's voltage regulation,
which would have to be dealing with by adjustments to the LTC. For those distribution systems
without LTCs, the integration might cause voltage regulation problems; the utilities have to use
permanent tap change to the distribution transformer. However, for a correctly designed
Microgrid, the voltage at the interfacing point will be constant with a large range of loads and
should greatly reduce the problems of LTCs.

2.5.4 Microgrid Monitoring and Control
Integrating DER will require overhauling the conventional distribution system so that it

19

functions similarly to the traditional transmission system. To perform a successful overhauling,
the key ingredients would be as follows:
a) Frequency Supervision: When DER is independent from the transmission grid, there
would be no reference frequency for them to follow. Therefore, a real-time, global signal must be
sent to DER to constantly set and synchronize the generation frequency.
b) Dispatch Control: To ensure the power generated must equal the power used.
c) Governors control: Control the power generated up to a point beyond which more
available generation must be dispatched to meet demand. When system load approaches
available generation, an automatically control system is needed to dispatch generation.
d) Load-Shedding Control: If demand exceeds all dispatched generation, loads must be
deenergized to avoid the system becoming unstable. A Load-Shedding controller is needed to
systematically deenergize the overloads.
e) Voltage and Reactive Power Support: DER must be able to establish and support system
voltage to regulate voltage throughout the distribution system. Reactive power control is also
needed to ensure system stability.
f) Synchronizing capability: An isolated DER must be able to reattach to an energized
distribution system without an interruption in service.
g) Dynamics Management: If Microgrids are to operate isolated from the utility grid, they
must have sufficient means to stabilize system disturbances, and it will not be a matter of simply
following past practice. For example, most DERs within a Microgrid are expected to be based on
power electronics, so they will have no stored rotational kinetic energy. When a disturbance
occurs in an isolated Microgrid, the system is constrained to match generation with loads.

20

Although the rotating loads within a Microgrid do have inertia, the loads themselves will likely
be insufficient to mitigate these dynamic concerns. Microgrid would need to use dynamic
management to correct this mismatch in such a way that further system voltage or frequency
suppression would result, leading to loss of loads and instability of the system.

2.5.5 Imbalance
The effects of imbalance on end-use equipment are uneven phase heating and accelerated
aging of the equipment, and interference with the controls of intelligent devices such as
converters and relays. The imbalance in a MicroGrid comes from three sources: single-phase
loads, distorting loads, and circuit asymmetries. Single-phase loads may make three-phase
currents unequal. The unbalanced currents generate unbalanced voltages because the voltage
drop in the various phases will be unequal.
In secondary distribution circuits (208 V or 408 V level) it is common to have distorting
loads, thus generate harmonics, which are always unbalanced. They tend to generate negative
and/or zero sequence harmonics, contributing to the system imbalance.
Circuit asymmetries is also a big source of imbalances in the system. A circuit is
asymmetric if the flow of a balanced set of electrical currents through it generates three-phase
voltages that are unbalanced. The degree of imbalance in a typical practical system may be up to
six percent, measured as the percentage difference among the three phases. By doing planned
placement and arrangement of the three phases can minimize the asymmetry of the circuit and
the resulting imbalance.
In a typical customer system, all three sources of imbalance are present. The relative degree

21

of the imbalance and the specific contributions from each source depends on the system. There
are many ways to mitigate imbalance. Some key strategies are as follows.
a) Load balancing: Load balancing entails distributing single-phase loads to the three
phases in such a way that each phase will have approximately the same amount of load. However,
electrical loads are not very predictable, the method does not always effectively balance the three
phases.
b) Use of transformers: When connecting single-phase loads to two phases using
transformers, the single-phase load current is converted into positive sequence and
negative-sequence current that reduces imbalance as compared to the single phase connection.
Using transformers in combination with load balancing is an effective way to mitigate
imbalance.
c) Circuit symmetry: Circuits can be made symmetric by twisting the three phases
continuously and making sure that the three-phase arrangement is symmetric.

2.5.6 Power Electronic Interactions
The level and effects of power electronic devices interaction depend on the dynamics of the
customer system. One way to characterize customer systems is by frequency scans that
determine the impedance of the system at a specific point as a function of frequency. Frequency
scans reveal that customer systems are in general asymmetric. Asymmetries can generate
non-characteristic harmonics resulting from the interaction of converter controls and the system.
The power electronic interface of DER can be used to control and mitigate these interactions,
which depend on system impedances as a function of frequency. Customer systems may also

22

exhibit a number of harmonic resonances, which may amplify the interaction of inverters and the
system.
System asymmetries can be revealed by frequency scans of each individual phase. For
asymmetric power system, the impedance of a specific phase versus frequency will be the same
for each one of the three phases. An asymmetric system will display differences and will affect
the performance of the power electronic interface of DER.

2.5.7 Voltage Profile
The voltage profile of a customer system depends on the wire size, circuit length, and load
distribution. Secondary distribution systems operate at the two standard line-to-line voltages, 480
V and 208 V, at which voltages level the currents for typical loads are relatively high, so the
voltage drop along the circuits is relatively high compared to the nominal voltage. Typical
customer systems have circuits with relatively short lengths to minimize the voltage drop along
each and therefore improve the voltage profile. Network systems have better voltage profile
performance.
By placing the DER at strategic locations, a system’s voltage profile can always be
benefitted. DER can affect voltage profile in two ways. First is to modulating the loading of the
circuit. If a microsource is placed at the appropriate location, the current level in the circuit is
decreased, so the voltage profile can be improved. Second way is to injecting reactive power that
can boost or control the voltage magnitude. It has the similar principle as a capacitor is used to
increase the voltage magnitude in an AC circuit.

23

CHAPTER 3 UNIVERSITY PARK CAMPUS DISTRIBUTION SYSTEM REVIEW
AND ANALYSIS
University of Southern California is a private, not-for-profit research university founded in
1880 with its main campus in Los Angeles, California. USC enrolls 18,316 students in its
four-year undergraduate program. It is also home to 21,642 graduate and professional students in
a number of different programs, including engineering, business, law, social work, and medicine.
[14] Meanwhile there are 23653 faculty and staff working in USC according to data in 2013.[15]
The University Park Campus is in the University Park district of Los Angeles, 2 miles (3.2 km)
southwest of Downtown Los Angeles. The campus' boundaries are Jefferson Boulevard on the
north and northeast, Figueroa Street on the southeast, Exposition Boulevard on the south, and
Vermont Avenue on the west, 226 acres in total. The project is going to fit the critical power need
of the USC, completing an assess study of Microgrid in UPC campus which serves a community
of around 40,000 people and encompasses a wide array of building types (residential, office,
research, classroom), transportation options (automobiles, buses, shared-cars, bicycles), and a
wide array of distributed energy resources.

3.1 Energy Infrastructure and Usage
There are a variety of heating and cooling systems in 195 academic buildings, dormitories,
and off campus University residences around University Park Campus. The HVAC system uses
natural gas-burn boilers for heating the room space areas. The natural gas consumption for Fiscal
Year 2013 within the whole campus is as below:

24

Month Comsumption
(MMBtu)
May 20,568.8
June 16,570.0
July 15,477.5
August 13,410.5
September 13,866.5
October 18,307.8
November 25,285.9
December 32,039.8
January 35,223.8
February 31,103.0
March 28,602.6
April 24,294.0
Total 79,893.3
Table 1. Fiscal Year Natural Gas Consumption

25

Figure 6. 2013 UPC Natural Gas Usage
Since majority of natural gas consumed in USC is mainly for room heating, consumption
quantity is obviously higher in relatively cold months as from November to March, which
exceeds 20,000 MMBtu. According to average rate for Natural Gas of $4.71/MMBtu, the total
fee for natural gas is $376,397.44 in fiscal year 2013.
For room space cooling, there is a 3.2 million gallon thermal energy storage system 40 feet
below Cromwell Field which is made of 2,310 cubic yards of pre-stressed concrete. This
massive tank circulates chilled water throughout the buildings on campus to cool them and
reduce air conditioning costs.
0.00
5,000.00
10,000.00
15,000.00
20,000.00
25,000.00
30,000.00
35,000.00
40,000.00
MMBtu
UPC Natural Gas Usage of Fiscal Year 2013

26

Figure 7. Thermal Energy Storage Tank
There are 9 chillers as shown in the table below running for producing chilled water. When
electricity rates are lower at night, the water is stored in the tank and chilled. During the day,
while electricity costs are at their peak, this chilled water is then circulated throughout campus
and electricity consumption decreases.

Chiller Identification Rating(ton)
DML Chiller-1 350
LAW Chiller-1 375
LAW Chiller-2 375
PED Chiller-1 1280

27

PED Chiller-2 750
SSC Chiller-1 250
SSC Chiller-2 250
VHE Chiller-1 560
TCC Chiller-1 1500
Table 2. Chiller Ratings

Figure 8. Chiller System
A pump house beneath Grace Ford Salvatori Hall services the thermal energy storage
system and regulates the flows of the system throughout campus. The storage tank saves the
university an estimated 4,500 megawatt-hours of electricity a year, which equates to about
$400,000 of electricity costs saved. Saving electricity reduces CO
2
emissions, and the amount

28

of electricity saved by this storage tank equates to the quantity of emissions produced by
approximately 615 cars annually.
Cromwell Field is covered with synthetic turf that provides numerous sports teams,
individual athletes, and the Trojan Marching Band with a place to practice. The field saves
energy and resources by eliminating the need for watering, mowing, and replanting.[16]
Providing running of energy infrastructure, electric vehicle charging stations, labs,
classrooms and dormitories, UPC campus has a total electric utility cost of $15Million per year.

3.2 Electrical Infrastructure
The structure of existing USC distribution system is shown in the figure below.

Figure 9. USC Distribution System
The electric service for the UPC campus has already experienced a history of changes and
steady growth that defines its present characteristics. The campus is served directly from two

29

LADWP 4.8 kV distribution stations, Jefferson and Biegler, which enter the UPC campus.
Jefferson Station locates in Building EVB and Biegler Station is in EVA. Each of these two
distribution stations has two services and separated into 19 sub ‐circuits in total that feed the
campus. Throughout the campus there are 114 first level transformers which transform the 4.8
kV voltage from LADWP distribution station into 480V and 208V. Then around the first level
transformers there are 118 second level ones producing the needed voltage value by specific
loads such as 277V and 120V.
3.3 Load Profile
Supporting energy usage of the whole campus with labs, classrooms, libraries, dormitories
and other facilities, UPC campus has a peak load power of 20.62MW and peak energy of 410
MWh per day.
The figure below shows average daily electric consumption in 2013. From the figure,
consumption is higher from June to October which is above 300 MWh per day. That’s because
central cooling system is on most of the time for a comfortable temperature of 76 degrees in
summer time. December shows the lowest because there are less students, faculty and staff in
campus when final exams start.

Figure 10. Average Daily Electric Consumption
0
100
200
300
400
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MWh
Average Daily Electric Consumption

30

The figure below indicates an hourly electric usage in a September week. Monday to Friday
has higher load profile obviously than weekends. And load goes up from morning time to noon,
which turns out as the first peak, then it falls down with a large slope. This is due to the energy
plan from USC facility Management Services according to variable electricity rate. And after 5
pm there shows a second small peak, this is because all chillers are in service from this time on.

Figure 11. Hourly Electric Usage in a September Week
Time-of-Use rates are based on the time of day that people use electricity. During the base
hours (Off Peak Hours), when customer use is low, electricity price will be lower than the
standard (non-Time-of-Use) residential rate. Prices during the low peak hours are slightly higher
than standard rate. In the high peak hours (On Peak Hours), the cost to supply energy is the
highest, and it will cost more than the standard rate.[17]
Specifically, some of the chillers are on during 7 am to 1 pm for remaining running cooling
system throughout the whole campus. Before 1 pm, for the reason of regulating rate, all chillers
are off since electricity rate has the highest value from 1 pm to 5 pm. After 5 all chillers are on
until 7 am to utilize the cheapest electricity chilling water.
6
8
10
12
14
16
18
20
0 7 14 21 4 11 18 1 8 15 22 5 12 19 2 9 16 23 6 13 20 3 10 17
MW
Hourly Electric Usage in a September Week
Sun Mon Tue Wed Thu Fri Sat

31

Figure 12. Chillers Running Time

32

CHAPTER 4 USC MICROGRID CONCEPTUAL PLAN AND MODELING
4.1 Plan Objective
Planning a whole microgrid within the area of CERTS concept requires microsourses has a
capacity larger than peak load of the grid in order to supply the full system when it operates in
island condition. UPC campus has a peak load of 20.3MW, which cannot be compensated by
only solar resource, which has sufficient resource in Southern California, has no operation and
maintainence fee and no pollution. Other distributed generations that can produce MWs of power
to meet the 20 MW load consumes fossil fuel and lead to air pollution. California Cap-and-trade
Program, which is a market based regulation that is designed to reduce greenhouse gases (GHGs)
from multiple sources, sets a firm limit or “cap” on GHGs and minimize the compliance costs of
achieving AB 32 goals. So large gas turbine is prohibited in central Los Angeles area. And this
situation limits the capability of USC microgrid design.
Basing on the limitations of source selections, the goal of this project planning is set to meet
critical load need in grid contingency. And assess operation economy with distributed generation
integrated.

4.2 Critical Load in UPC
195 buildings within UPC campus are categorized into several types: laboratory, academic,
parking structure, residential, and others. In this project, laboratory, academic and residential
buildings are regarded as critical loads which acts as most crucial roles in the university. There
are 14 laboratory buildings, 98 academic buildings, and 14 residential buildings taken in to
consideration. They have total peak load of 5.98 MW. List of buildings in every categorize is in

33

appendix.
4.3 Resource for USC Microgrid
4.3.1 Solar
California has a tremendous supply of renewable resources that can be harnessed to provide
clean and naturally replenishing electricity supplies for the state. And Los Angeles locates where
contains best residential and commercial solar potential. Figure 1 shows photovoltaic solar
resources of the United States.

Figure 13. Photovoltaic Solar Resource of the United States

34

The solar resource data of Los Angeles (34.0205° N, 118.2856° W) can be obtained from
the NASA Surface Meteorology and Solar Energy[18]. The annual average solar radiation of Los
Angeles area is about 5.41 kWh /m
2
/day with in the whole year.
California is striving to create megawatts of new solar-generated electricity, moving the
state towards a clean energy future. With this social environment, LADWP is reaffirming its
commitment to the environment, renewable energy, and the local economy by constructing
photovoltaic systems, offering customer incentives of $2.85/Watt.
With such sufficient natural resource and political support towards solar energy, USC has a
tremendous potential for rooftop photovoltaic. Basing on conditions of building height, rooftop
condition and surrounding environment, PV capacity potential can be estimated accordingly. The
Los Angeles County Office of Sustainability (COS) assessed rooftop solar potential within this
county and data is opened to public. 2006 Solar Radiation model is used in this map calculation,
which calculates and ranks incoming solar radiation every 25 square feet in the county, using
roof pitch, orientation, and shading from surrounding structures and trees to provide the best
estimates possible. Potential system sizes are calculated from the optimal roof area and panel
specifications based upon the SunPower 225 panel delivering 207 W/m
2
. The carbon dioxide
emission reductions from Southern California are 724 lbs of carbon dioxide reduced for every
MWh of solar electricity. This value is used in the calculation for potential annual emissions
savings. Conversion efficiency is 82% in this case.[19]

35

Figure 14. Solar Acception Condition
UPC area is divided into 13 sub areas in the system. Each area contains solar PV potential
varies from 12 .1kW AC to 2477.2 kW AC. Totally the assessed value is 5117.9 kW AC on total
roof area of 2,066,216 square feet. Electric savings is $967,776 per year with electricity
produced of 6,048,596 kWh/year. Carbon savings by this estimation is 552,205 lbs/year. Figure
below shows the solar map in middle of UPC campus. Red points stand for excellent solar
potential which is above 4.9 kWh/day. Yellow points are for 4.0 to 4.9 kWh/day which are also
considered as good conditions. Green and blue points are spaces have potential less than 4.0
kWh/day which are poor and not advisable indicators.

36

Figure 15. Solar Map
Basing on data of the 13 sub areas offered by the map system in UPC campus, together with
graphical status of each building, further estimation is conducted for every building. 38 buildings
within campus are chosen to be objects of installing photovoltaic panels. Considering error of the
solar map and estimation of each building solar potential, a factor of 0.9 is used for a safe plan.
Total photovoltaic panel capacity is calculated as 3.82MW AC output.
Building
ID
Circuit Capacity
(kW)
Building
ID
Circuit Capacity
(kW)
Building
ID
Circuit Capacity
(kW)
SEL N 88 ACB S,H 28 DMT H,P 88
MRF N 88 LAW H 180 DEN E,K 285
DCC N,I 88 BRI A 88 HER Q 156
PSD N 340 ACC A 88 OHE B 12
BIT K 88 HOH H 88 PRB M,F 84
PED K,E 268 AHF T 88 IRC M,F 120
THH P 88 LRC J,Q 20 GER D 120

37

ADM I,K 88 JKP P 88 WTO L 12
BKS A 88 DML A,P 84 PSB L 12
STU I 85 VKC P 128 KAP M,J 108
RRB A 88 LVL N,I 88 DRB M 120
SHS S,H 28 PTD A,P 84 PSA D 34
SLH S,H 28 BSR H,P 168
Table 3. Solar Panel Capacity
To get the most from solar panels, they need to be pointed in the direction that captures the
most sun. Solar panels should always face true south when in the northern hemisphere. Solar
panels are assumes to be fixed tilt angle because of its economic feature.
The formulas to find the best angles form the horizontal at which the panel should be tiled
are based on the latitude. Latitude of USC is 34.02 °N. The formula accordingly is:
Optimal Tilt Angle = Latitude × 0.76 + 3.1(degree)
So the optimal tilt angle for USC area is:
34.02 × 0.76 + 3.1 = 28.96(degrees)

4.3.2 Other Resources
Microturbines have small number of moving parts, compact size, low emissions and
relatively low installed and O&M costs. So Microturbines are used for compensating critical load
in UPC campus assisting solar energy.
4 MW microturbine capacity is taken in to consideration. Each MW of microturbines are

38

installed near each of the four LADWP services, because there is no main transformer in charge
of the whole campus. Power produced by the microturbines can be transmitted to different
circuits and then transform into different voltage levels according to the load need.
Batteries are used when necessary for energy storage device, especially when there is a
system issue in the bulk grid and UPC grid isolates as a microgrid. Energy storage system can
store energy when the system operate normally. During transient time domain, there may be
power fluctuation from sources and loads. The battery can serve as an energy supplier to smooth
the system and keep its stability.
The energy stored in the battery can be used either for tariff based rate arbitrage or power
quality and reliability. When grid connected, the battery can charge or discharge as dictated by
the Energy Management System in order to maximize the economic benefit of the battery. The
rate arbitrage scheme is based on the utility tariff structure and not on real time pricing. During a
grid disturbance or outage, the energy in the battery is used to continuously supply high quality
power to the on-site loads.
The battery is sized at 1MWh to be able to serve the facility demand. This would allow the
facility to island from the utility grid when the microturbine or part of the PV system are on-line,
but may require load shedding in the unlikely event that all PV inverters and the microturbines
are offline. The 1MWh storage capacity was sized such that on a typical summer day the battery,
and solar photovoltaics could serve critical load peak-period energy usage. This provides enough
energy to maintain the system until the all microturbine generators start, if required.
A power conversion system is required to interface the PV arrays and battery with the
Microgrid and utility source. The installed PCS is rated 5MW. This system architecture makes
the system highly flexible, allowing for proper maintainability and testing. The PCS was sized

39

such that it could supply some, but not all of the facilities reactive power needs. When
grid-connected, the EMS dispatches charge or discharge signals to the PCS to provide the highest
level of economic benefit to the campus. During the transition from grid-connected to island, the
PCS remains connected, operating as a voltage source, even if the voltage and/or frequency are
outside normal operation limits. The transient recovery voltage period is typically within one
cycle, but may last several cycles depending on the circumstances of the islanding process.
During this time, the PCS is constrained only by its internal current and power limiting
functions.

4.4 UPC Modeling
4.4.1 DEW Software
This project utilizes DEW (Distribution Engineering Workstation) software developed by
Electrical Distribution Design Inc. The company is funded and supported by Electric Power
Research Institute (EPRI) to service EPRI members who are mostly utility companies. The DEW
Software package hosts an Integrated System Model, which allows clients to build large,
complex models with advanced features unavailable in any other product. The software is
structured into a suite of core application modules and optional extensions. Core modules, which
are included in every installation, allow users to construct a fully functional integrated system
model and run basic analysis applications. The extension modules add more specialized analysis
packages, developed to meet specific customer needs and areas of interest.
The DEW software suite provides proven analytical tools to solve the largest distribution
system problems. All commonly offered analytical tools are included, as well as many tools for
enhancing the smart grid that cannot be found elsewhere. EDD software applications have been

40

verified in journal publications and validated in numerous field tests conducted by national labs
and multiple utilities. The DEW models and applications are utilized from the design and
planning stages to real-time analysis and operational controls, delivering a complete tool that
addresses key smart grid challenges identified by the Electric Power Research Institute.
4.4.2 UPC Model
The UPC model in DEW include 4 LADWP services as substations, circuits, breakers, bus
bars, feeders, distributed cables, disconnect switches, distribution transformers and load of the
existing USC grid, plus added photovoltaic resources and microturbines in this plan project.
Figure below shows the entire graph of the system. Different colors represent each circuit.

Figure 16. UPC Distribution System Model

41

Distribution substations contain information of the voltage level which is 4.8kV from
LADWP.

Figure 17. Distribution Substation Input
Breakers have parameters of current rating, current interrupting rating, instantaneous rating
and cycles to open and extinguish arc as shown below.

42

Figure 18. Breaker Input
Cables require configuration including phase position, phase wire, neutral wire and earth
type. Conductor material, conductor radius, geometric mean conductor radius (GMR), jacket
diameter, insulation diameter, current ratings for overhead, conduit and direct buried typs,
construction, resistance, temperature are asked for building cable library. Neutral construction
information including neutral strand resistance, neutral strand bundle diameter, neutral strand
radius, number of neutral strands, geometric mean radius of neutral strand and voltage range are
also required for cables.

43

Figure 19. Cable Input
Continuous current rating, load interrupting rating and fault/fused interrupting rating are
required for building switch library.
Distribution transformers require transformer type, phases, transformer connections,
nonminal power rating, summer normal rating, summer emergency rating, winter normal rating,
winter emergency rating, nominal primary phase voltage, and nominal secondary phase voltage.

Figure 20. Transformer Input
Load takes only total active power and reactive power of each phase. Here the whole system
is assumed to be balanced system with a global power factor of 0.87. This power factor value is
the common value used at USC FMS (Facility Management Service).

44

Figure 21. Spot Load Input
Solar resources are taken as inverter type distributed resources in DEW. For adjusting
output power for every building, measurement controlled P&Q output is used as control type.
12:00 pm, September 4
th
2013 is taken as the selected measurement time because this is the peak
load spot of 2013 and will be selected as the time for analysis when running the system. If peak
load can be picked up without an issue, the microgrid will be considered applicable.
Four 1 MW microturbines stand by synchronous generators are added under stream of
LADWP distribution services representing the power they provide.

45

Figure 22. Model Instance

4.5 System Analysis
In DEW software, circuits are run separately to analysis power flow, which means the
unselected circuits are open from the distribution services. Table below shows circuits under
every LADWP 4.8 kV distribution service.
Service ID Circuit ID
Biegler 1 Circuit A, B, C, G, I
Biegler 2 Circuit D, E, F, H, J
DWP 1 Circuit K, L, M, S, T
DWP 2 Circuit N, P, Q, R
Table 4. Circuits distribution
Loa Modeling is Constant P and Q since this is power flow calculation for one snapshot.

46

Convergence tolerances are set as 0.5% for volt difference, 0.05% for current change and 300
max number of iteration.
Figure below shows the power flow through each component from DWP Service #1 of
every phase.

Figure 23. Power Flow Result
The summary report gives bus voltages, connected loads, total losses, native load, total
feeder flow and bus current flow. Highest voltage, lowest voltage, largest overload and largest
imbalance and most overloaded distribution transformers are listed in the summary also.
The lowest voltage is 119.67V on 120 Base, which is within limit of voltage range. Power

47

flow of the total system can be calculated using superposition method. The four distribution
systems are like fours independent resources. Comparing power flow results with added
distributed generations and only the existing USC system, an obvious flow difference come up.
Under condition of existing USC infrastructure system, the power loss is 308.4 MVA within the
grid. This value decreases into 274.24 MVA with distributed generation, which is a deduction of
11.08%. This is the most apparent advantage of DG. Because resources are located just near the
load, there will be much less power running through distribution lines, cables and other elements,
which will consume a certain quantity of active and reactive power because of their impedance.
Such a reduction in power loss is a signal of saving of fuel and money, also an indicator for less
air pollution emission.
The total feeder flow which is flow through each circuit is decreased by 9.89% because of
the photovoltaic panels which are installed at downstream side of feeders. This means, the
utilization of solar energy avoids power from the grid by more than 3MW. This is a economic
advantage in a long run.

4.6 Microgrid Model and Analysis
This model is to simulate when there is a system issue in the bulk grid, the campus system
has to be islanded from the whole grid to operate under an islanded condition. Only critical loads
are served in this case, including 14 laboratory buildings, 98 academic buildings, and 14
residential buildings. Analysis time is taken to be the peak load of 2013, which is 12:00pm
September 4
th
with total critical load of 5,980 kW. All photovoltaic panels and microturbines are
on. Exceeded energy can be stored in the batteries. Again, load modeling is set to constant P and
Q because this is a snapshot run. Convergence tolerances are 0.5% for volt difference, 0.05% for

48

Current Change and 300 as max number of iterations.
Lowest voltage is 119.61V on 120V base, which is within the limitation. All four services
can be substituted by photovoltaic and microturbines. So this plan is applicable under island
condition. Power flow reports are in appendix.

49

CHAPTER 5 OPERATION ANALYSIS
5.1 HOMER Software
Operation analysis is studied using HOMER. HOMER is a computer model that simplifies
the task of designing distributed generation (DG) systems - both on and off-grid. HOMER's
optimization and sensitivity analysis algorithms allow users to evaluate the economic and
technical feasibility of a large number of technology options and to account for variations in
technology costs and energy resource availability. Originally designed at the National Renewable
Energy Laboratory for the village power program, HOMER is now licensed to HOMER Energy.
HOMER provides the detailed rigor of chronological simulation and optimization in a
model that is relatively simple and easy to use. It’s adaptable to a wide variety of projects. For a
village or community-scale power system, HOMER can model both the technical and economic
factors involved in the project. For larger systems, HOMER can provide an important overview
that compares the cost and feasibility of different configurations; then designers can use more
specialized software to model the technical performance.
HOMER is accessible to large set of users, including non-technical decision makers.
Chronological simulation is essential for modeling variable resources, such as solar and wind
power and for combined heat and power applications where the thermal load is variable.
HOMER’s sensitivity analysis helps determine the potential impact of uncertain factors such as
fuel prices or wind speed on a given system over time.

5.2 Modeling
The proposed hybrid power system is schematically shown in figure below. The

50

components include grid, generator, PV panels, converters, battery and UPC load.

Figure 24. Equipments in HOMER
Installing for microturbine is considered 1,650$/kW. And cost for O&M and replacing cost are
assumed as 0.016$/kWh and 1,320 $/kW. This data is from Oak Ridge National Laboratory. [20]
Sizes to consider are 0, 2000 and 4000 kW. This is for assessing the plan for this microgrid in
different configurations. Fuel for the microturbine is chosen to be natural gas, which has an
intercept co-efficiency of 0.097 per cubic meter per kWh from the data of
www.kylesconverter.com. Price for natural gas is 0.249 $/m
3
. This value is from US Energy
Information Administration. From HOMER library, natural gas has lower heating value of 45
MJ/kg, density of 0.79 kg/m
3
, carbon content of 67% and sulfur content of 0.33%.
Grid input in mainly real time price of electric. This data is calculated using LADWP
electric rate affecting in 2013. USC belongs to subtransmission service A-3(A), which is
applicable to general service delivered from the department’s 34.5 kV system and 30 kW demand
or greater. Electric rate varies hourly basing on season, highest demand in the last 12 months,
maximum demand within the applicable rating period during the billing month and energy usage
in every period.
Take low peak period in September, which locates the peak load demand of the year, as an

51

example. The real time rate is composed of the following variables:
Service charge per month: $75
Facilities charge per month: 4 $/kW
High peak period demand charge: 9 $/kW
Low peak period demand charge: 3 $/kW
Low peak period energy charge: 0.03764 $/kWh
Energy cost adjustment: 0.05690 $/kWh
Electric subsidy adjustment: 0.46 $/kW
Reliability cost adjustment: 0.96 $/kW
Low peak period reactive energy charge: 0.00017 $/kWh
Demand peak in the last 12 months: 20,620 MW (assumed to be the same with 2013)
Highest high peak period demand in September: 19,070 MW
Highest low peak period demand in September: 20,620 MW
Month total energy usage: 10,646 MWh
The calculation for electric rate during this period is

52

( ℎ + ( ℎ + + ) ∗ +
ℎ ℎ ∗ ℎ ℎ ℎ + ℎ ∗
ℎ )
/Month total energy+Low peak energy charge+ESA

=
75 + (4 + 0.46 + 0.96) ∗ 20.62 ∗ 1000 + 9 ∗ 19.07 ∗ 1000 + 3 ∗ 20.62 ∗ 1000
10646 ∗ 1000
+ 0.03764
+ 0.0569 = 0.1270 $/ ℎ
Considering tax and other fees, this rate is finally 0.1745 $/kWh.
This calculation is conducted for three time periods of 12 months. Figure below shows the
power price daily profile within the whole year 2013. During low seasons (October to May)
energy charge for high peak period and low peak period are the same while there is a 0.6 cent
difference in high seasons (June to September). That’s the reason why from June there are three
levels of power price while other months have two.

Figure 25. Hourly Electric Rate Plot

53

Hourly load data of UPC campus is imported to Homer. Figures below shows scaled data
monthly averages and load map.

Figure 26. Hourly Electric Load

Figure 27. Electric Load D-Map
The calculated average consumption is 315,655 kWh/day with an average load power of
13,152kW.

54

Costs for converters are assumed as 165$/kW capital cost with the same replace cost and
40$/kW/year of O&M cost. 15 year is considered as lifetime for converters with an efficiency of
90%.
No tracking PV system has capital cost of $3066 per kW. The replace cost is assumed to be
2628 $/kW with no O&M fee. Photovoltaic panels have a lifetime of 20 years with derating
factor of 80%. Slope is 28.96 degrees as calculated before. 4 levels of 0, 1000 kW, 2000 kW and
4000 kW are considered when operating.
A battery of 1MWh is used in this model with a capital cost of 5000$ each unit. O&M fee is
100$ per year. From perspective of system flexibility, 0, 2, 4, 8 batteries are considered as
different configurations.
Solar data is from Atmospheric Science Data Center (ASDC) at NASA Langley Research
Center. The annual average solar energy is 5.42 kWh/m
2
/day. The clearness index is equal to the
global solar radiation on the surface of the earth divided by the extraterrestrial radiation at the top
of the atmosphere. In other words, it is the proportion of the extraterrestrial solar radiation that
makes it through to the surface. It varies from around 0.8 in the clearest conditions to near zero
in overcast conditions. The monthly average clearness index may vary from near 0.8 down to
maybe 0.2.

55

Figure 28. Daily Solar Radiation in USC

Figure 29. Daily Solar Radiation in USC

56

Figure 30. Hourly Solar Radiation in USC
5.3 Analysis
5.3.1 Original System Analysis Result
The original system has a total net present cost of $234M with all of the cost are originated
from operation. Levelized cost of energy is 0.135 $/kWh. Operating cost is $15,568,598/year.
The system has a emission of carbon dioxide of 72,815,296 kg/year. And the emission for
sulfer dioxide is 315, 687 kg/year and for nitrogen oxides is 154,387 kg/year.

5.3.2 System with DG Analysis Result
Total net present cost for the planned system is $238,507,008 and the levelized cost of
energy is 0.138 $/kWh. In total it has operating cost of 14,587,762 $/year. Operating cost is less
than the existing system. But while the system requires capital cost and replacement, the COE is

57

higher.
This simulation is for the situation that all planned devices are installed but still run with the
optimal economy, so the microturbines are not always on. Throughout the whole year PV array
produce electricity in a fraction of 7% and microturbine produces 13%. PV array has a mean
output of 870 kW and mean output of 20,875 kWh/d. The capacity factor is 22.8%. This value
matches the tipycal capacity factor in California. PVs operate 4,389 hours per year.
Microturbines are on 3,650 hours a year in the optimal situation with 122 starts a year.
Marginal generation cost is 0.0242 $/kWhyr. They consump 2,832,400 m
3
/year natural gas. Fuel
energy input is 27,969,950 kWh/year.
Energy charge for the grid will be $12,115,984, more than $2M less than the existing
system.
From environmental perspective, there will be 64,717,256 kg/year carbon dioxide,
18.411kg/year carbon monoxide, 2,039 kg/year unburned hydrocarbons, 1,388 kg/year
particulate matter, 271,323 kg/year sulfur dioxide and 289,913 kg/year nitrogen oxides in total.

5.3.3 Comparison
Existing system has a lower Net Present Cost since it has only operation cost while the new
system with DGs in has a initial capital cost of $19M. With a return on investment of 4.84% and
internal rate of return of 3.84%, the planned system has a simple payback of 15.1 years. Figures
below show the planned system cash flow and difference between planned system and the
existing system cash flow.

58

Figure 31. Planned System Cash Flow

Figure 32. Cash Flow Difference

59

Figure 33. Cumulative Cash Flow

60

CHAPTER 6 CONCLUSIONS
An assessment of upgrading USC University Park Campus is completed from energy
perspective. After analysis of existing USC grid infrastructure, distributed generation potential
and load profile, photovoltaic and micro turbine basing on natural gas are selected and quantified.
After modeling and simulation of the planned system, both scenarios of new system and
microgrid under emergency have basic reliability to serve peak load. An economic analysis is
conducted for the planned system. However, some issues with this plan need to be addressed in
the future work:
1) Brand and model of equipments are not decided. This issue needs to be done basing on
market price and incentives from LADWP.
2) Control systems of microgrid are not concerned in this project. To complete a full
function microgrid, control system for energy management is a must.
3) System design is conducted basing on load of 2013. Redundancy should be considered
for several years when the real system starts.

61

APPENDIX

62

Economy Analysis Report

63

64

65

66

67

68

69

REFERENCES
[1] P. Asmus et al. “Microgrids Islanded Power Grids and Distributed Generation for Community, Commercial,
and Institutional Applications,” Pike Research, Rep. 4Q, 2009.
[2] R. H. Lasseter, A. Akhil, C. Marnay, et al, “The CERTS microgrid concept,” White Paper for Transmission
Reliability program, Office of Power Technologies U.S. Dept. Energy, Apr. 2002.
[3] IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE Std 1547.2-2008,
2009.
[4] “Summary Report: 2012 DOE Microgrid Workshop,” Office of Electricity Delivery and Energy Reliability
Smart Grid R&D Program. Chicago, IL, Rep. Jul. 2012.
[5] J. M. Guerrero, L. J. Hang, J. Uceda, "Control of Distributed Uninterruptible Power Supply
Systems," Industrial Electronics, vol.55, no.8, pp.2845,2859, Aug. 2008
[6] A. M. Salamah, S. J. Finney, B.W. Williams, "Autonomous controller for improved dynamic performance of
AC grid, parallel-connected, single-phase inverters," Generation, Transmission & Distribution, vol.2, no.2,
pp.209,218, Mar. 2008
[7] K. D. Brabandere, B. Bolsens, V. J. Keybus, A. Woyte, J. Driesen,; R. elmans, A Voltage and Frequency
Droop Control Method for Parallel Inverters," Power Electronics, vol.22, no.4, pp.1107,1115, Jul. 2007
[8] M. N. Marwali, A. Keyhani, "Control of distributed generation systems-Part I: Voltages and currents
control," Power Electronics, vol.19, no.6, pp.1541,1550, Nov. 2004
[9] Karlsson, P.; Svensson, J., "DC bus voltage control for a distributed power system," Power Electronics, IEEE
Transactions on , vol.18, no.6, pp.1405,1412, Nov. 2003
[10] V. A. Boicea, “Gas Turbine and Automotive Industry,” in Essentials of Natural Gas Turbines. 2013, ch. 2, pp.
1-20.
[11] L. Blomen and M. Mugerwa, “Fuel Cell Systems,” in Fuel Cell Systems. New York: Plenum Publishing, 1993
[12] G. Simons and J. M. Cabe, “California solar resources in support of the 2005 integrated energy policy report,”
Research and Development Energy Research and Development Division California Energy Commission, Rep.
Apr. 2005.
[13] “Batteries and Energy Storage,” United States Government Accountability Office, Rep. Aug.2012.

70

[14] University of Southern California. (2013). USC Student Figures 2012-2013 [Online]. Available:
http://about.usc.edu
[15] University of Southern California. (2013). Facts and Figures [Online]. Available: http://about.usc.edu/facts/
[16] University of Southern California. (2013). Cromwell Track and Field Thermal Energy Storage System [Online]
Available: http://green.usc.edu/content/cromwell-track-and-field-thermal-energy-storage-system
[17] Los Angeles Department of Water and Power. (2013). Electric Rates [Online] Available:
https://ladwp.com/ladwp/faces/wcnav_externalId/
[18] Atmosphere Science Data Center. (2009). NASA Surface Meteorology and Solar Energy [Online] Available:
http://eosweb.larc.nasa.gov.sse.
[19] Green LA County. (2014). How Solar Estimates Were Derived [Online] Available:
http://solarmap.lacounty.gov/content/map/solarDetails.html
[20] “Advanced Microturbine System: Market Assessment,” Energy and Environmental Analysis, Inc. Arlington,
Vi, Rep. May 2003.

71

BIBLIOGRAPHY
[1] P. Asmus et al. “Microgrids Islanded Power Grids and Distributed Generation for Community, Commercial,
and Institutional Applications,” Pike Research, Rep. 4Q, 2009.
[2] R. H. Lasseter, A. Akhil, C. Marnay, et al, “The CERTS microgrid concept,” White Paper for Transmission
Reliability program, Office of Power Technologies U.S. Dept. Energy, Apr. 2002.
[3] IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE Std 1547.2-2008,
2009.
[4] “Summary Report: 2012 DOE Microgrid Workshop,” Office of Electricity Delivery and Energy Reliability
Smart Grid R&D Program. Chicago, IL, Rep. Jul. 2012.
[5] M. Bollen and F. Hassan, “Power System Performance,” in Integration of Distributed Generation in the Power
System. Hoboken, New Jersey: John Wiley & Sons, Inc., 2010, ch. 3, sec. 1-7, pp. 84-102.
[6] A. Keyhani, “Power Grid and Microgrid Fault Studies,” in Design of Smart Power Grid Renewable Energy
Systems. Hoboken, New Jersey: John Wiley & Sons, Inc., 2011, ch. 8, sec. 1-9, pp. 467-531.
[7] S. Voutetakis et al, “System Design and Optimization,” in Design, Optimization and Control of Stand-Alone
Power System using Renewable Energy Sources and Hydrogen Production. New York: Nova Science
Publishers, Inc., 2011, ch. 5, pp. 151-179.
[8] P. Mancarella and G. Chicco, “Distributed Multi-Generation Systems: Structures and Schemes” in Distributed
Multi-Generation Systems Energy Models and Analyses. New York: Nova Science Publishers, Inc., 2009, ch 2,
sec. 1-4, pp 15-26.

Abstract (if available)

Abstract Comparing with traditional unidirectional energy flow from utilities, microgrid is based on distributed energy resources, effectively realizes environmental friendly energy cascade utilization as a promising method to enhance electric power reliability, security, flexibility and economical efficiency. At present, there is a need to develop the existing distribution system in University of Southern California for fitting the new technology and offer Smart Grid research conditions for faculty, staff and students. ❧ To accommodate the high demand of system development, the assess and plan of microgrid has been studied using Distribution Engineering Workstation and HOMER. Photovoltaic and microturbines are chosen to be microsources. Simulation results for both power flow and general analysis show case studies of existing, planned and islanded microgrid configuration of University Park Campus. The capability, economy and emissions are discussed. ❧ This study put up with an outline for energy plan in USC when developing the distribution system. It will help with the design and construction as an applicable reference.

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Asset Metadata

Creator Ding, Mengna (author)

Core Title USC microgrid development conceptual plan

School Viterbi School of Engineering

Degree Master of Science

Degree Program Electrical Engineering

Publication Date 04/30/2014

Defense Date 03/12/2014

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag microgrid,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Beshir, Mohammed J. (committee chair), Jonckheere, Edmond A. (committee member), Maby, Edward W. (committee member)

Creator Email mengnadi@usc.edu

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