local green teams - galvin electricity...

1540-7977/11/$26.00©2011 IEEE66 IEEE power & energy magazine january/february 2011

Local Green Teams

Digital Object Identifi er 10.1109/MPE.2010.939164 Date of publication: 21 December 2010

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january/february 2011 IEEE power & energy magazine 67

SSMART GRID HAS BECOME ONE OF THE MOST COMMON AND well-known terms in the fi eld of power systems. A smart grid is usually thought of as a next-generation grid that can potentially optimize energy effi ciency and provide tools for minimizing environmental problems and preparing for fossil fuel depletion. Whether one is engaged in power systems or not, it is not diffi cult to envision numerous wind turbines and solar power panels near towns in the future. Little is known, however, about how such systems can be operated and controlled so as to use the new resources with optimal effi ciency. To achieve this goal, it is necessary to enable two-way exchanges of real-time information between energy suppliers and consum-ers by applying IT technology. In addition, in order to improve the opera-tional effi ciency of the transmission and distribution systems, it is essential to accept that dispersed generation systems enhance power quality and opti-mize facility investment. Technologies for operating and controlling distri-bution systems are especially important because they are directly affected

by new facilities and information (dispersed generation, advanced metering infrastructure, and so on). Together, these technological opportunities can be used to support local community sustainabil-ity initiatives. In fact, local community sustainability initiatives and the social change they represent are important drivers for the adoption and usage of smart grid systems.

The Republic of Korea and the State of Illinois are jointly exploring shared opportunities for smart grid development and deployment that can support local community sustainability initia-tives and bring the promised benefi ts to citizens of both Korea and Illinois. In this article, we highlight local community sustainabil-

ity and economic development initiatives in Illinois that can be supported by smart grid systems, and we discuss opportunities inherent in the design and verifi cation of the Korea Smart Power Grid for communities planning to implement smart grid solutions.

Supporting Community Sustainability Initiatives in Illinois with Smart Grid SystemsLocal communities in Illinois, including Oak Park and Naperville, are seeking sustainable economic development approaches that offer real, last-ing benefi ts to the local environment and improve the quality of life in the community. Local sustainability approaches focused on resource conserva-tion and awareness and tailored for the community’s specifi c needs can help local governments and citizens manage energy costs, reduce the production of harmful emissions, create jobs, and strengthen the local economy.

Emerging smart technologies can potentially enable individuals and businesses alike to more easily participate in communitywide smart energy efforts by creating opportunities for customers to monitor and control the quantity of energy they use to live and work, generate and store energy from multiple sources, and manage the amount and timing of their use of that energy.

A well-designed “smart energy community” program will identify and test applications that develop sustainable models to deliver technology to end users in a way that empowers consumers and businesses to reduce energy consumption, cut emissions including carbon, and reduce the economic bur-den that energy consumption places on communities and the grid. Because these technologies are still developing and emerging, a smart community

By I.-K. Song, K.-D. Kim, J. Kelly, and C. Thomas

Implementing Smart Communities in Illinois and Korea

68 IEEE power & energy magazine january/february 2011

test-bed project will be useful to identify new business mod-els and fi nancing options that will help develop sustainable models for larger-scale future deployment of new energy- and emissions-saving technologies that can also lower utility bills and increase grid stability.

In short, local community goals of reliability, carbon emission reduction, diversifi cation of energy sources, and cost reduction suggest that local microgrids can be used to

create a new model for the generation, use, and delivery of electric power that is more effi cient, sustainable, robust, fl ex-ible, and environmentally sound and that encourages a much higher level of consumer participation and control.

The key to effective smart grid programs is deploying advanced technology in a smart way. Peter Senge, in his widely acclaimed book The Fifth Discipline, introduced the concept of systems thinking, a way to fi nd small changes

that produce dramatic improve-ments. Systems thinking meth-ods were further refi ned when Bob Galvin, the former CEO of Motorola, and other industry leaders developed what is known as the six sigma strategy. Build-ing on this work, smart grids can be built cost-effectively by utiliz-ing systems thinking to reveal key leverage points. A case in point is the city of Hinsdale, Illi-nois. Plagued with recurring out-ages that exceed the system aver-age interruption frequency index (SAIFI) value of four, Common-wealth Edison (ComEd), the local utility, identifi ed a cost-effective solution that virtually eliminated outages in the downtown area. This simple solution involved placing two smart switches at the

substation feeding downtown Hinsdale, adjacent neighbor-hoods, and a hospital.

As another example, Naperville, Illinois, utilized six sigma quality methods and systems thinking to develop a smart grid design that would dramatically improve reliability and lower operating costs (see http://galvinpower.org/galvin-conducts-naperville-smart-grid-initiative-case-study). This includes looping circuits, smart switches, advanced com-munications, and a state-of-the-art control room to oversee every major component in the system electronically. Reli-ability has improved dramatically, from roughly a SAIFI of 1.5 to a SAIFI of 0.3.

The Illinois Institute of Technology (IIT) independently developed a design similar to that used in Naperville by using six sigma design methods. In addition, IIT aggregated all of its building electricity needs—roughly 50,000 MWh—figure 2. KEPCO’s field test site for the IEC 61850-based SAS.

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figure 1. Configuration of KEPCO’s smart SAS.

Local communities in Illinois are seeking sustainable economic development approaches that offer real, lasting benefits to the local environment and improve the quality of life in the community.


to pursue a lower-cost and lower-carbon electricity supply mix in the competitive Illinois electricity markets. In March 2010, IIT signed a contract with Exelon Energy for about US$40/MW for a generation mix that is 75% carbon-free, with 25% hydropower.

These prototypes reveal that a community focus is one way to gain leverage on the electricity system. Communities can be empowered to work with their utilities to create so-called “perfect power” systems. This requires the develop-ment of a smart grid or perfect power plan and diagram that provides a conceptual design and a means for implement-ing the design. As Daniel Burnham, a now-famous Chicago architect, once said, “Make big plans; aim high in hope and work, remembering that a noble, logical diagram once recorded will not die.”

Oak Park, Illinois, which has long served as a model for sustainable community development, is now a focal point for the ComEd smart grid advanced meter prototype. The ComEd smart meter pilot program provides smart meters for every res-ident, establishing a foundation for further investment in con-servation and automation (e.g., smart homes). This will posi-tion Oak Park to achieve its goals of dramatically improving reliability, increasing conservation, and reducing the carbon emissions associated with electricity usage. The Illinois Sci-ence and Technology Coalition, Citizens Utility Board, IIT, leading Korean smart grid researchers, and Galvin Electric-ity Initiative have all agreed to join forces to assist Oak Park in design-ing a smart grid concept and plan.

Korea’s Smart Grid ArchitectureIn 2009, Korea initiated the development of a Korean smart power grid (K-SPG) to achieve advanced power system opera-tion from potential smart grid systems in the country. The Korea Electric Power Corpora-tion (KEPCO) played a lead role in the design and implementa-tion of the K-SPG. As described below, the K-SPG architecture is a prime option for local commu-nities looking to implement smart grid solutions.

The K-SPG design can be categorized into three parts: smart transmission, smart distribution, and microgrids. Smart transmission refers to a highly reliable and effi cient network using high-voltage dc (HVDC) and fl exible ac transmission systems (FACTSs), substation automation, and wide-area measurement and control system (WAMACS) techniques. Smart distribution consists of advanced dis-tribution management using intelligent electronic devices (IEDs) and energy management system (EMS) technologies. Microgrids employ interconnected and independent system operation techniques using sophisticated energy manage-ment systems.

Smart SubstationThe International Electrotechnical Commission’s reference architecture for electric power systems includes IEC 61850 as an international standard for substation automation, establishing protocols for communication between hard-wired and digital network–based devices. Under a recent power IT project, KEPCO constructed an IEC 61850–based substation automation system (SAS) with domestic Korean IED trial products. Figure 1 illustrates the confi guration of this smart substation automation system. For use in verifi -cation of the new digital substation automation system, the KEPCO Research Institute (KERI) constructed an IED testing system to perform a variety of communication tests

Conventional Type

Intelligent Type

figure 3. KEPCO’s substation automation field test site.

The K-SPG architecture is a promising option for local communities looking to implement smart grid solutions.


with products developed by many vendors. This system exchanges data and operates the substation through a peer-to-peer or server-and-client relation of IEDs and human-machine interfaces (HMI), based on the Ethernet network.

KEPCO constructed the SAS with IEC 61850-based devices at the 154-kV fi eld test substation (see Figure 2) and

completed additional system verifi cation work and functional communication testing at the KEPCO laboratory. About 20 Korean vendors participated in the SAS develop-ment effort and integrated their own devices and solutions. SAS testing is an essential element for assuring interoperability of engineering processes and applications and verifi cation of system performance.

Recently, KEPCO attempted the fi eld test of an actual operating substation. The Seo-Gochang substation was selected for the fi eld test. Figure 3 depicts the test sub-station for the smart SAS.

Smart DistributionThe Korean distribution automation sys-tem (KDAS) has been operating since 1998. The KDAS is installed in all 190 branch offi ces, and approximately 35% of the 127,000 line switches have been

automated. Several types of communication media such as optical fi ber (68%), telephone wires (15%), trunked radio systems (8%), mobile data (8%), and circuit breaker monitor analysis, or CDMA (1%) are used in the KDAS. The major functions of the KDAS are to monitor distribution feeders, clear faults, and restore unfaulted sections. For this purpose,

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-Examine the FutureNetwork Conditions forExpected Outage Schedule--> Examine Using thePower Flow, NetworkReconf.

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Study Mode 1

-Voltage Control Failed inReal Time Operation--> Other Solution ExamineUsing the Network Reconf.

Real Time andEvent Driven Mode

Operator

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figure 4. Solution extraction procedures for the KSDMS.

table 1. Categories of application solutions for KSDMS.

No Group type

Execution /Periodic /Execution Time Object Application

1 Event-driven mode

Automatic/Irregular/Less than a few seconds

Fault clearing and restoration for current operations

NP, PC, NR

2 Real-time mode

Automatic/Periodic /Less than a few minutes

Recognition of accuracy of current network conditions and recommendation of appropriate solutions

NCP, SE, RPF, VVC, LM&F

3 Study mode Manual /Irregular /Less than a few minutes

Examination of other solutions and devices, and future network conditions

DPF, ONR, GF

NP = network protection; PC = protective coordination; NR = network restoration; NCP = network connectivity processing; SE = state estimation; RPF = real-time power flow; VVC = voltage variation control; LM&F = load management and forecasting; DPF =dispatch power flow; ONR = optimal network reconfiguration; GF = generation forecasting.


the KDAS has application programs for fault location, isola-tion, and restoration (FLISR); load balancing and loss mini-mization; and relay coordination.

In smart distribution systems, sources of dispersed gen-eration (DG) pose a major challenge for the system operator to control and manage. Due to unexpected variations in the output of DG sources, the voltage of distribution load points fl uctuates. Therefore, we need a solution for voltage control in a smart distribution grid.

To achieve high reliability, KEPCO is considering a looped distribution topology. In a looped distribution sys-tem, operators cannot intuitively know the direction and magnitude of power fl ows. Therefore, the topology must be processed for the entire monitored network and periodic load fl ow analyses are needed.

Smart distribution systems must also face the challenge of dealing with large volumes of real-time data, including customer information from the advanced metering infra-structure (AMI) as well as data refl ecting device conditions. These data can be used to recognize accuracy network con-ditions such as the distribution state estimation.

To solve these challenges, the Korean Smart Distribu-tion Management System (KSDMS) was initiated in 2009. The KSDMS procedures described in Figure 4 and Table 1 enable operators to recognize problems and anticipate potential risks for the entire distribution network for each branch offi ce.

The new challenges discussed above for smart distri-bution systems can be solved by the following KSDMS procedures:

✔ Voltage control of interconnected DG sources: In real-time mode, operators receive periodic solutions for network voltage control strategies using the real-time power fl ow (RPF) and voltage variation control (VVC). If a solution in real-time mode is not satisfac-tory, operators examine the case in study mode. They can examine the case using other applications such as dispatch power fl ow (DPF) and optimal network reconfi guration (ONR), after which the network con-ditions (analog and digital status and devices) can be modifi ed.

✔ Looped network: In real-time mode, network connectivity processing (NCP) is periodi-cally executed and informs the operators of the topology of the entire network. For any topological conditions, state estimation (SE), RPF, or VVC can be executed.

✔ Usage of additional infor-mation: Distribution SE can be performed using accura-cy data for each load point,

and the conditions of the entire network can be recog-nized. Load management and forecasting (LM&F) and generation forecasting (GF) use additional data and can offer pseudo loads and generation MW/MVARs for current and future networks.

The data communication-processing (DCP) compo-nent of KSDMS processes data from field devices using IEC 61850 as well as Distributed Network Protocol (DNP) 3.0. The DCP component analyzes data frames from smart field devices such as feeder intelligent elec-tronic devices (FIEDs) and feeder remote terminal units (FRTUs) and converts these events to measurement and control data that are then adapted to a common informa-tion model (CIM) database. Using Simple Network Man-agement Protocol (SNMP), the DCP component provides capabilities for configuring and monitoring communica-tion networks and devices. It also uses redundancy con-trol to achieve high availability and can manage time synchronization between field devices using Simple Net-work Time Protocol (SNTP). The DCP component system architecture is illustrated in Figure 5.

The system architecture of the KSDMS server and the interconnections among the components through middle-ware are illustrated in Figure 6. Data from fi eld devices such as the prototype FIED are connected and exchanged with the server via the DCP component. Other system compo-nents include HMIs, engineering stations for database and schematic editing. The application server and database man-agement system (DBMS) server are also connected to each component via middleware.

MicrogridsIn Korea, a wide array of research has been conducted on distributed generation and storage. In 2005, a power IT development program planned 11 detailed projects funded by the Korean government. Many consortia for develop-ing components and intelligent power systems were estab-lished; members included numerous universities, research institutes, manufacturing companies, and the electric power

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figure 5. System architecture of the DCP component.


utility KEPCO. One such project established a consortium to develop microgrid system components and construct a demonstration site with the conceptual design summarized in Table 2 and Figure 7.

The microgrid consortium that KEPCO was a member of completed several projects, including the development of

systems for distributed generation and battery energy stor-age; development of microgrid components such as a PCS, a static transfer switch (STS), and an EMS; and technical performance testing in the KERI microgrid pilot plant. The microgrid R&D products produced in phase 1 of the project are displayed in Figure 8.

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figure 7. Pilot 120-kW microgrid plant.

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Historical Data Proc.

figure 6. Server system architecture.


The 120-kW KERI microgrid pilot is designed to evalu-ate the performance of devices such as PCSs for renewable energy sources, gateways for the communication between an EMS and fi eld devices, and EMSs for the control of the out-put power of DG sources.

The project also addressed microgrid planning techniques focused on identifying the optimal combination of resources for a specifi ed set economic, environmental and system reli-ability objectives. Figure 9 provides a brief depiction of the microgrid system planning process.

In the environmental analysis, the annual wind speed and solar radiation in selected areas are examined to evaluate the renewable energy resource potential. An analysis of electrical and thermal demand is conducted to determine the required capacity of each generator. Next, a system-modeling tool is applied to identify the optimum composition of resources. A power network analysis is performed to test the stability and security of the identifi ed optimum microgrid system compo-sition, and necessary adjustments are made to ensure compli-ance with the IEEE 1547 standard for the interconnection of distributed resources with electric power systems. Finally, economic evaluation indices for microgrid systems—such as total investment requirements, operation and management costs, net present value, and greenhouse-gas reduction—are computed and compared.

ConclusionsTable 3 provides a glimpse of what can be accomplished with a community or microgrid approach to smart grids. The table summarizes the investments, impacts, and costs associated with implementing a smart grid or perfect power prototype for Oak Park, Illinois. The results are dramatic and only achievable if city leadership, the local utility, global solution providers, and consumers work together to

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figure 8. Microgrid R&D products in Phase 1.

table 2. Overviews of microgrid R&D project in Korea.

Phase Objective and contents

Phase 1‘(’07. 9~’09.8)

Establishments and performance evaluation of 100 kW class Microgrid system– Microgrid design: determine microsources type and capacity

– Dynamic Simulation for characteristics of microgrid and protection scheme

– Establishment of 100 kW pilot plant and operation performance evaluation

Phase 2‘(’10.2~’13.1)

Establishment and performance evaluation of two type microgrid demonstration site such as interconnected and remote MG– For the commercialization microgrid standardization and policy analysis

– Development of microgrid engineering technology


develop and implement a smart grid pilot that meets the needs of the local community.

The K-SPG architecture is a promising option for local communities looking to implement smart grid solutions. K-SPG is concentrated on the connection of large-capacity distributed energy resources and enhancement of end-to-end energy effi ciency. The business model for K-SPG implementation centers on the creation of value from enabling reductions in overall energy costs, reduction of environmental pollution, enhance-ment of power system reliability, and contribu-tions to national and local energy security issues.

Together, the Republic of Korea and Illinois are exploring shared opportunities for smart grid development and deployment that can support local community sustainability initiatives and bring the desired benefi ts to citizens of both countries.

BiographiesI.-K. Song is with KEPCO, Republic of Korea.

K.-D. Kim is with the Korea Smart Grid In-stitute.

John Kelly is with the Galvin Electricity Ini-tiative.

C. Thomas is with the Illinois Citizens Util-ity Board, Chicago. p&e

table 3. Estimated benefits of smart grid implementation in the village of Oak Park, Illinois.

Smart Grid Prototype Elements

Investment US $ millions

Source Energy, mmbtu

Carbon, Tons,

Delta Cost, ~$/MWh

Grid Reliability Improvements 100 70% improvement 12

Community Aggregation 90 –25% –30% –7

Wind, 15 MW @ $100/MWh 30 –6% –5% 4

Hydro, 3 MW @ $40/MWh NA –5% –4% –4

CCCT, 10 MW @ $90/MWh 30 –4% –10% 4

Bio-energy, 5 MW @ $90/MWh 30 –10% –10% 4

Lower cost and revenue –15

Clean Energy Financing, PACE 160 –25% –30% 0

Solar PV, 7.5 MW 60 –2% –2% 3

Efficiency/DR/Home Automation 50 –20% –15% –5

Cogeneration , 15 MW 30 –3% –9% 2

Storage/DG, 10 MW 20 0% –4% 0

Plug in electric vehicles, 5000 NA 2% –10% 0

Total US$350 –50% –70% $5

DER Analysis

Demand Analysis

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Analysis

Evaluation

Economic Assessment

Microgrid

Management SystemFeedback

Network Analysis

Network

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Composition

— Total Cost/O&M Cost

— Payback

— IRR, NPV, GHG etc

— Power Flow/Fault Analysis

— Stability Analysis

— Power Quality Analysis

figure 9. Microgrid system planning process.

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