ANALYSIS OF SPOT PRICES ARRANGEMENTS IN DEREGULATEDELECTRICITY MARKET

Tehzeeb-ul-Hassan Ashiq Haral Dr. M. Farooq AslamAssociate Professor Ph.D. Scholar Professor

Department of Electrical Department of Electrical Department of ElectricalEngineering Engineering Engineering

University of Engineering. & University of Engineering. & University of Engineering. &Technology, Lahore, Pakistan Technology, Lahore, Pakistan Technology, Lahore, Pakistan

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ABSTRACT 1. IntroductionThe absence of central coordination in deregulated Academic discussions about the opportunities andelectricity markets sets a new range of challenges to their challenges associated with introducing wholesale andorganization and functioning. Although a lot of academic retail competition into the electric power sector have goneresearch has been done in the recent years on these topics, on for decades. However, serious considerations ofcontributions and discussions tend to stay within a single comprehensive electricity sector restructuring andfield of policy analysis. The fundamental factors in the deregulation initiatives in the U.S. only began in the mid-operation of electrical power systems, at a macro level, 1990s, following the first comprehensive privatization,are distribution of the operation parameters over vast restructuring, wholesale and retail competition programareas, dominance of human factors and high undertaken in England and Wales (E&W) in 1990 [2]. Adimensionality of the problem. number of other countries followed the same practiceEconomics and stability are two disjoint areas of electrical after that. However the process seems to be still in itspower system operation. Economic operation of power evolution stage, even after 15 years of inception of thesystems is a complex problem of decision management idea of deregulated and competitive electricity market. [1]because of distributed nature of the information,dominance of human factors and high dimensionality of In the last quarter of 1999 and early 2000, the collapse ofthe state space. The new deregulated market environment California's electricity restructuring and competitionhas rendered this management even more complex. program has attracted attention around the world. PricesContemporary power system operation is based on the in California's competitive wholesale electricity marketidea of a central load dispatch center (CDO). The data increased by 50000 between the second half of 1999 andarriving in the CDO from all over the system, is although the second half of 2000. For the first four months of 2001,useful for system stability, is of little value for the short wholesale spot prices averaged over $300/MWh, tenterm economic operation. Interconnection of independent times what they were is 1998 and 1999 [2].power producers (IPP) has increased the state space to thelevel of combinatorial explosiveness, while recent Although wholesale prices began to moderatedevelopment of multiple fuel plants has added to the significantly during June 2001, the California'sdominance of the human factor. Distributed client-server experiment poses a big question to the new electricitydatabases, artificial intelligence, internet and the intranets restructuring regime. And while many analysts predictedare emerging information technologies that can be that there would be problems resulting from a variety ofeffectively utilized to address these problems. market design and regulatory decisions made during theDistributed economic operation is a new area of research. new system's formation, nobody predicted thatThis paper extends that research to the management of California's electricity restructuring and competitioninformation distributed in the power network to make it reforms would lead to such a huge mess [3].useful for short term economic operation.

KEY WORDS 1.1: Restructuring of the Power MarketDistributed Economic Operation, Client-Server Replacing the hierarchical governance arrangements withDatabases, Decision Management well functioning decentralized market mechanisms is a

very significant technical challenge, about which even thebest experts have disagreements. [2]

The restructuring and competition initiative got off on the properly designed intelligent database systems and thuswrong foot in the very beginning, at least in part because can be made available at important points to activelyof the underestimation of the nature and magnitude of the participate in the decision making process [13]. Thesetechnical and institutional challenges associated with client-server databases when properly connected wouldintroduction of competitive wholesale and retail transform the electrical power system into a distributedelectricity markets and the associated uncertainties. information network. See Fig. 1.To some extent this underestimation was strategic,reflecting efforts by some participants in the process to Installation and use of intelligent client-server databasesfeather their own nests. However, it also reflected a require another kind of system architecture entirelycombination of ignorance, political barriers, and true different from contemporary centralized control.uncertainty about how best to restructure to support An important question arises here, "Where to put thiscompetition and how to design effective wholesale and data?" The reengineering paradigm provides an answerretail market, transmission, and system operations that is significantly different from conventionalinstitutions. The experts did not, and in many areas still contemporary practice which requires keeping the datado not, agree on exactly how best to proceed with these where it is generated. The information generated by thestructural and institutional reforms [2]. principal entities can then be logged into client-serverThis and other growing pains of the electric energy databases and may be processed at the sites it is beingindustry restructuring are becoming quite visible to the collected and the single transaction containing the outputgeneral public now. These are reflected either through could then be sent over the intranet to the CDO. Thisundesired service interruptions and/or through highly would not only reduce the network traffic but also wouldvolatile electricity prices [4]. If deregulation is to play a relieve from the costly hardware of the SCADA system.role in helping to improve the efficiency with which Distributed problem solving is said to occur when aelectricity is produced and used, it must be introduced as number of independent problem-solving agentspart of a long-term process that also encompasses collaborate in solving a problem. Collaboration isregulatory and structural reform [5]. Electricity necessary when no single agent can solve the entirerestructuring is likely to involve both costs and benefits. If problem [13]. It is easy to visualize that the problem ofthe restructuring is done right the benefits can power system operation is distributed in nature, wheresignificantly outweigh the costs [6]. most of the problem-solving agents are hundreds of

kilometres apart. Individually none of them can solve theentire problem and thus collaboration is necessary [10]

Present day electrical power systems are spread over veryvast areas. All principal entities participating in thesystem operation continuously generate a lot of data. In A prime motive behind the deregulation movement is tothe contemporary system operation CDO is responsible provide electricity to the general public at a cheaper rate.for keeping all the data that is sensed from various For economic operation of the system, the fuel costlocations by Regional Telemetry Units (RTU) and characteristic are modeled for each unit in the system as asubsequently transmitted by Supervisory Control And quadratic and are shown in (1) below.Data Acquisition (SCADA) system. As a result the CDO + 2 (1)is overloaded with a huge amount of data that not only put F(P) a + /P+a multidimensional impact on the system performance but Where F(Pi) is the cost of fuel incurred per hour. Thegetting useful information from this pile is in itself a determination of the parameter cc, D and y requires thedifficult problem [8,9]. availability of data relating the cost F(Pi) to theThe system operation has two main aspects; economic generation level Pi considering the operation ofm thermaland stability. These two are disjoint areas of system generating units on the same bus [7,14]. Assuming thatoperation [10]. A less obvious impact of sending whole of the variation of the fuel cost (F.) of each generator withthe telemetry data to the CDO is that parameters requiredfor stability and control of the system are easily sensed by similar to(i) above, the total fuel cost of the plant can bethe RTU and find their way easily to the control center given as the sum of the individual unit cost converted towhereas most of the parameters crucial for economic $/h [14,15].operation are not transmitted by SCADA and aredispatched through slow paper links [11]. Thus most ofthis data that is distributed in various parts of the system 2+ p + Iip2is lying dormant and do not participate in any way F = ia +whatsoever, in the economic operation. Before the present 1

era of information technology, it was not even For the system operation to be optimally economic, all theconceivable to find any suitable means for mobilizing this units participating in the operation at a certain time shouldinformation [12]. operate at equal incremental fuel costs [15]. Therefore asThe information generated by all entities may be logged a necessary condition for optimal economic operation,by online logging system at regular intervals, into

Information Network

Staition Bus..................K __ _ g ~~~~~~~~~~~~~~~~E66 IS

TransmissionLine tI

GeneratorsILoad lengths are in

kilomffeters~~~~~~Fig.1: Electrical Pow er System as an Inform ation

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reflecting a price for power from their plants. The price operating on multiple gas fuels where the gas fuel can bebid by the last plant used to meet electricity needs in a readily mixed together not only causes the calorific valuegiven time period is the price for capacity from all plants. to change, but at the same time it also changes the price ofAccording to theoretical studies of this kind of market fuel in a complicated manner. [17] However to keep theoperation suggests that bidders selling more than one unit analysis simple only the case of single gas fuel is used.of a good have a monopoly to increase the prices they bidat high quantities. According to Catherine D. Wolfram

theidsfor ive plats reFige when theti suppler ste Lno

ad Load

haves mnouhtmaesreavailabl ecapacity.[16]s Gar600 15.e1. 72 .04

GT-2 400.0 100.0 310.0 7.85 0.00194 GT-3 1147.613 to 1343.950 Rs/MWhGT-3 l200.0 50.0 78.0 7.97 0.00482

Maximum IFC of the system 1343.950 Rs./MWhUnits are indicated by GT- 1, GT-2 and GT-3. The data ofunits is taken from reference [15] and is shown in Table I Minimum IFC of the system 1035.458 Rs./MWhabove.

The results of load dispatch are given below in Table III.Table II:Data of gas fuels used, I US $ = 63 Rs., and The spare loading capacity under this load dispatch in

Hm3 = 100 m3 each unit is also shownCalorifi'c Prc Sae

Gas Field Value rice3 Sal Table III:Result of load dis atch, I US $ = 63 Rs.R2s/Hm Tax

Btu/Cft Unit QT41 GT-2 GT-3Sui 918 382.77 15.0 Ful SLi Gap Sui Gas SLi GasMani 724 361.22 15.0 Load MW 578.52 255.92 90.0Kandh Kot 699 363.26 0.0Tullow 875 382.63 0.0 Energy

Supplied MWh 578.52 255.92 90.0ostl IkWh 1.238 1.238 1.238

The gas fuels are coming from 4 gas fields named as Sui, SpareMari, Kandhkot and Tullow and are shown in Table- Capacit 21.48 144.08 109.4II.[17] These are the natural gas fuels actually used inNatural Gas Thermal Power Station, Guddu, Pakistan. The unit GT-3 has the maximum IFC of all the three units[18] and would be the last unit in the commitment order.

According to [16] if unit GT-1 wins the bid and get theCase study: shown in Fig. 2 below is the one where all the opportunity to supply the load the economic dispatchthree units are operating on the same fuel from Sui gas would be disrupted and the cost of unit of electricityfield. The IFC of units have large overlapping areas and would increase to Rs. 1.246 / kWh, causing a national lossthus may be operated at a common system incremental of fuel to the country, although the individual generatorfuel cost IFC. may be running at a net profit.

This is the root cause of the California's electricity crises

1400.0 mentioned earlier in this paper. The price continued torise up to 500 % until the original company approached

B 1300.0 the bankruptcy.

t 1200.0 The case of multiple fuel units is more sever because the& ~~~~~~~~~~~~~changein fuel not only changes the calorific value of the

1100.0 fuel but the economic load sharing is also becomes void.[19]

1000.0-4-GT-1, Sui X

0

GT-2, Sui 0.0 200.0 400.0 600.0 800.0 4. ConclusionGT-3, Sui Case I-B, Power P (MW)

Two sub problems in the system operation would beFig. 2: Case Study, where all 3 units are operating on addressed in this proposal; the problem of unit

the same gas fuel. commitment and economic dispatch of thermal units. Atpresent the priority list schemes are being used togenerate a 10 day schedule for the simulated conditions.

At an example load of 925 MW, the result of economicThsreacwolbinaluitonieadcretdisptchperaionis a folows This research would bring all units on line and current

economic status would be available to the operators in

Total Load = 925 MW real time in the central dispatch office. It has beenestimated in a previous study that for a dispatch of 3thermal units with a total capability of approximatelyUnits operating on fuel = Sui gas 1200 MW, a saving ranging from Rs.0.6 Million to Rs.6.5

The.liits.o increentalfuel cost (IFC) i Million is possible in a 24 hour operation, supplyingThellmtsof creenal ue cot (FC valaone US$) energy of about 22,000.0 MWh to the load. (1I $ =Rs.63each generating unit are given below. (63 Rs. = n S)Approximately)

GT-I1 1035.458 to 1208.985 Rs/MWh Power system network is to be represented as anGT-2 =1118556 to 127.604Rs/MWhinformation network where client-server databaseGT-21118.556 to 1276.604 Rs/MWhsystems would be installed at all thermal plants for

logging the economic parameters into suitably designed 7. M. E. El-Hawary, Electrical Power Systems Designdatabase system. IEEE 30 bus network can serve as a andAnalysis, Virginia, Reston, 1983, pp. 701-716good starting point. The generation sites in the network 8. Miao S., S. Wang, P. Liu, S. Cheng, The Design andwould be replaced by thermal plants comprising from six Implementation of the GPS based Real-timeto ten thermal units. The data for the fuels used by the Monitoring System for the State of Power Network,WAPDA for its thermal plants would be utilized in thisresearch whereas the heat-input characteristics for each InentoaJou l P e d r S munit in each plant would be generated on the test bench Vol.21, No.3, 2001.under simulation [30, 31]. 9. Pinheiro Raul, Zita A. Vale, Electrical DistributionDistributed database computing techniques would be Network Measurement Data Pre-Processing fordeveloped for completion of economic dispatch under no Knowledge Discovery: Preliminary Results, Proc. oftransmission loss. These distributed database systems IASTED International Conference on Power &would communicate over the internet. Energy System, EuroPES-03, Marbella, Spain, Sep-To incorporate the effect of transmission losses the 03 - 05, 2003network would be partitioned into different parts. 10. Aslam, M. F., An Expert System for OptimalPartitioning rules has to be developed for that purpose and Economic Operation of Mixed Hydro-Thermal Powerwould be a major contribution to knowledge. Systems, Ph.D. Dissertation, University of

Engineering and Technology, Lahore, 2004.

5. Acknowledgements 11. Aslam M. F., D. Lidgate and T. A. Shami, A5.Acknowledgements Distributed Database System for Economic Dispatchof Thermal Plants, Proc. of IASTED International

The authors are indebted to Chief Engineer, Natural Gas Conference on Power and Energy Systems, EuroPES-Thermal Power Station, Guddu, Pakistan. The authors are 03, Marbella, Spain, Sep 03 - 05, 2003.especially thankful to the University of Engineering & 12. Aslam M. F. and T. A. Shami, Power SystemTechnology, Lahore for providing the necessary funding Operation in Information Technology Era, Proc. offor this research. the 2nd International Electrical Engineering

Congress, Lahore, Pakistan, Feb. 2001.

13. Talukdar, S. N. and Cardozo, E., Leao, L., Banares6. References: R., and Joobbani R., A System for Distributed1. Aslam M. Farooq, Tehzeb Hassan, and Tabrez A. Problem Solving, Workshop on Coupling Symbolic

Shami, "Reengineering of Systems Operation; A and Numerical Computing in Expert Systems,Solution to the Challenges in the Deregulated Market Bellevue, Washington, 27 - 29 August 1985Environment - I", WSEAS Transactions on Systems, 14. Kirchmayer, Leon K., Economic Control ofIssue 8, Vol. 4, August 2005 Interconnected Systems, New York: Wiley, 1959

2. Joskow, P. L. The Difficult Transition to Competitive 15. Allen J. Wood and Bruce F. Wollenberg, PowerElectricity Markets in the U.S. Conference on generation operation & control (New York: Wiley,"Electricity Deregulation: Where From Here?", Bush 1984)Presidential Conference Center. Texas A&MUniversity, April 4, 2003. 16. Catherine D. Wolfram, Strategic Bidding in a Multi-

Unit Auction: An Inperical Analysis of Bids to3. Joskow, P. L. California's Electricity Crises, Supply Electricity in England and Wales, Working

Working Paper # 8442, National Bureau of Economic Paper 6269, National Bureau of Economic Research,Research, Massachusetts Avenue, Cambridge, Cambridge, Nov 1997August 2001.

17. Aslam M. Farooq, D. Lidgate and Tabrez A. Shami,4. S. Stoft, PJM's Capacity Market in a Price-Spike A Coupled Knowledge Based System for Online

World, University of California, Energy Institute, Economic Dispatch of Multiple Fuel Units in aMay 2000. Thermal Plant, Proc. 39th International Universities

5. Joskow, P. L. and R. Schmalensee, Markets for Power Engineering Conference", UpecO4, Sep-06 toPower, MIT Press, 1983. Sep-08, 2004, University of West England, Bristol,

UK6. Joskow, P. L. Restructuring, Competition and

ReultryRfom nth .S letrctySctr 18. R. A. Ansari, 450 MW Combined cycle power stationJournal of~~~~~~~Ecnoi Prpcie, 113,Sme Guddu, technical & statistical data, Water and Power

1997, pp. 1 19-138. Development Authorityv (Pakistan, 1995)

19. Aslam M. F., D. Lidgate and Tabrez A. Shami, FuelCost Characteristics of CCP and Simple CycleMultiple Fuel Units, Proc. of 38th InternationalUniversities Power Engineering Conference,UpecO3, Thessaloniki, GREECE, Sep-01 - 03, 2003