Integrated Resource Scheduling and Bidding in the DeregulatedElectric Power Market: New Challenges
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- 作者：Guan ; Xiaohong ; Luh ; Peter B.
- 关键词：power system scheduling ; bidding ; deregulated electric power market
- 刊名：Discrete Event Dynamic Systems
- 出版年：1999
- 出版时间：1999
- 年：1999
- 卷：9
- 期：4
- 页码：331-350
- 全文大小：137 KB
文摘
Manychallenging issues arise in the newly deregulated competitiveelectric power markets worldwide. Instead of centralized decision-makingin a monopoly environment as in the past, many parties with differentgoals are now involved and competing in the market. The informationavailable to a party may be limited, regulated, and receivedwith time delay, and decisions made by one party may influencethe decision space and well-being of others. These difficultiesare compounded by the underlying uncertainties inherent in thesystem such as the demand for electricity, fuel prices, outagesof generators and transmission lines, tactics by certain marketparticipants, etc. Consequently the market is full of uncertaintyand risk. Key questions to be addressed include how to predictload and market clearing prices, how to consider other parties'decisions in deciding one's own bids, and how to manage uncertaintyand risk. Since finding an optimal solution to a traditionalunit commitment problem is NP-hard even without considering multipleparties and uncertainties, it may be more practical to know whichdecision is good with confidence rather than looking for an optimalsolution. For an energy supplier, bidding decisions are coupledwith generation resource scheduling or unit commitment sincegenerator characteristics and how they will be used to meet theaccepted bids in the future have to be considered before bidsare submitted. For example, if starting up a thermal unit isexpected, the associated startup cost should somehow be configuredin the bid curves. The decisions, however, can be quite subtlesince generally startup costs are not part of a bid. Biddingdecisions should therefore be carefully made by considering theanticipated MCP, system demand, generation and startup costs,and competitor' decisions. What further complicates the issueis that some of the information is not available, or will beavailable but with significant delays. In paper, two promisingbidding strategies for power suppliers are discussed. The ordinaloptimization method seeks ``good enough'' bids with high probability,and is an effective in handling market uncertainties with muchreduced computational efforts. The basic idea of this methodis to use a model to describe the influence of bidding strategieson the MCP. A nominal bid curve is obtained by solving optimalpower generation for a given set of the MCPs within the Lagrangianrelaxation framework. Then bids are generatedby perturbing the nominal bid curve. The ordinal optimizationmethod is applied to form a good enough bid set ,which contains some good bids with high probability, by performingrough evaluation. The best bid is then searched and selectedover by solving generation scheduling or unitcommitment problems within reasonable computational time. Thegame theoretic method aims at bidding and self-scheduling ofa utility company in New England. The problem is investigatedfrom the viewpoint of a particular utility bidder. The uncertaintiescaused by bids from other bidders and the ISO (Independent SystemOperator) bid selection process are explicitly considered. Theproblem is then solved within a reduced game theoretical framework,where the ISO has a closed-form solution for a given probabilisticdescription of the bids, and the utility's problem is solvedby using Lagrangian relaxation. Although the two specific methodsrepresent significant progress made thus far, the area is wideopen for creative research to make the deregulated market a truesuccess.