FORMAL PROJECT PROPOSAL
Game Theory Based Loss Allocation Method in Electricity Markets – Based on cooperative game theory, a method for power losses allocation in a competitive electricity market is to be developed
1.0 Aims of the project
Basically, the project aims to develop an effective method of power loss allocation in electricity industry. The basis of the method is the cooperative game theory, which is an offset of the game theory. Game theory is simply the attempt to quantitatively capture the elements of a strategic situation, and that a game is perceived to be cooperative if the players are able to form binding commitments. Cooperative game theory analyses optimal strategies for groups of individuals while presuming that enforcing agreements between them regarding proper strategies would be feasible. As such, another aim of the project is to develop an effective loss allocation method which could mutually quantify the influences of different players on the loss allocation system as well as to reasonably allocate network power losses at each transaction. The method that shall be developed must hold the capability to analyse losses involved in the transfer of power from one point to another.
2.0 Summary of the literature search
According to Lim (2006), the changes in the electric industry have introduced many opportunities and challenges into becoming a competitive electricity industry. One of these changes is an advocacy on the necessity ‘for charging energy losses to market participants through a more satisfactory and transparent mechanism’. The author continued that market participants would want a loss allocation scheme that is able to reflect each market participants’ contribution of generation or usage in the network. However, as electricity is an indistinguishable entity, there is no accurate method to trace the flow of electricity thus far. Hence, the issue of power loss allocation still remains an unresolved setback to progress to a fully competitive electricity market. Many loss allocation methods have been introduced; however, none have been universally accepted.
Lahlou and Gnansounou (2007) assert that the introduction of competition, higher uncertainty and decentralised planning requires new planning and analysis tools on the medium to long term to support decision making at the level of the industry as well as at the level of the market authorities. Their thesis focuses on bilateral transactions because the authors believe that such transaction processes are specially relevant from the point of view of risk management when considering medium to long term decisions (for both portfolio management and investment decision making). The study makes use of the decision analysis.
Carpaneto et al (2007) assert that meaningful loss allocation methods are required in order to send correct signals to the market taking into account the location and characteristics of loads and generations, including the local sources forming the distributed generation (DG). Reta and Vargas (2001), on the other hand, state that competitionin electricity markets requires the identification of the responsibilities inthe use of transmission networks or the associated effects. Nonetheless, the authors use the electric circuit theory because of its practical implementation that requires only to compute a loadflow and solve a linear equation system. Such method was utilised in order to assess the power output flowingfrom a specific generator to a specific load and to determine `influence areas’ and to allocate losses among participants that share the network.
A study conducted by Lima et al (2007) suggests that the cooperative game theory model in which the players are represented by equivalent bilateral exchanges must be accompanied of a loss allocation solution. The researchers made use of the Core in analysing and discussing the allocation of the cost of losses to generators and demands in transmission systems. Their objective is to illustrate why is not possible to find an optimal solution for allocating the cost of losses to the users of a network. Dai et al (2008), on the other hand, addresses the problem of transmission loss allocation in a power system where the generators, the demands and the system operator are independent. The researchers figured that the transmission losses are exclusively charged to the generators, which are willing to adopt a perfectly competitive behavior.
Molina et al (n.d.) attempted to present a novel procedure for the allocation of active and reactive power losses among generators and loads in the transmission grid. The procedure they used considers the grid as a block which makes the analysis of the elements within the block unnecessary. Aumann-Shapley method was utilised. The method is a combination of circuit theory and game theory in allocating the active and reactive power losses. For them, one of the most complicated tasks in the competitive electricity industry is the allocation of costs among participants in different markets. As such, loss allocation is a major issue in the industry because of the nonlinearity and nonseparability features of power loss problem. They also contend that only cooperative game theory is the most applicable to cost allocation problems among participants that make use of the same service and its objective is to obtain the fairest solution.
De Oliveira-De Jesus et al (2007) maintain that although different ex post methodologies have been proposed to allocate network losses, the implementation of these procedures implies an access-pricing framework based on half-hour or hourly locational prices. The authors contend that locational prices depend on allocation procedure, altering the market equilibrium point as a resultant factor of price elasticity of demand. The study applied the social welfare theory to ensure a non-discriminatory access to networks and came up with a base scenario which was obtained through optimal power flow study. The purpose of the activity is to stimulate an efficient energy market by means of considering four allocation philosophies as incremental, roll-in-embedded, tracing based and circuit based.
Ma et al (2005) also believed that until today the transmission power loss is disregarded in most literature that focuses on the gaming behaviors of the producers in the electricity market. The authors have proposed a supply function game model in considering the power flow loss of the transmission network. Such model is composed of the upper-level optimization problem of the producer’s surplus for generation firms and the lower-level optimization of the market system surplus. They found out that not only in the perfect competition market but also in the supply function equilibrium based oligopoly market, the power flow loss impacts from the electricity network will drive the total transactions and the market efficiency decreased in relatively large extent with respect to the power flow loss disregarded model.
Kamir and Yamashiro (2005) propose an empirical formula or preliminary loss allocation to each generator in a network which was derived from the relationship of Incremental Transmission Loss (ITL) and the power outputs of generators. What they did in order to get the allocated losses to generators is to adjust preliminary losses according to the correction factors calculated from them. The allocated losses calculated were compared with those of incremental method for the both model power systems. For the bilateral transactions, transmission pricing is important due to the fact that estimates of accurate costs are needed to provide the correct price signals. That is why under the competitive environment, an effective transmission pricing methodology is important for bilateral transactions (Baniya et al, 2005).
Opok (2003) also presented a computation of loss allocation which could be applied to sellers and buyers participating in electric power trade. The approach that author considers is based on the Jacobian and Hessian matrices of the power flow equations and that the losses to be allocated are derived from load flow of a specified power network and operating conditions. Nevertheless, he proposed method is suitable for an application in a deregulated power market where market participants can arrange to cover for the cost of losses. It contrasts with those approach used n the underegulated electric power system where losses are accounted for by penalizing the generators using penalty factor approach.
For Unsihuay and Saavedra (2003), transmission losses are a significant component of the amount of power to be generated in order to meet the power demand. Transmission losses must be allocated among the market participants in a competitive environment operating either under bilateral contracts or hybrid model. The authors claim that such process should take in account the buyer and seller spatial locations on the network as well as the non-linear interaction among simultaneous transactions in order to reflect the real market operation and adequate economic efficiencies.
3.0 Proposed approach/methodology to be used
Core as the solution concept as applied to the bilateral transactions. Bilateral transactions in competitive electricity market requires that power losses be allocated open, equal and under impartial principles of electricity market.
4.0 Some brief descriptions on the theory of the approach/methodology
Core
According to Serrano (2007), core is one of the two counterparts of game theory. Core focuses on the interactions among coalitions of players. Core seeks to answer the question: Given the sets of feasible payoffs for each coalition, what payoff will be awarded to each player? As such, a project could take a positive or normative approach to answering this question, and different solution concepts in the theory lean towards one or the other.
5.0 Time table/schedule of work for the entire project
At this stage, the project plan is subdivided into two parts: the actual and the planned phases.
On the Actual phase, the activities are:
Planning of project topic and assigning of task – WEEK 1
Preliminary literature review – WEEK 2
Writing formal research proposal – WEEK 3
On the Planned phase, the activities are:
Collating information and analysis – WEEKS 5-6
Tracking status of the project – WEEK 7
Project reviews – WEEKS 8-9
Documentation and reporting – WEEKS 10-11
Taking corrective actions – WEEK 12
6.0 References
Baniya, J., Bao, F., Fan, S. and Chen, L. (2005). Evaluating Transmission Services for Bilateral Transactions in Electricity Market. Transmission and Distribution Conference and Exhibition: Asia and Pacific
Carpaneto, E., Chicco, G. and Akilimali, J. S. (2007). Characterization of the loss allocation techniques for radial systems with distributed generation. Electric Power Systems Research, 78(8): 1396-1406.
Dai, J., Phulpin, Y. Rious, V. and Ernst, D. (2008). How Compatible is Perfect Competition with Transmission Loss Allocation Methods? European Electricity Market 2008.
De Oliveira-De Jesus, P. M., Ponce de Leao, M. T. and Khodr, H. M. (2007). Network-cost-loss-allocation methods evaluation under the perspective of the social welfare theory. International Journal of Global Energy Issues, 28(1): 11-31.
Kabir, M. H. and Yamashiro, S. (2005). An Empirical Formula for Transmission Loss Allocation of Power Systems. IEEJ Transactions on Power and Energy, 125(11): 1033-1040.
Lahlou, A. and Gnansounou, E. (2007). Multi-agent modeling of electricity markets: transaction processes and generation capacity expansion under competition.
Lim, V. S. C. (2006). Power Loss Allocation Methods for Deregulated Electricity Markets. PhD Thesis. University of Queensland. School of Information Technology and Electrical Engineering.
Lima, D. A., Contreras, J. and Padilha-Feltrin, A. (2007). A cooperative game theory analysis for transmission loss allocation. Electric Power Systems Research, 78(2): 265-275.
Ma, Y., Jiang, C. and Hou, Z. (2005). Transmission power loss impacts on the oligopoly competitive electricity market. Proceedings of the 9th International Conference on Circuits. World Scientific and Engineering Academy and Society (WSEAS).
Molina, Y. P., Prada, R. B. and Saavedra, O. R. (n.d.). Allocation of transmission loss cost using game theory. IEEE.
Opok, A. O. (2003). Computation of loss allocation in electric power network using loss vector. Botswana Journal of Technology, 12(1): 7-12.
Reta, R. and Vargas, A. (2001). Electricity tracing and loss allocation methods based on electric concepts. IEE Proceedings – Generation, Transmission and Distribution, 148(6): 518-522.
Serrano, R. (2007). Cooperative Games: Core and Shapley Value. Department of Economics, Brown University.
Unsihuay, C. and Saavedra, O. R. (2003). Comparative studies on transmission loss allocation methods for competitive electricity markets. Power Tech Conference Proceedings.
Credit:ivythesis.typepad.com
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