The method of experimental economics is appliedto research of oligopolistic electricity markets. The design ofexperimental platform, principles of experimental economicsand experimental design are introduced. The experiments areorganized on base of the Cournot model of oligopolistic electricitymarkets. A set of experiments are conducted on the experimentaloligopolistic markets with three generating companies (Gencos)and the experimental results are analyzed with strict statisticsapproaches. The results show that the market competition willconverge to the results between perfect competition equilibriumand Nash equilibrium in oligopolistic electricity markets withasymmetric production cost functions and repeated play amongthe Gencos. The decision support tools of Gencos have significantinfluences on experimental results. The markets converge to staticCournot-Nash equilibrium when the bounded-rational subjectsrepeatedly play, equipped with the tools that can give best responsestrategies. The experimental method provides a complement tothe theoretical research and computer simulation and has manymerits in modeling realistic electricity markets.

This paper presents a new unified framework ofelectricity market analysis based on coevolutionary computation(CCEM) for both the one-shot and the repeated games ofoligopolistic electricity markets. The standard Cournot modeland the new Pareto improvement model are used. The linear andconstant elasticity demand functions are considered. Case studyshows that CCEM is highly efficient and can handle the nonlinearmarket models that are difficult to be handled by conventionalmethods. The framework presented in this paper can help to overcomethe difficulties of demand function specification encounteredby the Cournot models. CCEM is found to be an effective andpowerful approach for electricity market analysis.

This paper presents a coevolutionary approachto analyzing supply function equilibrium (SFE) models of anoligopolistic electricity market. Both the affine supply functionmodel and the piece-wise affine supply function model are considered.Different parametrization cases of the affine supply functionmodel are analyzed. The piece-wise affine supply functions thathave a large number of pieces are used to numerically estimatethe equilibrium supply functions of any shapes. Simulation casesof the piece-wise affine supply function model with different peakloads, nonquadratic and nonconvex costs, and different demandelasticities are studied. An example based on the cost data fromthe real-world electricity industry is used to validate the approachpresented in this paper. Simulation results show that the coevolutionaryapproach rapidly converges to SFE in the affine supplyfunction model simulation and robustly converges to SFE in allcases of the piece-wise affine supply function model simulation.The approach is robust and flexible and has the potential to beused to solve the complicated equilibrium problems in real-worldelectricity markets.

Generation planning has been extensively investigated and applied to practical power industry. This paper presents the generation planningmodel of Jiaotong Automatic System Planning Package (JASP) of Xi’an Jiaotong University, China. JASP decomposes the generationplanning problem into a high-level power plant investment decision problem and a low-level operation planning problem and solves them bya decomposition-coordination method. Lagrangian Relaxation is used to solve the power plant investment decision problem and probabilisticproduction simulation is used to solve the operation planning problem. The generation planning model of JASP can be easily extended to thecontext of market liberalization. Simulation results show that JASP can not only overcome the ‘curse of dimensionality’ but also findeconomical and technically sound generation planning scheme.

This paper presents a new Cooperative CoevolutionaryAlgorithm (CCA) for power system unit commitment.CCA is an extension of the traditional genetic algorithm (GA)which appears to have considerable potential for formulatingand solving more complex problems by explicitly modeling thecoevolution of cooperating species. This method combines thebasic ideas of Lagrangian relaxation technique (LR) and GA toform a two-level approach. The first level uses a subgradient-basedstochastic optimization method to optimize Lagrangian multipliers.The second level uses GA to solve the individual unitcommitment sub-problems. CCA can manage more complicatedtime-dependent constraints than conventional LR. Simulationresults show that CCA has a good convergent property and asignificant speedup over traditional GAs and can obtain highquality solutions. The “curse of dimensionality” is surmounted,and the computational burden is almost linear with the problemscale.

A strategy for volt/VAr control in distribution systems is described. The aim is todetermine optimum dispatch schedules for on-load tap changer (OLTC) settings at substations andall shunt capacitor switching based on the day-ahead load forecast. To reduce switching operationsfor OLTC at substations, a time-interval based control strategy is adopted that decomposes a dailyload forecast into several sequential load levels. A genetic algorithm based procedure is used todetermine both the load level partitioning and the dispatch scheduling. The proposed strategyminimises the power loss and improves the voltage profile for a whole day across the whole system,whilst ensuring that the number of switching operations is less than the maximum daily allowance.A comparison of numerical studies and their associated results illustrates both the feasibility andthe effectiveness of the proposed strategy.

The paper presents a new framework of oligopolistic marketsimulation based on coevolutionary computation. The coevolutionary computationarchitecture can be regarded as a special model of the agent-basedcomputational economics (ACE), which is a computational study of economiesmodeled as dynamic systems of interacting agents. The supply functionequilibrium (SFE) model of an oligopolistic market is used in simulation. Thepiece-wise affine and continuous supply functions which have a large number ofpieces are used to numerically estimate the equilibrium supply functions of anyshapes. An example based on the cost data from the real-world electricity industryis used to validate the approach presented in this paper. Simulation results showthat the coevolutionary approach robustly converges to SFE in different cases.The approach is robust and flexible and has the potential to be used to solve thecomplicated equilibrium problems in real-world oligopolistic markets.

Cooperative Co-evolutionary Approach (CCA) is a new architectureof evolutionary computation. Based on CCA, the paper proposes a new methodfor reactive power optimization problem in power system, which is non-convex,non-linear, discrete, and usually with a large number of control variables. Accordingto the decomposition-coordination principle, the reactive power optimizationproblem is decomposed into a number of sub-problems, which is optimizedby a single evolutionary algorithm population. The populations interactwith each other through a common system model and co-evolve and result inthe continuous evolution of the whole system. The reactive power optimizationproblem is solved when the co-evolutionary process ends. Simulation resultsshow that compared with conventional Genetic Algorithm (GA), CCA not onlycan obtain better optimal results, but also has better convergence property. CCAreduce the over-long computational time of GA and is more suitable for solvinglarge-scale optimization problems

将实验经济学的方法成功应用于寡头垄断电力市场研究，介绍了价值诱导原理、电力市场寡头垄断实验设计方案和实验过程，针对一个由3个厂商组成的寡头垄断实验市场进行了多次实验并对实验结果进行了严格的统计分析。实验结果表明，在寡头竞争市场环境、不对称成本函数和重复博弈条件下，市场竞争逐渐收敛到完全竞争均衡和纳什均衡之间的结果。被试者是否具有辅助决策工具对实验结果有显著影响，在具有辅助决策工具时，有限理性的被试者在重复博弈中能达到理论上的静态纳什均衡。所得结论为电力市场的仿真实验研究提供了方法论上的参考，也为寡头垄断电力市场的参与者行为和市场均衡分析提供了实验依据。

采用实验经济学的方法和多个商品同时拍卖的模型，研究了电力市场不同需求响应条件下统一价格竞价和PAB（pay-asbid）竞价的市场行为和发电商报价策略问题。实验结果表明，2种竞价机制下市场均能收敛到完全竞争均衡附近，但PAB竞价的市场平均价格高于统一价格竞价的市场平均价格且价格较稳定，因此购电费用较高；市场需求弹性较小时2种竞价机制的市场价格均有显著提高，但在发电容量充足时仍可保持充分的竞争性；在不同的竞价机制下，发电商将采取不同的报价策略，统一价格竞价中发电商之间的竞争更为明显。