Research On Reactive Power And Electricity Price Risk Management In Electricity Market Environment

The power industry restructuring breaks the vertically integrated monopoly of the tranditional power industry with the aim of introducing competition, improving efficiency optimizing resource allocation and reducing power price. However, many new problems and challenges have emerged during the restructuring process. Two vital problems are damage to system caused by insufficient reactive power support, as well as financial risks due to fluctuations of electricity market prices. If these new problems are not properly solved, the emerging electricity market may not be able to grow healthily and even the security and stability of power system associated operation could be endangered. This dissertation focuses on the study of reactive power related issues and on the research of price risk management in the electricity market environment and some significant results are obtained.This dissertation first reviews the reactive power related issues, which include costs of reactive power, Var pricing, procurement and payment of Var, Var dispatch and reactive market power. As followed, literatures on price risk management problem are reviewed.Physical characteristics of reactive power equipments, including synchronous generator, shunt capacitor, synchronous compensator, transformer tap changer, SVC, and STATCOM, are compared firstly. Fixed costs and variable costs of different reactive power sources in electricity market environment are estimated. And then the fixed cost allocation between active power and reactive power provided by synchronous generator is put forward. Meanwhile, this paper indicates one mistake in calculating investment costs of reactive capacity with yuan/MVA expression. The calculation of opportunity costs of synchronous generator in providing reactive power services is illustrated. Lastly, the annual component of fixed cost taking account of return on capital is presented.Appropriate determination of reactive power requirements is an important issue for maintaining voltage stability, decreasing transmission losses, and mitigating the potential exercise of reactive market power. A model is developed for annual procurement of reactive power capacity considering the possible outage of multiple Var sources in electricity market environment. The objective is to minimize the total cost, including the cost of purchasing reactive power capacity, load shedding and generation redispatch. A method based on the Monte-Carlo simulation and Differential Evolution algorithm is served for solving the established optimization problem. Simulation results from case studies demonstrate the essential features of the developed model and method.Reactive market power has been regarded as a vital problem for its negative effect on the efficient operation of the market. Up to now, research work on the evaluation index for reactive market power has been mainly based on technical characteristics of power system. However, the strategic bidding between market participants is not taken into account. Given this background, an agent-based market simulation framework is presented for analyzing the game behaviors and resulting reactive market power of market participants. Replicator dynamics algorithm is utilized to simulate agents' rational behavior of pursuing maximum profits. Two models, in which minimum reactive power requirement is taken into account, are presented for describing uniform-price auction and pas-as-bid (PAB) auction in reactive power market. The reactive market power is calculated using well-know price cost margin index. The CIGRE 32-bus system is used for case studies. Simulation results demonstrate the essential features of the developed model and method. Furthermore, the analysis results indicate that reactive market power in uniform-price auction is more severe than that in PAB auction.The study on probability density function and distribution function of electricity prices contributes to the power generators and purchasers to estimate their own management accurately, and helps the regulator monitor the periods seriously deviating from normal distribution. Based on the assumption that load presents normal distribution, combining serious non-linear characteristic of aggregate supply curve, this paper has theoretically derived the distribution of electricity prices as the function of random variable of load utilizing knowledge of probability theory. And the conclusion has been validated with the electricity price data of California, PJM and Zhejiang markets. The result shows that electricity prices obey normal distribution approximately only when supply-demand relationship is very loose, whereas the prices deviate from normal distribution highly and present seriously right-skewness characteristic. Moreover, the real electricity markets also display the narrow-peak characteristic when undersupply occurs.Participants can sign forward bilateral contracts several months in advance of its delivery for mitigating price risk in electricity markets. Up to now, the research work for bilateral contracts has concentrated on the effect of bilateral contracts on reducing price risk. Given this background, we propose a systematic negotiation scheme through which a generator and distribution company can reach a mutually beneficial and risk tolerable forward bilateral contract. Under this approach, the generator and distribution company respond rationally to a stream of bilateral offers/counter-offers considering their respective benefits while accounting for the risks incurred by the uncertainty in the pool spot price. Each negotiating party can choose its own definition of benefits and risk, which are expected utility in this paper. Concession factor is utilized to illustrate the negotiation strategy of participants. The reservation expected utility and reservation expected profit are added to this approach to model the tolerable limits of risk and benefit. Numerical tests show that this flexible negotiating framework can be readily put into practice.