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首页> 外文期刊>Operations Research: The Journal of the Operations Research Society of America >Optimal economic dispatch and risk management of thermal power plants in deregulated markets
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Optimal economic dispatch and risk management of thermal power plants in deregulated markets

机译:放松管制市场中火电厂的最佳经济调度和风险管理

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This paper presents a methodology for the valuation, optimization, market, margin and credit risk management of gas-fired power plants and associated tolling contracts. Term structure models for the power and gas forward curves are employed to facilitate hedging and risk adjustment and for improved forecasting of short-term prices. The model for the power forward curve is capable of reproducing the important phenomena often observed in power markets, including spot price spikes and spike clustering, negative prices, and the empirically observed volatility term structures of power and gas forward prices as well as the correlation term structure between these forward curves. The method solves the stochastic dynamic optimization problem that arises from the inclusion of the various operational constraints of gas-fired power plants including minimum uptime and downtime requirements, ramp rate restrictions and costs, variable output and efficiency rates, and minimum generation levels. The model involves the solution of a system of partial differential equations (PDEs), which are solved using the radial basis function (RBF) method. At each time step and operational configuration the model produces an analytic function (RBF expansion) for the value of the power plant as a function of the independent risk factors. These functions can be used for determining optimal operating strategies and can be differentiated analytically to obtain the relevant hedging statistics for the dynamic management of market risk. In addition, these value functions facilitate the calculation of the credit value adjustment (CVA) and potential future exposure (PFE) measurement of tolling contracts. The analytic differentiability of these value functions also facilitates the pricing and risk management of commodity contingent revolvers (CCRs), credit vehicles used to manage margin requirements that result from hedging market risk on an exchange.
机译:本文提出了一种用于燃气电厂及相关收费合同的估值,优化,市场,保证金和信用风险管理的方法。动力和天然气远期曲线的期限结构模型用于促进套期保值和风险调整,以及改善短期价格的预测。电力远期曲线模型能够重现在电力市场中经常观察到的重要现象,包括现货价格峰值和峰值集群,负价格,以及根据经验观察到的电力和天然气远期价格的波动期限结构以及相关项。这些正向曲线之间的结构。该方法解决了随机动态优化问题,该问题是由于燃气发电厂的各种运行约束包括最小运行时间和停机时间要求,斜坡率限制和成本,可变输出和效率率以及最小发电量而引起的。该模型涉及使用径向基函数(RBF)方法求解的偏微分方程(PDE)系统的求解。在每个时间步长和操作配置上,模型都会根据独立风险因素生成电厂价值的分析函数(RBF扩展)。这些功能可用于确定最佳操作策略,并可进行分析区分以获得用于动态管理市场风险的相关对冲统计数据。此外,这些价值功能还有助于计算通行费合同的信用价值调整(CVA)和潜在的未来风险敞口(PFE)。这些价值函数的分析可区分性也促进了商品或有左轮手枪(CCR)的定价和风险管理,CCR是用于管理由对冲市场风险对冲交易所产生的保证金要求的信贷工具。

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