摘要翻译：
为了降低市场参与者的机会成本（如发电商的未收回成本），本文对二元变量非凸电力市场的近均衡价格进行了研究。机会成本是指市场参与者按照市场经营者的指令自由作出决定时的利润与市场参与者根据市场价格自由作出决定时的利润之差。我们使用最小互补近似最小总机会成本(MTOC)模型，从以前的研究，并测试了一个更现实的机组组合(UC)模型比以前的研究，包括特征，如储备要求，斜坡约束，最小上升和下降时间。与以前的研究一样，所建立的模型包含了弹性价格响应需求，但由于并非所有需求都是价格响应的，我们考虑了总需求是固定和弹性混合的更现实的情况。与以前的MTOC研究相比，另一个改进是计算性的：虽然以前的研究在目标函数的连续变量中含有非凸项，但我们将目标转化为在连续变量中只含有线性和凸二次项的等价形式。在一系列敏感性分析中，我们将机组组合模型与UC的标准社会福利优化版本进行了比较，不同的弹性需求代表了未来电动汽车和智能家电的不同渗透程度，不同的发电可用率，以及不同的输电线路容量值以考虑可能的阻塞。最小总机会成本和社会福利解决方案在不同情况下大多非常接近，但在一些极端情况下除外。
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英文标题：
《Extended opportunity cost model to find near equilibrium electricity
  prices under non-convexities》
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作者：
Hassan Shavandi, Mehrdad Pirnia, J. David Fuller
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  This paper finds near equilibrium prices for electricity markets with nonconvexities due to binary variables, in order to reduce the market participants' opportunity costs, such as generators' unrecovered costs. The opportunity cost is defined as the difference between the profit when the instructions of the market operator are followed and when the market participants can freely make their own decisions based on the market prices. We use the minimum complementarity approximation to the minimum total opportunity cost (MTOC) model, from previous research, with tests on a much more realistic unit commitment (UC) model than in previous research, including features such as reserve requirements, ramping constraints, and minimum up and down times. The developed model incorporates flexible price responsive demand, as in previous research, but since not all demand is price responsive, we consider the more realistic case that total demand is a mixture of fixed and flexible. Another improvement over previous MTOC research is computational: whereas the previous research had nonconvex terms among the objective function's continuous variables, we convert the objective to an equivalent form that contains only linear and convex quadratic terms in the continuous variables. We compare the unit commitment model with the standard social welfare optimization version of UC, in a series of sensitivity analyses, varying flexible demand to represent varying degrees of future penetration of electric vehicles and smart appliances, different ratios of generation availability, and different values of transmission line capacities to consider possible congestion. The minimum total opportunity cost and social welfare solutions are mostly very close in different scenarios, except in some extreme cases.
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PDF链接：
https://arxiv.org/pdf/1809.09734