Capacity expansion of stochastic power generation under two-stage electricity markets
Capacity expansion of stochastic power generation under two-stage electricity markets
复制标题
两阶段电力市场下随机发电扩容
DOI：
10.1016/j.cor.2015.12.007
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
J. Morales
中科院分区：
文献类型：
--
作者：
S. Pineda;J. Morales
由于电力预测误差引起的能源失衡对电力系统的运行成本和随机发电机组的盈利能力都有很大的影响。在本文中，我们提出了一个模型框架来分析这些不平衡成本对随机发电机组扩张的影响。这一框架包括对提前一天的明确表示和一个平衡的市场结算机制，以适当地捕捉发电量预测误差对电力系统短期运行的影响。所提出的发电量扩张问题首先是从社会规划者的角度来描述一个完全竞争的市场。我们研究了两种典型的市场设计对发电扩展计划的影响：一种是按照传统的成本择优排序原则进行出清的提前一天市场，另一种是考虑其对平衡运营成本的影响来确定提前一天调度决策的理想市场出清程序。此外，我们对所提出的模型进行了重新表述，以确定使随机发电商合谋的利润最大化的最优扩张决策，以探讨投资水平上的竞争效应。该模型首先被描述为多层规划问题，然后在一定的假设下，利用对偶理论将其重塑为单层混合整数线性或非线性优化问题。随机发电量和需求水平的预测在整个规划周期内的变异性是使用年持续时间曲线来建模的。同样，与电力预测误差有关的不确定性通过情景集来表征。最后，以丹麦电力系统为例，讨论了所提模型的主要特点和结果。
Energy imbalances due to power forecast errors have a significant impact on both the cost of operating the power system and the profitability of stochastic power generating units. In this paper, we propose a modeling framework to analyze the effect of the costs of these imbalances on the expansion of stochastic power generating units. This framework includes the explicit representation of a day-ahead and a balancing market-clearing mechanisms to properly capture the impact of forecast errors of power production on the short-term operation of a power system. The proposed generation expansion problems are first formulated from the standpoint of a social planner to characterize a perfectly competitive market. We investigate the effect of two paradigmatic market designs on generation expansion planning: a day-ahead market that is cleared following a conventional cost merit-order principle, and an ideal market-clearing procedure that determines day-ahead dispatch decisions accounting for their impact on balancing operation costs. Furthermore, we reformulate the proposed models to determine the optimal expansion decisions that maximize the profit of a collusion of stochastic power producers in order to explore the effects of competition at the investment level. The proposed models are first formulated as multi-level programming problems and then recast, under certain assumptions, as single-level mixed-integer linear or non-linear optimization problems using duality theory. The variability of the forecast of the stochastic power production and the demand level throughout the planning horizon is modeled using yearly duration curves. Likewise, the uncertainty pertaining to power forecast errors is characterized through scenario sets. The main features and results of the proposed models are discussed using an illustrative example and a more realistic case study based on the Danish power system.
DOI：
10.1016/j.cor.2012.09.002
发表时间：
2014
期刊：
Comput. Oper. Res.
影响因子：
--
作者：
S. Dempe;S. Franke
通讯作者：
S. Dempe;S. Franke