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首页> 外文期刊>Systems Journal, IEEE >Joint Energy and Spinning Reserve Market Clearing Incorporating Wind Power and Load Forecast Uncertainties
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Joint Energy and Spinning Reserve Market Clearing Incorporating Wind Power and Load Forecast Uncertainties

机译：结合风能和负荷预测不确定性的联合能源和旋转备用市场结算

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摘要

This paper proposes an energy and spinning reserve market clearing (ESRMC) mechanism for wind–thermal power system, considering uncertainties in wind power and load forecasts. Two different market models for the ESRMC are proposed. One model includes reserve offers from the conventional thermal generators, and the other includes reserve offers from both thermal generators and demand/consumers. The stochastic behavior of wind speed and wind power is represented by the Weibull probability density function (pdf), and that of the load is represented by a normal pdf. This paper considers two objectives: total cost minimization and the system-risk-level minimization. The first objective includes the cost of energy provided by thermal and wind generators, and the cost of reserves provided by thermal generators and loads. It also includes costs due to overestimation and underestimation of available wind power and load demand. The system risk level is considered as another objective as wind power is highly uncertain. Multiobjective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the ESRMC problem. The results of the IEEE 30 bus system demonstrate the utility of the proposed approach.
机译：考虑到风电和负荷预测的不确定性，本文提出了一种用于风热发电系统的能源和空转储备市场清算（ESRMC）机制。提出了ESRMC的两种不同的市场模型。一种模型包括传统热力发电机的储备报价，另一种模型包括热力发电机和需求/消费者的储备报价。风速和风能的随机行为由威布尔概率密度函数（pdf）表示，而负荷的随机行为由正常pdf表示。本文考虑了两个目标：总成本最小化和系统风险级别最小化。第一个目标包括由热力发电机和风力发电机提供的能源成本，以及由热力发电机和负载提供的储备成本。它还包括由于高估和低估了可用风能和负载需求而导致的成本。由于风电的高度不确定性，系统风险等级被认为是另一个目标。多目标强度帕累托进化算法2+（SPEA 2+）已用于解决ESRMC问题。 IEEE 30总线系统的结果证明了该方法的实用性。

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