考虑竞价风险的多目标优化发电研究

基于交易日市场电价预测曲线,采用概率统计方法对竞价风险进行评估,并在发电成本中纳入有害气体排放控制成本,以竞价风险最低化和全天发电期望利润最大化为目标,构建可体现机组出力与市场电价之间协调联动关系的机组交易日分时段出力多目标优化模型;通过将非劣排序操作与微分进化算法有机融合及改进以克服进化早熟和搜索不均匀等问题,设计出一种新型多目标微分进化算法对模型进行求解,并采用模糊集理论提取总体最优解。最后通过算例仿真,验证了本文方法能有效降低发电商对竞价风险的敏感性,可实现低风险、高收益的竞价上网。

Multi-Objective Optimization of Thermal Power Units Output Considering the Bidding Risk

A new multi-objective optimization model for bidding and generating of thermal power units during the transaction day was established to minimize bidding risk and maximize generating profit,where bidding risk is assessed by probability statistics method based on forecasted electricity prices curves,and emissions cost is included in generation cost,and the coordinated interactive relation between unit output and market price is reflected.Moreover,a new multi-objective optimization algorithm is proposed to solute this model,in which the non-dominated sorting mechanism is integrated with the differential evolution algorithm,and the hybrid algorithm is improved to overcome the premature convergence and search bias problems,and fuzzy set theory is employed to extract the general best solution.Results of case simulation show that the effectiveness to reducing the sensitivity of bidding risk and the contribution to achieving low-risk bidding and high-profit generating of the proposed method.