Abstract Recently, employing environmentally-friendly devices such as Energy Storage Systems (EESs) and Renewable Energy Resources (RERs) has been one of the remarkable ways to deal with the increasing trend of fossil fuel cost as well as environmental issues. Due to the stochastic nature of the RERs, especially wind farms and their effects on power system operation and planning, the ESS is used to alleviate output fluctuations of the renewable resources. The reduction of daily fuel cost is justified by the utilization of the ESS. In this research, the day-ahead scheduling of the ESS is concerned with reducing the fuel cost and the emission pollutants of thermal power plants considering load and wind speed uncertainties. The optimal day-ahead scheduling of the ESS has been obtained through using the proposed stochastic bi-objective optimization framework. Based on the proposed approach, the uncertainties are taken into account by the scenario-based decision-making technique as a time-efficient method. Pareto optimal solutions have been derived by the epsilon-constraint technique. Consequently, the fuzzy satisfying approach is employed to find the conservative decision based on the network planner’s perspective. The system under the study is IEEE 30 BUS system. In the presence of the uncertainties, it has been concluded that peak shifting and peak shaving can be achieved by the optimal scheduling of the ESS. Moreover, the ESS effects on the hourly electricity generation cost and the hourly emission pollutants have been discussed. Finally, the ESS has been used to simultaneous cost-emission reduction.

中文翻译：

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通过提出的基于随机 MINLP 的双目标优化方法对集中式储能系统进行日前调度

摘要 近年来，采用诸如储能系统 (EES) 和可再生能源 (RER) 等环保设备已成为应对化石燃料成本上升趋势和环境问题的重要方法之一。由于 RER 的随机性，尤其是风电场及其对电力系统运行和规划的影响，ESS 用于缓解可再生资源的输出波动。ESS 的使用证明了每日燃料成本的降低是合理的。在本研究中，ESS 的日前调度涉及在考虑负载和风速不确定性的情况下降低燃料成本和火力发电厂的污染物排放。通过使用所提出的随机双目标优化框架，已经获得了ESS的最佳日前调度。基于所提出的方法，基于场景的决策技术将不确定性考虑在内，作为一种省时的方法。帕累托最优解已经通过 epsilon 约束技术推导出来。因此，基于网络规划者的观点，采用模糊满足方法来寻找保守决策。研究的系统是IEEE 30 BUS系统。在存在不确定性的情况下，已经得出结论，可以通过ESS的优化调度来实现移峰和调峰。此外，还讨论了 ESS 对每小时发电成本和每小时排放污染物的影响。最后，