In this paper, a stochastic multi-objective structure is introduced in joint energy and reserve market to allow energy generation companies (GENCOs) participating in the short-term hydro-thermal self-scheduling with wind, photovoltaic uncertainty and small-hydro units. In addition, uncertainties including energy price, spinning and non-spinning reserve prices as well as the uncertainty of renewable energy resources such as output power of the wind, PV and small-hydro power plants are mentioned. One pivotal feature of this study is that two methods are used to generate stochastic multi-objective scenarios, namely lattice monte carlo simulation and roulette wheel mechanism. After that, the main purpose of the study is described, i.e., making GENCOs able to achieve the maximum profit and the minimum emission by using a multi-objective function considering a stochastic process. To reach this aim, the mixed integer programming which includes a set of multi stage deterministic scenarios is employed. However, some special cases should be introduced in the formulation structure of the presented scheduling regarding hydro-thermal units to make the SMO-HTSS problem with wind, PV and SH units alike real time modeling. Since optimal Pareto solutions are produced in this method, one can allude to the application of the ε-constraint method. Nevertheless, in order to select one of the most appropriate solutions among Pareto solutions obtained, the utilization of fuzzy method has been presented. In the end, some tests are carried out on an IEEE 118-bus test system to verify the accuracy and validity of the proposed method.

本文在能源和储备联合市场中引入了一种随机的多目标结构，以允许发电公司（GENCO）参与具有风能，光伏不确定性和小水电单元的短期水热自调度。此外，提到了不确定性，包括能源价格，自旋和非自旋储备价格，以及可再生能源的不确定性，例如风能，光伏和小型水力发电厂的输出功率。这项研究的一个关键特征是使用了两种方法来生成随机的多目标场景，即格子蒙特卡洛模拟和轮盘赌轮机制。之后，描述了研究的主要目的，即 通过考虑随机过程的多目标函数，使GENCO能够实现最大的利润和最小的排放。为了达到这个目的，采用了包括一组多阶段确定性场景的混合整数编程。然而，在所提出的调度表的结构中，应该引入一些特殊情况，涉及水热机组，以使SMO-HTSS问题与风能，PV和SH装置相似，并进行实时建模。由于以这种方法产生了最佳的帕累托解决方案，因此可以暗示该方法的应用。在所提出的日程安排的表述结构中，应该引入一些关于热液单元的特殊情况，以使带有风，PV和SH单元的SMO-HTSS问题类似于实时建模。由于以这种方法产生了最佳的帕累托解决方案，因此可以暗示该方法的应用。在所提出的日程安排的表述结构中，应该引入一些关于热液单元的特殊情况，以使带有风，PV和SH单元的SMO-HTSS问题类似于实时建模。由于以这种方法产生了最佳的帕累托解决方案，因此可以暗示该方法的应用。ε-约束方法。然而，为了从所获得的帕累托解中选择最合适的解之一，提出了模糊方法的利用。最后，在IEEE 118总线测试系统上进行了一些测试，以验证所提出方法的准确性和有效性。