Multi-Objective Antlion Algorithm for Short-Term Hydro-thermal Self-scheduling with Uncertainties

In this paper, a stochastic multi-objective structure is introduced in joint energy and reserve market to allow energy generation companies participating in the short-term hydro-thermal self-scheduling with uncertainties. To solve this problem, an antlion optimization (ALO) algorithm is used. In addition, uncertainties including energy price, spinning and non-spinning reserve prices, output power of the wind, photovoltaic and small hydro units are mentioned. In this study, two methods are used to generate stochastic multi-objective scenarios, namely lattice monte-carlo simulation and roulette wheel mechanism (RWM). 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 (MIP) 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, photovoltaic and small hydro units similar to the real time modeling. Since optimal solutions are produced in this method, one can allude to the application of the epsilon-constraint. 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, as shown in this paper, the ALO algorithm is limited to the epsilon-constraint; some tests are carried out on an IEEE 118-bus test system to verify the accuracy and validity of the proposed method.