Economic Dispatch of Thermal Units considering Valve-point Effect using Learning Backtracking Search Optimization Algorithm

The production of electric energy for power systems with the goal of minimizing the total production cost for existing active units in the power network is one of the most important issues of modern systems. In other words, the purpose of economic dispatching is proper and optimized planning for production units, by taking into account the existing nonlinear factors and limitations in the power network and manufacturing units. The issue of economic dispatch is a challenging, non-linear, and non-convex optimization problem, which due to its intricate characteristics, heuristic algorithms are utilized as the resolution. In this paper, the issue of economic dispatch has become an optimization issue considering non-linear constraints and it has been solved using learning backtracking search algorithm (LBSA). The proposed algorithm is hybrid of backtracking search algorithm (BSA) and teaching-learning based optimization (TLBO). In order to evaluate the efficiency of the proposed algorithm, two test systems are used as case studies and the obtained results are compared to that of other algorithms in the literature. Based on numerical results, the LBSA algorithm is capable of offering better solutions and, in some cases, solutions identical to other reported methods regarding the fuel cost.