Bacteria foraging optimization algorithm based strategic bidding in electricity markets

In an electricity market, suppliers are more concerned with maximizing their profit and minimizing risk. To achieve this, optimal bidding strategy of a supplier has been formulated as a Bi-Level Multi Objective Optimization Problem (BLMOOP), in which lower level problem represents market clearing process by System Operator (SO) for minimization of customers' payments. Upper level problem is a multi objective formulation, which considers profit maximization and risk minimization simultaneously. An ε-constraint method has been used to obtain pareto-optimal solutions of the BLMOOP. A fuzzy approach has been used to derive the most efficient solution among the pareto-optimal solutions. Upper level objective functions are highly nonlinear. Therefore, Bacteria Foraging Optimization (BFO) algorithm, a relatively new heuristic approach, has been applied to obtain the best solution to the BLMOOP for day-ahead hourly market. The effectiveness of the proposed method has been established on 30-bus test system. The results, obtained using the BFO algorithm, have been compared with those obtained using Sequential Quadratic Programming (SQP) based approach, a classical optimization method.