Artificial Immune Network Combined with Normative Knowledge for Power Economic Dispatch of Thermal Units

摘要

Recently, many research activities have been devoted to Artificial Immune Systems (AISs). AISs use ideas gleaned from immunology to develop intelligent systems capable of learning and adapting. AISs are optimization methods that can be applied to the solution of many different types of optimization problems in power systems. In particular, a new meta-heuristic optimization approach using artificial immune networks called opt-aiNET combined with normative knowledge, a cultural algorithm feature, is presented in this paper. The proposed opt-aiNET methodology and its variants are validated for a economic load dispatch problem consisting of 13 thermal units with incremental fuel cost function takes into account the valve-point loadings effects. The proposed opt- aiNET approach provides quality solutions in terms of efficiency compared with other existing techniques in literature for load dispatch problem with valve-point effect.