A new approach based on ant colony algorithm to distribution management system with regard to dispersed generation

Electric power industry has found a way to break and change the old domination by large utilities that had an overall authority over all activities in generation, transmission and distribution of power within its domain of operation. These changes in power system (deregulation) along with environment pollution problems, and technology advancement to make small-scale generators economically, have caused customers to prefer local generation, which do not need transmission lines. Therefore the usage of DGs is increasing, which leads to necessity of their impacts study on distribution systems. One of the most important problems in distribution system is distribution management system (DMS), which can be affected by DGs. Some DMS algorithms have already developed by researchers [1–9]. The aim of this paper is to present a new approach to distribution management system with regard to Distributed Generations. In the proposed algorithm, DMS is divided two parts: • State Estimation • Optimal Operation Management In other words, at first, state variable of distribution network have been estimated and then optimal operation management has been done based on results of state estimation. In State Estimation part, DGs and Loads that do not have constant outputs, are considered as state variables, the output values of which is obtained by minimizing the difference between measured and calculated values. The target of Optimal Operation Management part is to minimize cost reactive power production of DGs, reactive power cost of capacitors and energy losses with controlling tap of Load Tap Changers Transformers and Voltage Regulators, reactive power of capacitors and reactive power of DGS. In overall view, Distribution management system is an optimization problem including continuous and discrete variables. Because of existence of DGs, Voltage Regulators (VRs), SVCs, Load tap Changers (LTC) and etc. in distribution system, it is difficult to solve by ordinary and classic methods which objective function and constraints should be continuous and derivative. It is seemed that evolutionary approaches are the best choice for solving these problems. Recently, a new evolutionary global optimization technique known as ant colony optimization (ACO) has become a candidate for many optimization applications. The ant colony optimization has been used to solve several combinatorial optimization problems such as the Traveling Salesman Problem (TSP), Quadratic Assignment Problem (QAP), Job Shop Scheduling Problem (JSP), Single Machine Total Tardiness Problem (SMTTP), Unit Commitment, Economic Dispatch of Power system, Hydroelectric Generation Scheduling, reactive power pricing in deregulated system, voltage and var control in distribution systems and so on[10–18]. The paper is organized as follows. Section II defines Distribution Management System formulation with regard DGs. Section III presents evaluation cost of distributed generation. In section IV ant colony mechanism has been presented Simulation results will be brought in section V. Finally, section VI presents conclusion.