A combination of MADM and genetic algorithm for optimal DG allocation in power systems

摘要: Distributed Generation (DG) can help in reducing the cost of electricity to customer, relieve network congestion, provide environmentally friendly energy close load centers as well promote system technical characteristics such loss reduction, voltage profile enhancement, reserve mitigation and many other factors. Furthermore, its capacity is also scalable it support at distribution level. The planning studies include penetration level placement evaluation which are influenced directly by DG type. Most previous publications this field chose one or two preferred parameter basic objective implement optimizations systems. But due small size DGs output, according just parameters usually leads more theoretical results with incorporation less resources. optimization might degrade another attribute. In paper a multi-objective Generators (DGs) examined, concerning both economical power using Genetic Algorithm (GA) combined Multi-Attribute Decision Making (MADM) method. fact, GA best plans for determined. For approaching aim, 4 system, including total losses, buses profile, lines limits reactive flow, consider appropriate priorities applied each objective. next step, Analytic Hierarchy Process (AHP) along Data Envelopment Analysis (DEA) used multi attribute decision making technique form framework selecting place units. attributes defined parameters. voltages on buses, losses transmission emissions, congestion capital cost. proposed approach illustrated case IEEE 30 bus demonstrate significant improvement through procedure.