Optimal sizing & siting of DG with load models using genetic algorithm under different loading conditions

Abstract

The majority of states/provinces now have renewable portfolio standards, with many requiring that over 20 percent of electricity sales be generated by renewable energy sources within the next five to fifteen years. A combination of public policy, incentives and economics is driving a rapid growth of distributed generation in the electric power system. The majority of these requirements will be addressed by adding significant amounts of wind energy and growing amounts of solar energy to the bulk power system. Wind and solar power plants exhibit greater variability and uncertainty because of the nature of their “fuel” sources. Optimization is one of the tools that can be used to address concerns and costs around this variability and uncertainty. This report discusses operational and market system impacts, provides background on what can be realistically expected from distributed generation power-output forecasting, and proposes recommendations to deploy forecasting systems into operational use.