Economic Optimal Dispatching Method of Power Microgrid under Environmental Uncertainties

With the rapid growth of electric energy consumption and environmental concerns, renewable energy resources, power quality and reliability, has become the fields of interest for many researchers. By integrating renewable energy resources such as wind and solar power into a power microgrid (PMG), we can give consideration to both sides of environmental issue and energy independency. A PMG is a localized grouping of electricity generation units, energy storage devices and loads, within which, power can be generated locally to reduce dependence on long distance transmission lines and cut transmission losses. The point of coupling with traditional centralized grid can be disconnected, so that PMG can function autonomously to ensure high reliability in case of blackouts in traditional grid. But wind and solar power are easily affected by weather condition so that uncertainty has been introduced into this economic optimal dispatching (EOD) problem. To deal with power shortage or violation of technical limitations, a PMG model containing battery as an energy buffer is built and a chance-constrained programming (CCP) based particle swarm optimization (PSO) method is proposed in this paper to solve the economic optimal dispatching problem.