The Research Of Generation Rights Trade Based On Particle Swarm Optimization Algorithm

With the development of economy, China’s energy consumption is growing rapidly, whichresults in massive pollutant. The energy and environment problems become one of the mostimportant obstacles in China’s economic and social development. Power industry is a basicindustry with high consumption of energy so that energy saving and emission reduction ofpower industry plays an important role in integrated national strategy.Generation rights trade is an effective measure to optimize power supply structure and tosave energy. But GTR will cause many security problems in power system, such as thechange of power flow congestion. Traditional GTR organizes exchange in high and lowmatching method without considering grid security constraints. But GTR is the marketeconomy activity in power system, so for its solution cannot be separated from the nature ofthe power system, it must meet the constraints of security and steady operation of powersystem. The deals are said to be mutually coupled because power system is a nonlinear system,so the high and low matching method will result in congestion in grid, then influence theeffect of GTR. Based on domestic and foreign research and practical GTR experiences, thispaper designs a solution considering the safety constraints and searches the optimal solutionin the high dimensional, nonlinear generation trading solution space using particle swarmoptimization algorithm. PSO algorithm processes the result of transactions parallelly, it avoidsthe effect of the order and it will gain the optimal solution which maximizes society utilityand the effect of energy saving and emission reduction. This will not only optimize powersupply structure, but also ensure the safety operation of grid.