Research on Generation Expansion Planning in Low-Carbon Economy Environment Under Incentive Mechanism of Renewable Energy Sources

Application of renewable energy sources promotes the emission reduction of CO2, however due to its prematuration the situation of high investment cost and low return of investment appears. To encourage the power generation technology using renewable energy sources, electric power industry proposes various incentive measures. Leading the green certificate trading mechanism and carbon emissions trading scheme into the generation expansion planning(GEP) model and considering system revenue, investment cost and operation cost within the planned period, a GEP model in low-carbon environment, in which the maximized net income of the planned system within the planned period is taken as the objective, is established, and such constraints as the quota of the renewable energy sources, the number of the sold or purchased green certificates and the trading volume of the carbon emission are added into traditional constraint conditions. Using discrete bacterial colony chemotaxis algorithm(DBCC), the optimization solution of the established model is performed, the result of GEP in low-carbon economy environment and the optimized result of traditional power source planning are compared and analyzed, and under three conditions, namely the different carbon tax levels, the different quota of carbon emission and the proportions of different renewable energy sources, the sensitivity analyses are carried out. The reasonableness of above-mentioned model and algorithm is validated by results of calculation examples.