Low-carbon Economy Flexible Generation Expansion Planning Under The Incentive System Of Renewable Energy

As a source of power industry emissions of polluting gases, reasonable power structure is crucial important to the environment. The development of low-carbon electricity has important meaning for the implementation of the low carbon economy and sustainable development of the electric power. 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 they have a positive impact on low carbon emissions of power system economic operation. But the uncertainties of the load forecasting and other factors have increased the difficulty of GEP. Therefore, the problem of low-carbon and economy flexible generation expansion planning under the incentive system of renewable energy is studied as follows:At first, the background of the connotation and principle of incentive mechanism of renewable energy sources are expounded and the incentive mechanism is introduced. The classification of renewable energy power is discussed. Typical and modern GEP models are discussed.Moreover, a new type GEP model of both economy and low carbon is put forward, where the objective based on system revenue, investment cost and operation cost are established. Using discrete bacterial colony chemotaxis(DBCC) algorithm, 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, the influences of different carbon tax levels, the different quota of carbon emission and the proportions of different renewable energy sources are analyzed. The reasonableness has verified the feasibility of the model and the rationality of the algorithm by results of calculation examples.At last, the low-carbon and economy flexible generation expansion planning under the incentive system of renewable energy is established. The uncertainties which influence the GEP are analyzed and the concept of adaption cost is introduced. Describe the uncertainties’ s changing process by the linear model or the exponential model and the scenarios are applied to deal with the various uncertainties in the GEP and use k-means clustering algorithm to reduce the scenarios. Indice of flexibility is defined to facilitate the analysis of the planning’s flexibility. The established GEP optimal model is solved by the improved DBCC algorithm. Results of numerical examples show that the proposed model and algorithm are reasonable.