Abstract
In order to solve the multi-objective energy optimization problem with conflicting sub-objectives, fuzzy optimization theory is used in this chapter. The optimization model of multi-objective economic-operated combined heat and power (CHP) microgrid system considering heating income is established in this chapter. The microsources can provide both active and reactive power in the model. A typical microgrid consists of a wind turbine, a photovoltaic, a storage battery, a microturbine, a fuel cell, and heating and electric loads. The maximum fuzzy satisfaction degree method is adopted to transform the multi-objective optimization problem into a nonlinear single-objective optimum problem. The improved genetic algorithm is used to optimize microsources’ active and reactive output and the satisfaction degree of multi-objective optimization for grid-connected mode considering spot price. And the single-objective and multi-objective optimal values are comparatively analyzed. Simulation results show that multi-objective model is more precise than single-objective model in reflecting the actual operation characteristics of microgrid and the better environmental benefits can be reached at operation cost as low as possible in this model. So the validity of the proposed model and algorithm is proved.
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