| With the depletion of global fossil energy and the increasingly serious problem of environmental pollution,people urgently need a new energy supply system to realize the advantage complementary and cascade utilization of energy.The combined heat and power micro-energy grid(CHPMEG)has become the focus of people’s attention,because it can simultaneously meet the energy demand of users’ electricity,heat(cold)and gas,realize the complementary utilization of multiple energy sources and local accommodation of renewable energy.Reasonable optimal configuration of capacity and coordination of output state for the internal equipment in the CHPMEG can not only reduce the system investment and operation cost,improve the energy utilization efficiency and reduce the emission of pollutants,but also the ratio of the system utilization of the renewable energy power generation can also be improved.The thesis mainly aims at the shortcoming of the optimal configuration of CHPMEG and the improvement of the wind power accommodation model and strategy of the existing CHPMEG.The main contents of this thesis are as follows:First of all,in optimal configuration of CHPMEG considering the correlation and randomness of the wind power and photovoltaic power.In order to improve the credibility of configuring device capacity of CHPMEG,the traditional optimal configuration method only takes into account the randomness of the wind and the light in the data generation stage,and ignores the correlation between the wind and the light in the same region.In order to solve this problem,a scene data generation method based on Kendall rank correlation coefficient,nonparametric kernel density estimation,Copula theory and Monte Carlo simulation is proposed in this thesis,and the correlation and randomness of the wind power and photovoltaic power are considered in optimal configuration.At the same time,in the aspect of optimal configuration of the obj ective function,in addition to consider the investment operation cost of the system and the cost of environmental treatment,the evaluation index of energy supply reliability is introduced into the objective function by the method of penalty function,and the hybrid scheme genetic algorithm is used to solve the problem.Secondly,in wind power accommodation model and strategy of CHPMEG based on bidirectional electrical transformation of equipment side.In order to improve the ability of CHPMG to absorb local wind power,the traditional method decouples the "Following the Thermal Load" mode of CHP by adding heat storage equipment or electric boiler and heat storage equipment,so as to improve the ability of the system to absorb wind power.However,this method is difficult to realize the bidirectional conversion of the heat and electricity.In order to solve this problem,this thesis puts forward a wind power accommodation model and strategy for CHPMEG based on bidirectional transformation,which can not only decouple the operation mode of the "Following the Thermal Load" and "Following the Electric Load" of CHP simultaneously,but also realize the bidirectional transformation from "wind power to gas to electricity".Finally,in wind power accommodation strategy of CHPMEG based on user side response and thermal inertia.The existing methods of wind power accommodation in CHPMEG are generally improved from the equipment side to improve the ability of the system to use local wind power.At the same time,the heat load and electric load are treated with the same time response in the optimal operation.In view of the above problems,this thesis establishes a wind power accomodation strategy of CHPMEG,which takes into account the demand side response of electric load and thermal inertia,and improves the system’s ability to absorb wind power through the demand side response of electric load and the thermal storage characteristics of the house on the user side.The work done in this thesis can provide reference for the optimization of the CHPMEG and the improvement of its internal wind power utilization ratio. |
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