Research On Renewable Energy Consumption Strategy Based On Cuckoo Search Algorithm

With the increasing severity of energy shortage and environmental problems,it has changed the way of human energy consumption and promoted the rapid development of new energy technologies.How to improve energy efficiency,improve the consumption of renewable energy by power grids,and achieve energy cleanliness and sustainable development are the common concerns of all countries in the world today.The volatility and randomness of renewable energy generation,such as wind energy and solar energy,have a serious negative impact on the security,stability and economic operation of the power system.Therefore,the research on renewable energy absorption has become an important topic.This paper establishes the dispatching model from three aspects:wind-water-fire integrated system,virtual power plant and regional integrated energy,and uses cuckoo search algorithm to solve the problem,in order to explore the strategy of renewable energy consumption.In order to study the application of hydropower station in wind power consumption:First,water flow and head height are used to transform water flow and head height into power station output,and the uncertainty of wind power output is expressed as a prediction error with zero mean and normal distribution;Therefore,a joint scheduling model of wind water and fire power system is constructed;The scheduling model takes the minimum system cost as the objective function,including coal consumption cost of thermal power unit,management cost of hydropower station,management cost of wind farm and prediction error cost;Hydraulic and thermal constraints,water flow constraints,and speed constraints of thermal power units are taken as constraints in the model.Finally,the new burgeoning bird search algorithm is used to solve it.The simulation results show that the hydropower station can play a good role in peak shaving in the power system,make up the random fluctuation of wind power output,reduce the system peak and valley difference,reduce the frequent change of the power unit output,reduce the system reserve capacity,increase the security,stabilityand power supply reliability of the power system.The virtual power plant consisting of uncontrollable renewable energy and controllable energy can reduce the impact of renewable energy uncertainty on the power grid and improve the reliability of power supply.The objective function is the benefit of a wind/PV/gas/storage virtual power plant,and using the penalty function method to introduce the constraints into the objective function.The cuckoo search algorithm was used to solve the model,and the output of each plant in the virtual power plant was obtained.The uncertainty of wind power and PV output is expressed as a prediction error with zero mean and normal distribution.And the influence of normal distribution coefficient on prediction error and virtual power plant was analyzed.The impact of time-of-use power price and energy storage equipment on the virtual power plant is analyzed.The results demonstrate the validity of the proposed model and algorithm.A new method and way for the economic dispatch of the virtual power plant was provided.The integrated regional energy system,which is composed of electric / gas / heat / cold and other energy sources,can unify the planning and dispatching of grid power,natural gas and distributed energy,and realize the complementary advantages of different energy sources,it is the important direction of future energy system development.The scheduling model of the integrated regional energy system was built,which contains wind,light,gas,electricity,heat,and cold.The model takes the minimum cost of the integrated energy system as the objective function subjected to the power supply,heat(cold)supply balance and operation of micro gas turbine.According to the "thermal power setting" and "electricity fixed heat" modes,four scenarios are set in the summer and winter seasons,the scheduling model is solved under the four scenes by using the cuckoo search algorithm to obtain the output of each participant in the integrated regional energy system under the four scenarios,and the operation cost of the regional integrated energy system under the four scenarios is compared and analyzed.Finally,the model is solved by traditional particle swarm optimization and genetic algorithm,and the results are compared with those obtained by cuckoo search algorithm.The results demonstrate the validity of the proposed model and algorithm,and get a more suitable running strategy,which provides a new method and approach for the economic dispatch of the regional integrated energy system.