| In recent years,along with the large scale integration of renewable energy generation,the operation mode of China’s electrical power system has changed thoroughly.The generation side of electrical power system is no longer absolute stable and controllable due to the randomness and intermittency of renewable energy generation.The bilateral randomness from both supply and demand side of electrical power system is emerging:for one thing,the generation side can not form stable and predicable generation supply due to the tight correlation between renewable energy generation and environmental factors,for another,the randomness of demand side still exists though lots of demand side management and demand side response programs have been put into implementation.Therefore,the traditional way of fulfilling power demand,which relies on expanding the supply side,is difficult to continue in the future.Hence problems about how to solve the bilateral randomness problem and form new planning and operation mode has become the hot research topic in China.This paper has proposed a new operation mode of electrical power system based on the coordination between "Generation-Grid-Load-Energy Storage".On one hand,along with the coordinative cooperation between generation,grid,load and energy storage,to form relatively controllable generation supply based on the optimized generation combination between renewable energy generation and peak-shaving generation resources.On the other hand,to lead power demand to track the generation supply through demand side management,demand side response and charge-discharge of energy storage devices.The optimized bilateral optimization process will be a possible solution to bilateral randomness problem.The operation mode presented above includes planning,dispatch,decision-making and other several steps,this paper focuses on the planning part and aims to brought the coordination between "Generation-Grid-Load-Energy Storage"into planning stage and provide decision making basis and references to system planning.First and foremost,theoretical research of coordinative optimized planning of"Generation-Grid-Load-Energy Storage".Its connotation and structure has been proposed according to bilateral coordinative optimization theory and methods.The coordinative optimization operation mode and its detailed process has been designed,at the same time,key technologies and representative projects were summarized at last.Second,research of the robust optimization model for microgrid system planning.The robust optimization model for microgrid system has been proposed from micro level,the robustness constraints based on the deviation between real deviation and estimated deviation of distributed generation has been proposed.Meanwhile The robust optimization model with robustness constraints were made,related NSGA-Ⅱ method was proposed and put into example analysis.Third,research of robust optimal planning model for power system considering demand side response.The electrical power system planning optimization was carried out from demand side on macro level.The uncertainty of load changes caused by demand side response was described using elasticity according to economic principles.This paper has built a multi-objective robust optimization model with planning cost,operation cost and pollution minimization as its objective functions.Besides,improved NSGA-II method was introduced to solve the above model.The rationality of proposed model was proved through example analysis,under the unknown range of demand side response elasticity(which means its load change is difficult to predict under demand side response policies),it is able to get optimal system planning schemes considering demand side response uncertainty with minimum planning and operation cost.Fourth,research of optimized planning model between supply and demand side based on "Generation-Grid-Load-Energy Storage" coordination.The prediction model of wind power as well as photovoltaic generation have been built considering related probability distribution.Besides,the direct load control and dynamic time-of-use price programs were proposed.This paper has built the "Generation-Grid-Load-Energy Storage" planning model with the objective functions of operation cost and gas emission minimization,meanwhile the system planning cost was one of its constraints.At last,multi-objective particle swarm optimization method has been proposed and put into an empirical analysis,which has proved the significance of model in achieving bilateral coordination of electrical power system with minimun operation cost and pollution under planning cost constraints.Fifth,research of power system planning simulation based on Monte Carlo Method.This paper has designed the Multi-linear Monte Carlo method based on linear cut of probability distribution of wind generation,photovoltaic generation and load.Besides,the system planning model has been built with planning cost,operation cost and pollution minimization as its objective functions,and the superiority of Multi-linear Monte Carlo method has been proved through example analysis.Meanwhile the system operation of power system planning has been simulated through the proposed method to get the results of several key system indexes and has provided scientific basis for system planning decisions.Last but not least,research of evaluation model for "Generation-Grid-Load-Energy Storage" planning of electrical power system based on improved DEA model,meanwhile related policies and mechanisms to promote the implementation of bilateral coordination planning has been proposed.The evaluation indexes,which includes four aspects(generation,grid,load and energy storage),were derived based on the basic theory,planning and simulation methods of above coordinative optimization.The improved DEA model was proposed and put into example analysis and sensitivity analysis.Besides,planning mechanisms and related policies were designed according to evaluation results in order to provide policy guarantee for related planning methods,models and implementation of "Generation-Grid-Load-Energy Storage" coordinative optimization. |
PDF Full Text Request