Operation Optimization Research On Renewable Combined Cooling Heating And Power(CCHP)systems

As the development of both urbanization and industrialization,Chinese energy consumption has increased significantly.More than half of the energy demands of buildings in metropolis are heating and cooling loads,and it is a trend to provide multiple energy demands.Meanwhile,extensive fossil fuel consumption resulted in the serious contamination.What’s more,massive power outrages happen frequently all over the world and lead to huge financial loss.Hence,high efficiency and environmentally friendly distributed power systems with multiple energy provision are required to mitigate this problem.Combined cooling,heating,and power(CCHP)systems follow the principle of cascade utilization of energy with high energy efficiency and can supply cooling,heating and power loads.Therefore,it is considered to be a crucial part of distributed energy systems in the future.However,such complex systems should be carefully managed to obtain optimal performance.Specifically,the uncertainties of renewables and loads make operation optimization a stochastic optimizing problem.The off-design performance requires nonlinear modeling to describe the equipment of CCHP systems.The presence of energy storage leads to dynamic correlations between adjacent operating stages in multi-stage optimization.Hence,the operating optimization of CCHP systems is a stochastic dynamic nonlinear problem,which requires much more investigation.In this paper,we propose a stochastic dynamic solving method to solve the aforementioned optimization problem.This method can help the CCHP system to operate at high efficiency and improve its performance.The main work of this thesis is as follows:Firstly,this research presents a typical CCHP system with storage units,and the off-design performance model of power generating unit is established.In addition the energy flux relationship is obtained by equipment modeling and system structure.The complex CCHP system’s state transition equation is extracted by selecting the stored cooling and heating energy as the discretized state variables.Setting the operating cost as evaluation index,the CCHP system operation optimization is modeled.Then,balancing the merits and demerits of existing researches,the traditional solving method is discarded.Considering a recently renewed study,a dynamic solving method is proposed.The operation optimization of CCHP system with energy storage units is abstracted as a shortest path problem of a weighted graph.This problem is divided into a host of small static optimization problems by dynamic programming.Referring to the concept of variable cost and constant cost,repeated computations are saved.Furthermore,the photovoltaic is introduced in this traditional CCHP system,to handle the randomness of renewables and load,the abovementioned method is improved to stochastic dynamic solving method.At last,electric,cooling,and heating loads as well as renewables outputs of one typical day in summer was applied to verify the proposed method.In rolling optimization simulation,the operating strategy is optimized per hour.As shown in the result,the operating cost is reduced considerably.Hence,the conclusion can be drawn that the proposed method can solve the stochastic dynamic nonlinear CCHP system operation optimization problem successfully.