Heat-Electricity Integrated Energy System Modelling And Optimal Dispatch

In recent years,the significance of boosting the economy and social welfare without sacrificing environment has drawn more attention at the global stage,as the challenges associated with climate change,instability of fossil fuels price and energy crisis become more and more prominent.Currently,the drastic growth of both energy demand and generation in China along with its increasing political and economic influences enables it to be among the most competitive players in the playground of sustainable energy future.However,China is facing an obscure and challenging energy situation,with relatively insuff-icient energy efficiency,a considerable amount of wind and solar generation shedding and energy reliability issues.To create a reliable,efficient and green energy system is inevitable.The high penetration of distributed generation(DG),mainly wind and solar power,has introduced significant uncertainties into the power system because of its intermittent and unpredictable nature,leading to power quality violating,demand-supply balance difficulty and costly infrastructure investment.In order to accommodate the DGs,an innovative idea of a multi-energy system has been brought up,incorporating electricity,heating,cooling and gas system.Conventionally,the different energy sectors are planned,designed and operated separately,due to the non-synchronized development stages.The integration and coordination of such systems has the untapping potential of improving overall energy efficiency,minimizing the energy cost and reducing GHG(Green House Gas)emissions.In this study,a multi-energy system consisting of renewable energy generation,electric vehicles,heat storages,electric heat pumps,energy storages,is presented and modelled to maximize its economic and environmental benefits.The modelling algorithm consisting of:(1)the uncertainty in the renewable generation is incorporated utilizing the K-means clustering method to generate representative scenarios;(2)whilst the heat demand is simulated with the day-ahead outdoor temperature forecast;(3)district heating system is implemented and modelled to supply heat demand via water pipelines;and(4)the dispatch of the system under real-time electricity pricel is then modelled to minimize the energy costs and carbon dioxide emissions along with several cases utilized to test the applicability of the proposed model.Numerical results confirm the effectiveness of the proposed model,as the system energy cost from grid importation as well as the peak net demand(satisfied by the power imported from the grid)decrease compared with no energy storages.