Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainti...Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.展开更多
Heat exchanger systems(HXSs)or heat recovery steam generators(HRSGs)are commonly used in 100 kW to 50 MW combined cooling,heating,and power(CCHP)systems.Power flow coupling(PFC)is found in HXSs and is complex for rese...Heat exchanger systems(HXSs)or heat recovery steam generators(HRSGs)are commonly used in 100 kW to 50 MW combined cooling,heating,and power(CCHP)systems.Power flow coupling(PFC)is found in HXSs and is complex for researchers to quantify.This could possibly mislead the dispatch schedule and result in the inaccurate dispatch.PFC is caused by the inlet and outlet temperatures of each component,gas flow pressure variation,conductive medium flow rate,and atmosphere condition variation.In this paper,the expression of PFC is built by using quadratic functions to fit the non!inearit>of thermal dynamics.While fitting the model,the environmental condition needs prediction,which is calculated using phase space reconstruction(PSR)Kalman filter.In order to solve the complex quadratic dispatch model,a hybrid following electricity load(FEL)and following thermal load(FTL)mode for reducing the dimension of dispatch model,and a feasible zone analysis(FZA)method are proposed.As a result,the PFC problem of CCHP system is solved,and the dispatch cost,investment cost,and the maximum power requirements are optimized.In this paper,a case in Jinan,China is studied.The PFC model is proven to be more precise and accurate compared with traditional models.展开更多
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.
基金the National Natural Science Foundation of China(No.61733010).
文摘Heat exchanger systems(HXSs)or heat recovery steam generators(HRSGs)are commonly used in 100 kW to 50 MW combined cooling,heating,and power(CCHP)systems.Power flow coupling(PFC)is found in HXSs and is complex for researchers to quantify.This could possibly mislead the dispatch schedule and result in the inaccurate dispatch.PFC is caused by the inlet and outlet temperatures of each component,gas flow pressure variation,conductive medium flow rate,and atmosphere condition variation.In this paper,the expression of PFC is built by using quadratic functions to fit the non!inearit>of thermal dynamics.While fitting the model,the environmental condition needs prediction,which is calculated using phase space reconstruction(PSR)Kalman filter.In order to solve the complex quadratic dispatch model,a hybrid following electricity load(FEL)and following thermal load(FTL)mode for reducing the dimension of dispatch model,and a feasible zone analysis(FZA)method are proposed.As a result,the PFC problem of CCHP system is solved,and the dispatch cost,investment cost,and the maximum power requirements are optimized.In this paper,a case in Jinan,China is studied.The PFC model is proven to be more precise and accurate compared with traditional models.
