With the development of energy internet technology,the operational optimization of regional electricity-heating-gas systems is becoming a key research area.Considering that the thermal system’s quasi-dynamic characte...With the development of energy internet technology,the operational optimization of regional electricity-heating-gas systems is becoming a key research area.Considering that the thermal system’s quasi-dynamic characteristics will make the dispatching of regional multi-energy systems more accurate,the flexibility and energy efficiency of electricity-heating-gas system’s operations can be improved.The quasi-dynamic characteristics of regional thermal networks are analyzed here,as well as the demand side of the heating system.Based on thermal inertia characteristics,the virtual thermal energy storage models of both thermal networks and buildings,considering the thermal comfort index,are formulated synthetically for a central heating system.By comparing the operating results of different adjustment methods,a quality adjustment method is found to have the most flexibility for regional heating system control.With the hot water supply network and heating load modeling considering virtual storage,an operational optimization model for a regional electricity-heating-gas system is presented with the purpose of reducing the total operating costs.Numerical results show the effectiveness of the proposed method.Through a case study,it is found that when considering the virtual energy storage specialty for both the heating supply and demand side,the heating load can be shifted across the time periods under a time-of-use(TOU)price,leading to the obvious economic improvement of multienergy system operation.展开更多
Multi-energy microgrids,such as integrated electricity-heat-gas microgrids(IEHS-MG),have been widely recognized as one of the most convenient ways to connect wind power(WP).However,the inherent intermittency and uncer...Multi-energy microgrids,such as integrated electricity-heat-gas microgrids(IEHS-MG),have been widely recognized as one of the most convenient ways to connect wind power(WP).However,the inherent intermittency and uncertainty of WP still render serious power curtailment in the operation.To this end,this paper presents an IEHS-MG model equipped with power-to-gas technology,thermal storage,electricity storage,and an electrical boiler for improving WP utilization efficiency.Moreover,a two-stage distributionally robust economic dispatch model is constructed for the IEHSMG,with the objective of minimizing total operational costs.The first stage determines the day-ahead decisions including on/off state and set-point decisions.The second stage adjusts the day-ahead decision according to real-time WP realization.Furthermore,WP uncertainty is characterized through an Imprecise Dirichlet model(IDM)based ambiguity set.Finally,Column-and-Constraints Generation method is utilized to solve the model,which provides a day-ahead economic dispatch strategy that immunizes against the worst-case WP distributions.Case studies demonstrate the presented IEHS-MG model outperforms traditional IEHS-MG model in terms of WP utilization and dispatch economics,and that distributionally robust optimization can handle uncertainty effectively.展开更多
基金supported by National Natural Science Foundation of China(No.U22B20112 and No.U1766203)。
文摘With the development of energy internet technology,the operational optimization of regional electricity-heating-gas systems is becoming a key research area.Considering that the thermal system’s quasi-dynamic characteristics will make the dispatching of regional multi-energy systems more accurate,the flexibility and energy efficiency of electricity-heating-gas system’s operations can be improved.The quasi-dynamic characteristics of regional thermal networks are analyzed here,as well as the demand side of the heating system.Based on thermal inertia characteristics,the virtual thermal energy storage models of both thermal networks and buildings,considering the thermal comfort index,are formulated synthetically for a central heating system.By comparing the operating results of different adjustment methods,a quality adjustment method is found to have the most flexibility for regional heating system control.With the hot water supply network and heating load modeling considering virtual storage,an operational optimization model for a regional electricity-heating-gas system is presented with the purpose of reducing the total operating costs.Numerical results show the effectiveness of the proposed method.Through a case study,it is found that when considering the virtual energy storage specialty for both the heating supply and demand side,the heating load can be shifted across the time periods under a time-of-use(TOU)price,leading to the obvious economic improvement of multienergy system operation.
文摘Multi-energy microgrids,such as integrated electricity-heat-gas microgrids(IEHS-MG),have been widely recognized as one of the most convenient ways to connect wind power(WP).However,the inherent intermittency and uncertainty of WP still render serious power curtailment in the operation.To this end,this paper presents an IEHS-MG model equipped with power-to-gas technology,thermal storage,electricity storage,and an electrical boiler for improving WP utilization efficiency.Moreover,a two-stage distributionally robust economic dispatch model is constructed for the IEHSMG,with the objective of minimizing total operational costs.The first stage determines the day-ahead decisions including on/off state and set-point decisions.The second stage adjusts the day-ahead decision according to real-time WP realization.Furthermore,WP uncertainty is characterized through an Imprecise Dirichlet model(IDM)based ambiguity set.Finally,Column-and-Constraints Generation method is utilized to solve the model,which provides a day-ahead economic dispatch strategy that immunizes against the worst-case WP distributions.Case studies demonstrate the presented IEHS-MG model outperforms traditional IEHS-MG model in terms of WP utilization and dispatch economics,and that distributionally robust optimization can handle uncertainty effectively.
