The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch ...The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.展开更多
This paper proposes a coordinated two-stage real-time market mechanism in an unbalanced distribution system which can utilize flexibility service from home energy management system(HEMS)to alleviate line congestion,vo...This paper proposes a coordinated two-stage real-time market mechanism in an unbalanced distribution system which can utilize flexibility service from home energy management system(HEMS)to alleviate line congestion,voltage violation,and substation-level power imbalance.At the grid level,the distribution system operator(DSO)computes the distribution locational marginal prices(DLMPs)and its energy,loss,congestion,and voltage violation components through comprehensive sensitivity analyses.By using the DLMP components in a firststage optimization problem,the DSO generates two price signals and sends them to HEMS to seek flexibility service.In response to the request of DSO,each home-level HEMS computes a flexibility range by incorporating the prices of DSO in its own optimization problem.Due to future uncertainties,the HEMS optimization problem is modeled as an adaptive dynamic programming(ADP)to minimize the total expected cost and discomfort of the household over a forward-looking horizon.The flexibility range of each HEMS is then used by the DSO in a second-stage optimization problem to determine new optimal dispatch points which ensure the efficient,reliable,and congestionfree operation of the distribution system.Lastly,the second-stage dispatch points are used by each HEMS to constrain its maximum consumption level in a final ADP to assign consumption level of major appliances such as energy storage,heating,ventilation and air-conditioning,and water heater.The proposed method is validated on an IEEE 69-bus system with a large number of regular and HEMS-equipped homes in each phase.展开更多
基金supported by State Key Laboratory of HVDC under Grant SKLHVDC-2021-KF-09.
文摘The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.
基金Supported by the National Natural Science Foundation ofChina under Grant No.60745002(国家自然科学基金)the National Basic Research Program of China under No.2003CB317002(国家重点基础研究发展计划(973))
文摘This paper proposes a coordinated two-stage real-time market mechanism in an unbalanced distribution system which can utilize flexibility service from home energy management system(HEMS)to alleviate line congestion,voltage violation,and substation-level power imbalance.At the grid level,the distribution system operator(DSO)computes the distribution locational marginal prices(DLMPs)and its energy,loss,congestion,and voltage violation components through comprehensive sensitivity analyses.By using the DLMP components in a firststage optimization problem,the DSO generates two price signals and sends them to HEMS to seek flexibility service.In response to the request of DSO,each home-level HEMS computes a flexibility range by incorporating the prices of DSO in its own optimization problem.Due to future uncertainties,the HEMS optimization problem is modeled as an adaptive dynamic programming(ADP)to minimize the total expected cost and discomfort of the household over a forward-looking horizon.The flexibility range of each HEMS is then used by the DSO in a second-stage optimization problem to determine new optimal dispatch points which ensure the efficient,reliable,and congestionfree operation of the distribution system.Lastly,the second-stage dispatch points are used by each HEMS to constrain its maximum consumption level in a final ADP to assign consumption level of major appliances such as energy storage,heating,ventilation and air-conditioning,and water heater.The proposed method is validated on an IEEE 69-bus system with a large number of regular and HEMS-equipped homes in each phase.
