Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEHS).Considering the thermal quasi-dynamics in pipelines,the mea...Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEHS).Considering the thermal quasi-dynamics in pipelines,the measurement equations in heating systems are dependent on the estimated results,leading to an interdependency between OA and SE.Conventional OA methods require measurement equations be known exactly before SE is performed,and they are not applicable to IEHSs.To bridge this gap,a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency.As its core procedure,the observable state identification and observability restoration are formulated in terms of integer linear programming.Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.展开更多
基金supported by National Natural Science Foundation of China(52177086)Fundamental Research Funds for the Central Universities(2023ZYGXZR063).
文摘Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEHS).Considering the thermal quasi-dynamics in pipelines,the measurement equations in heating systems are dependent on the estimated results,leading to an interdependency between OA and SE.Conventional OA methods require measurement equations be known exactly before SE is performed,and they are not applicable to IEHSs.To bridge this gap,a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency.As its core procedure,the observable state identification and observability restoration are formulated in terms of integer linear programming.Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.
