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The battery energy storage system (EES) deployed in power system can effectively counteract the power fluctuation of renewable energy source. In the planning and operation process of grid side EES, however, the incorporation of power flow constraints into the optimization problem will strongly affect the solving efficiency. Therefore, a bi‐level planning and operation co‐optimization model for EES is proposed based on a constraint boundarization technique. Firstly, a constraint boundarization method for considering power flow constraints is proposed to solve the efficiency problem of the optimization model. Secondly, in terms of the upper and lower bounds of storage's operation curve obtained by the constraint boundarization method, an operation risk evaluation index is defined to describe the potential risk of storage planning scheme. Thirdly, this paper establishes a bi‐level planning and operation co‐optimization model for EES, in which the planning problem with a goal of minimizing total cost is taken as an outer layer and the operation problem for pursuing renewable energy consumption and reducing the load curtailment is taken as an inner layer. Finally, case studies are carried out, and results demonstrate the feasibility and effectiveness of the proposed model and method. [ABSTRACT FROM AUTHOR]

Equipment maintenance decision is a very critical technology in power grid asset management. The traditional maintenance decision focuses on the analysis of the operation performance of the equipment itself, but lacks the analysis and description of the fuzziness of power equipment outage parameters. Therefore, this paper establishes the reliability assessment model based on equipment health condition monitoring, which makes the maintenance decision transition from equipment level to system level, and the fuzzy mathematics theory is introduced to establish a model describing the fuzziness of equipment failure rate parameter to make system reliability assessment and equipment maintenance decision scheme. Firstly, this paper proposes a fuzzy failure rate model of power transformer based on condition monitoring. Then the fuzzy parameters are combined with the conventional probabilistic reliability assessment method to establish the fuzzy probability hybrid reliability assessment model of the transmission system, and the fuzzy maintenance reliability benefit index is defined and deduced. Finally, a maintenance strategy of transformer based on fuzzy probability hybrid reliability assessment and fuzzy set theory is proposed, and the case study is carried out on a regional power grid in East China. The results show that the proposed model provides an improved maintenance strategy of power equipment. [ABSTRACT FROM AUTHOR]

• This paper proposes quantum computing models (including device's reliability model and system's reliability model) and an efficient quantum sampling method. • This paper proposes a universal quantum modeling approach for describing the reliability indices LOLP and EENS. • This paper proposes an IQAE-based reliability indices calculation method to achieves accuracy improvement compared to classical methods. Aiming at the reliability assessment of power system, the state sampling process as a critical step requires to generate power system states one by one using classical computer. Due to the quantum superposition, all system states can be generated at once using the quantum computing and then assess the reliability, and thus it will improve the assessment efficiency. However, how to sample system states and assess reliability using the quantum computing theory will be very important. Therefore, this paper proposes a power system reliability assessment technique and its modeling approach based on the quantum computing theory. Firstly, this paper develops a quantum model of power system reliability (including reliability models of electrical device and system) and proposes a new system state sampling method based on the quantum computing theory, which samples all system states at once and improves the sampling efficiency. Secondly, this paper proposes a quantum computing theory based on reliability assessment technique and its modeling approach for the reliability indices: Loss of Load Probability (LOLP) and Expected Energy Not Supplied (EENS). Thirdly, this paper uses an iterative quantum amplitude estimation (IQAE) algorithm to measure the reliability indices for improving the measurement accuracy. Finally, this paper investigates both designed Case and RBTS, and results shows the correctness and effectiveness of reliability assessment of power system based on the quantum computing. [ABSTRACT FROM AUTHOR]