Battery energy storage systems (BESSs) are important for the operation and optimisation of the islanded microgrid (MG).However, the BESSs will have different dynamics due to the differences in characteristics and operating conditions, leading to unbalanced state‐of‐charges (SoCs). On the other hand, because of the unequal line impedances, the conventional reactive power‐voltage ( Q–V ) droop control results in disproportional reactivepower‐sharing. To deal with suchissues, a power ‐frequency ( P–f ) droop‐based decentralised SoC balancing strategy is developed first to regulate the active power outputs of BESSs in terms of SoCs, thus ensuring SoC balancing among BESSs. Furthermore, the authors develop a Q–V droop‐based decentralised reactive power‐sharing strategy to dispatch the reactive power among BESSs in terms of their respective reactive power ratings. In this way, compared with the existing control strategies, the proposed control method is fully decentralised, which removes the necessity for both the central controller and communication links. Moreover, the proposed control method has a simpler control structure with the plug and play capability. Finally, the simulation results are presented in an islanded MG to demonstrate the effectiveness, plug and play capability of the proposed control method.

The rise of electric vehicles (EVs) fosters closer integration between the power and transportation sectors. While implementing a fair EV charging pricing strategy optimizes the system economic performance, modeling EV users’ behaviors and their elastic demand in response to charging prices remains a significant challenge. This paper proposes a novel pricing scheme for EV charging within power-transportation systems using a tri-level framework that considers the interactions among the power distribution network (PDN), charging network operator (CNO), and EVs. To capture the responsive behaviors of EVs, a user equilibrium (UE) model with price-elastic demand is formulated as a quasi-variational inequality (QVI). This approach reduces the tri-level pricing problem to a bi-level optimization problem by merging the middle and lower levels into an optimization problem with QVI constraints, thereby achieving mathematical tractability. The outer level optimizes energy dispatch in the PDN, while the inner level focuses on the CNO's pricing optimization in response to elastic EV demand. To solve the problem, a projection gradient algorithm and a tailored fixed-point algorithm are developed. Simulation results confirm the effectiveness and superiority of the proposed model and algorithms. Sensitivity analysis further shows that elasticity and regulation significantly affect system efficiency, demonstrating the model's robustness.

An enormous challenge for the harmonic state estimation of distribution network is how to perceive the complex and varied dynamic harmonics in a higher resolution method. To solve this problem, this paper proposes an interval dynamic harmonic high-resolution state estimation method for distribution network based on multi-source measurement data fusion. Firstly, to obtain the typical high-resolution harmonic measurement information of distribution networks under the limited measurement devices, a selection method for the measurement sites of high-resolution power quality monitoring devices (PQMDs) is proposed based on the harmonic electrical distance. On this basis, a multi-source data fusion method based on the time period inclusion index is proposed to establish hybrid interval measurement datasets. Secondly, to improve the efficiency of interval dynamic harmonic state estimation, the interval intermediate variables are introduced to construct the three-stage hybrid interval harmonic measurement equations. Finally, an interval dynamic harmonic high-resolution state estimation method is proposed based on the predictor-corrector method, the IGG-III robust interval Kalman filter (IGGIII-RIKF) is used as the predictor stage, and the forward-backward interval constraint propagation algorithm (FBICP) is used as the corrector stage to realize interval dynamic harmonic high-resolution state estimation. The effectiveness and feasibility of the proposed method have been demonstrated on the IEEE 33-bus system and the IEEE 118-bus system.