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The unbalanced load distribution, the single-phase connection of renewable energy, and the uncoordinated charging of electric vehicles (EVs) will bring a severe issue corresponding to the three-phase unbalance in modern distribution networks. To deal with this issue, a novel multistage optimal dispatching model with the hybrid energy storage system (HESS), consisting of the battery energy storage system (BESS), EV, and supercapacitor (SC), is proposed in this paper. The first stage is conducted on the day-ahead stage, driven by minimizing the total operation cost and relieving power unbalance, the unbalanced penalty cost is introduced into the optimal dispatching model with the electricity purchasing cost and the degradation cost of HESS. Also, the chance-constraint stochastic programming (SP) model with the coordinated operation of HESS is accommodated to handle the diverse uncertainties of renewable energy, load demand, and EV users' behaviors. In the intra-day operation stage, a rolling optimization-based dispatch model is formulated to re-optimize the operation of the SC for the rapid response of mitigating the real-time three-phase unbalance caused by renewable energy. The numerical experiments are executed on the IEEE 34-bus three-phase test system. Compared with the cases without considering SC and the degradation cost of HESS, the power unbalance in the proposed model is reduced by 3.27% and 3.62% per day at the real-time stage, respectively, while total operation cost is reduced by 46.77 US$ and 350.62 US$ per day, respectively. The results validated that the proposed model is efficient in reducing the three-phase unbalance under multi-time scales, improving the economic operation of the distribution network. • Three-phase power unbalance reduction is achieved by hybrid energy storage system. • Supercapacitor is embedded with BESS and EV in day-ahead and intra-day stages. • Multi-stage optimization scheduling model proposed to minimize power unbalance. • Rolling optimization employed in intra-day stage to address short-term unbalance. [ABSTRACT FROM AUTHOR]

Reliability improvement is regarded as a crucial task in modern distribution network expansion planning. Compared to previous works, this paper presents a bi-level optimization model to optimize the planning of the distribution network complying with multiple renewable energy and energy storage system (ESS) functionalities to guarantee the economical and reliable operation of the distribution network. The candidate assets include substations, distribution lines, renewable energy-based distributed generations (DGs), and ESSs are systematically involved. The load level affected by seasonal change and the multiple uncertainties, including renewable energy, load fluctuation, and contingency outage, are comprehensively considered. The uncertainties caused by the stochastic of renewable energy and load demand are described using Latin Hypercube Sampling (LHS) method. To address the computational burden and complexities associated with non-linear AC power flow, the mixed-integer linear programming (MILP)-based bi-level model is proposed via piecewise linearization methodology. Therein, the upper-level optimization model is proposed to minimize the total present value cost of the planning scheme in normal operating conditions. The lower level model, which is constrained to investment decision-making of the upper-level framework, aims to minimize the total cost of expected energy not supplied (EENS) considering the uncertainties of the single contingency outage. The effectiveness of the proposed bi-level planning model is validated by numerical studies to guarantee economic and reliability improvement for distribution network. • Multiple uncertainties are comprehensively considered in the proposed model. • Branches and multi-type generators are incorporated to the joint planning model. • Optimal allocation and reliability assessment are coordinated to build bi-level model. • The benefits from ESS for reliability enhancement is analyzed. [ABSTRACT FROM AUTHOR]