Objectives Traditional electric energy storage has limitations in scale, duration, and environmental impact.Moreover, the renewable energy absorption capacity in the microgrid is low, and low-carbon and economy cannot be taken into account in planning. In order to solve the above problems, based on the basic working principle of hydrogen energy storage, hydrogen energy storage was incorporated into the microgrid instead of traditional electric energy storage, and a low-carbon and economic synergy bi-level optimization configuration model of microgrid with hydrogen energy storage was established. Methods The upper-level planning model aimed at minimizing the comprehensive equivalent annual value of the microgrid, based on the joint operation of electricity and hydrogen. The carbon trading mechanism was introduced to plan the capacity of various power generation equipments in the microgrid, which can enhance the low-carbon of the system. The lower-level operation model aimed to minimize the sum of the absolute values of the difference between the new energy output and the load demand. The model also encouraged users to adopt diversified demand-side response behaviors with the goal of accurately tracking the new energy output curve, and feeded back the user’s energy consumption behavior to the upper-level model to optimize the load curve. On the basis of improving the absorption capacity of new energy, the system economy is further improved, deeply exploring the synergy between the low-carbon and economic characteristics of microgrids. Results The simulation results of microgrid in a certain industrial park show that the proposed method yields a planning scheme with excellent low-carbon and economy. Compared with the traditional planning method, the low-carbon and economy are improved by 53.6% and 37.1%, respectively. Conclusions The model presented in this paper not only enhances the capacity for new energy absorption but also further improves the system economic performance. It achieves a synergistic enhancement of the microgrid low-carbon and economy.

Objectives Battery energy storage system is one of the effective means to ensure the reliability of photovoltaic (PV) power generation system and improve the utilization rate of PV power generation. However, there are some problems in the PV-energy storage power station, such as the difficulty of power fluctuation suppression and the unreasonable configuration of energy storage capacity. In order to solve these problems, relevant research was carried out. Methods For energy-based battery energy storage, the characteristics of scheduling mode and autonomous mode were analyzed, and a power-limited suppression strategy of PV-energy storage system based on energy storage operation in scheduling mode was proposed to realize power suppression and reduce the frequency of energy storage charge/discharge switching. The optimization objective of minimizing abandoned power losses in the PV-energy storage system was established, with constraints such as the probability of power fluctuation exceeding the limit. An algorithm was used to solve and optimize the energy storage configuration. Taking the 50 MW Sangzhuzi PV-energy storage power station in Langming, Tibet as an example, the effectiveness of the proposed grid-connected power suppression strategy was validated. Results The proposed grid-connected power suppression strategy can reduce the probability of power fluctuation exceeding the limit from 25.64% to 6.41% without increasing the frequency of energy storage charge/discharge switching. When the probability of grid-connected power fluctuation exceeding the limit is 5%, the optimal configuration for the energy storage system of the power station is determined to be 14.5 MW/94 MW⋅h. Conclusions The proposed power fluctuation suppression strategy and energy storage optimization configuration method can provide technical reference for the optimal design and operation of grid-connected PV-energy storage system.

To exploit the schedulable potential of electric vehicles (EVs) efficiently and relieve the energy supply pressure of microgrids with a high proportion of new energy sources, a multi-time-scale optimization scheduling model of the microgrid is proposed, considering the participation of EV resources combined with the multi-demand response technology. In the day-ahead scheduling stage, some EV resources are combined with the price-based demand response technology to optimize comprehensive user satisfaction. Based on the scheduling plan of the EV resources based on price, the microgrid is optimized focusing on minimizing economic cost, ensuring low-carbon expenditure, and maximizing flexibility satisfaction, and the scheduling arrangement of the adjustable resources on each side is determined. In the intra-day scheduling phase, another portion of the EV resources is combined with the incentive demand response technology. The microgrid energy management center, as the leader, aims to minimize the operating costs, and the incentive EV group, as the follower, aims to minimize the electricity costs. The intra-day master-slave game model of the microgrid was constructed for rolling optimization, and the two sides played the game based on a subsidized price and energy use strategy. Finally, a simulation verification was conducted based on a microgrid scenario, and the results show that the proposed model can reduce the electricity cost of users, reduce the peak-valley difference of the load curve, and realize the full absorption of new energy.