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• An improved multi-timescale coordinated control strategy is proposed to be used in an integrated energy system. • A hybrid energy storage system is introduced into the system. • Operating costs and carbon emissions are considered as the optimization objectives. • General rules for sizing hybrid energy storage system are proposed in this paper. In view of the complex energy coupling and fluctuation of renewable energy sources in the integrated energy system, this paper proposes an improved multi-timescale coordinated control strategy for an integrated energy system (IES) with a hybrid energy storage system (HESS). The power response characteristics of various devices in IES at different time scales are analyzed which shows that the multi-timescale coordinated control method can be well coupled with the IES including HESS. The advantages of HESS over single energy storage system in stabilizing power fluctuation and extending energy storage life are compared and analyzed while the control method of supercapacitor under multi-time scale coordinated control strategy is proposed. The primary energy consumption, operating costs, carbon dioxide emissions and load shedding costs are considered the optimization objectives in the day-ahead rolling optimization stage according to the day-ahead forecast renewable energy (RE) data. In the intraday rolling adjusting stage, the proposed method can reduce the effect of the RE day-ahead forecasting errors to achieve the intraday energy scheduling balance and ensure the safe operation of the devices of IES. Considering the background of IES with a high proportion of renewable energy, this paper makes innovative use of the advantages of HESS to improve the power response characteristic of the system. The high-frequency part of RE is balanced by HESS in the real-time coordinated control stage. A typical structure of IES is applied and the simulation results are analyzed to show the performance of the proposed method in this paper. Moreover, general rules for sizing of HESS are also proposed. The influence of the hybrid energy storage capacity allocation ratio on battery capacity loss and carbon emission reduction is discussed. The Pareto front including the configuration and cost of supercapacitor has been obtained. As shown in the case, the application of HESS in the IES can improve the power response characteristic, extend the lithium-ion battery (LiB) life and has more benefits in reducing carbon emissions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Regions where feed-in tariff higher than valley price should follow dual objective optimization. • The economy of the household PV-BES-EV system mainly depends on the purchase cost of EVs. • Decreasing electricity price will not undermine the effectiveness of the household PV-BES-EV system. • The energy bills and carbon emissions decrease significantly with the optimal scheduling schemes. The household PV-BES-EV system (photovoltaic - battery energy storage - electric vehicle system) connected to the grid can guarantee the electricity demand of the household and facilitate the flexible trade with the grid to achieve the goals of cutting energy bills and reducing carbon emissions. In related issues, past studies often assume that renewable energy is both economical and environmentally friendly, and thus regarded it as the primary power source. While in fact, in some regions where the feed-in tariff is higher than the sales price at a certain time, households may be driven by arbitrage opportunities to frequently purchase electricity from the grid at the certain time to gain benefits, resulting in far greater carbon emissions than expected within the household measurement boundary. To avoid the environmental burden caused by pure economic incentives and to provide practical and sustainable solutions consistent with various energy price policies, the optimal scheduling schemes of the household PV-BES-EV system that considers both economic and environmental incentives for different scenarios solved by the genetic algorithm is proposed in this paper. Household data in Shanghai, China and Hamburg, Germany were selected for modelling, representing the dual-objective optimization scenario with arbitrage opportunities and the single-objective optimization scenario with sales price higher than feed-in tariff, respectively. Results show that for urban and rural residents in Shanghai, the energy bill and carbon emission would decline about 105%, 48% and 88%, 62%, respectively. As for Hamburg, the accordingly results would be 69% and 64%. In addition, based on the cost-effectiveness of the system in long-term, this paper puts forward policy recommendations that align with local conditions to further improve the economy of the system. [ABSTRACT FROM AUTHOR]