A distributionally collaborated planning of energy storage, transmission and distribution systems considering long- and short-term energy storage characteristics

Abstract

Inherent uncertainty and variability of renewable generation increasingly brings significant challenges to power systems planning and operation in that serious multi-scale spatio-temporal imbalances resulting in loss of load and significant renewable generation curtailment caused by excess generation co-exist. To address these new challenges, new types of planning method and operation strategy are required. This article proposes a distributed collaborative planning model for energy storage, transmission and distribution networks considering characteristics of long-term hydrogen energy storage (h-ESSs) and short-term electrochemical energy storage systems (ESSs). Firstly, the collaborative planning framework is proposed considering long- and short-term energy storage operational characteristics and their coupling mechanisms with network expansion planning. Secondly, the collaborative planning model of energy storage and transmission as well as energy storage and distribution networks are established to minimize the demand losses and renewable generation curtailment, in addition to minimizing overall investment and operational costs. The characteristics of long- term energy storage is utilized to ensure seasonal spatio-temporal generation and supply balances while the short- term energy storage is considered to smooth renewable energy uncertainty and fluctuations. Thirdly, considering energy storage, transmission and distribution systems as independent investment entities, in order to protect their privacy, a distributed robust alternating direction multiplier method (ADMM) was employed, in addition, Lagrangian multipliers and penalty parameters are dynamically updated to improve solution efficiency and convergence. Finally, the proposed method is applied to case studies. Results show that the proposed method effectively allocates h-ESS and ESSs to ensure supply-demand balance across all timescales, and as the RES penetration level increases, requirements for h-ESS rises much faster than ESSs, reaching 1.7 times that of ESS at the 70 % penetration rate, this is due to increased seasonal volatility. Furthermore, compared with independent planning practices, the proposed method reduces total cost by up to 10 % with significant reduction in RES curtailment, demonstrating the effectiveness and validity of the proposed method.