Review on the Optimal Configuration of Distributed Energy Storage

Liu, Ziqi; Su, Tingting; Quan, Zhiying; Wu, Quanli; Wang, Yu

doi:10.3390/en16145426

Cited by 2 publications

(1 citation statement)

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“…In the distribution grid system containing a high percentage of grid-connected DPVs, reasonable access to the energy storage system can better solve the above problems [2,3], and the user side of the DESS configuration, because of its fast response and ease of control, can be adjusted in both directions and so on [4], and gradually become a popular choice of distribution grid to deal with the access of large-scale distributed DPVs, but the energy storage access to the distribution grid must be taken into account in the premise of the security of distribution grid. Inappropriate energy storage capacity configuration or charging and discharging operation curve will add uncertainty factors but are not conducive to the safe and stable operation of the DN [5,6].…”

Section: Introduction 1motivationmentioning

confidence: 99%

A Stackelberg Game-Based Model of Distribution Network-Distributed Energy Storage Systems Considering Demand Response

Li,

Peng,

et al. 2023

Mathematics

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In the context of national efforts to promote country-wide distributed photovoltaics (DPVs), the installation of distributed energy storage systems (DESSs) can solve the current problems of DPV consumption, peak shaving, and valley filling, as well as operation optimization faced by medium-voltage distribution networks (DN). In this paper, firstly, a price elasticity matrix based on the peak and valley tariff mechanism is introduced to establish a master–slave game framework for DN-DESSs under the DPV multi-point access environment. Secondly, the main model optimizes the pricing strategy of peak and valley tariffs with the objective of the lowest annual operating cost of the DN, and the slave model establishes a two-layer optimization model of DESSs with the objective of the maximum investment return of the DESSs and the lowest daily operating costs and call the CPLEX solver and particle swarm optimization algorithm for solving. Finally, the IEEE33 node system is used as a prototype for simulation verification. The results show that the proposed model can not only effectively reduce the operating cost of the distribution network but also play a role in improving the energy storage revenue and DPV consumption capacity, which has a certain degree of rationality and practicality.

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