Towards Developing a Large Distributed Energy Storage Using a Weighted Batteries Scheduling Scheme

Abstract

The energy storage system (ESS) is the next major disruption to the current architecture of the electricity grid. Energy storage offers several benefits to the electricity grid, which include frequency regulation, energy arbitrage, peak shaving, reducing intermittency of renewable energy sources (RESs), and many other benefits that are not possible without large energy storage. Large-scale batteries are still expensive and cannot be readily used with a reasonable return on investment. Aggregating a large number of consumers' small scale batteries may provide us with the benefits of large central storage. However, aggregated small-scale batteries have several advantages over large central storage. Small-scale batteries provide better scalability and open up many new investment opportunities for the grid as well as for the consumers. In this paper, we present a control scheme for small-scale distributed batteries, namely, Weighted Batteries Scheduling (WBS) scheme to make a large distributed energy storage. We also present a method to calculate weights, that are required for the WBS scheme, by prioritizing the batteries with respect to the state-of-charge (SOC). We evaluate the fairness of the proposed scheme using Jain's fairness index and entropy-based fairness index. The proposed storage model can be used for any necessary support for the electricity grid. We study financial benefits obtained by the large distributed energy storage for frequency regulation, energy arbitrage and peak shaving. Frequency regulation appears to be of the highest value for energy storage. Our results show that a distributed storage consisting of 1000 small batteries each of 1 kW power achieves average daily revenue of $606.61. INDEX TERMS Distributed energy storage, energy arbitrage, energy storage, frequency regulation, smart grid.

Economic Model for Coordinating Large-Scale Energy Storage Power Plant With Demand Response Management Options in Smart Grid Energy Management

“…0 ≤ 𝐸 ! ≤ 𝑋 ∀𝑡 ∈ 𝑇 (5) Equations ( 6) and (7) show the allowable number of the charging and discharging operations within their limits 𝜚 8+ and 𝜚 %/# .…”

“…To show the superiority of the proposed model and method, the results obtained from the operation of a battery unit are compared with other similar papers, shown in Table (7). Here are proposed method (MILP) is compared with other methods such as (GALP [31]), (LP [32]) and (NLP [33]).…”

“…In [6], different types of battery storage are introduced, and then the batteries used in California electricity transmission, distribution, and subscriber networks are presented. In [7] the authors have used energy storage to regulate the frequency of smart grids, energy arbitrage, peak reduction, reduction of power fluctuations of renewable energy sources (RES), which is not possible without energy storage. In [8] the authors presented an improved gray wolf optimization algorithm to solve the optimal scheduling problem for battery energy storage systems (BESS), taking into account the mass integration of renewable energy resources, such as solar and wind energies in active distribution networks.…”

A novel approach for sizing battery storage system for enhancing resilience ability of a microgrid

“…The energy capacity of BESS is influenced by its initial capital cost 4 . Recently, the adaptation of the BESS in power system has been increasing dramatically with a large amount of capacity installation, such as the BESS of Buzen Substation project in Japan, which is considered the largest BESS in the world with a capacity of 300 MWh, 5 the Rokkasho, Aomori station, 6 and Hornsdale in Australia 7 …”

“…4 Recently, the adaptation of the BESS in power system has been increasing dramatically with a large amount of capacity installation, such as the BESS of Buzen Substation project in Japan, which is considered the largest BESS in the world with a capacity of 300 MWh, 5 the Rokkasho, Aomori station, 6 and Hornsdale in Australia. 7 The operation cost minimization problem of MG is one of the optimization approaches in the energy management system (EMS) to obtain the optimal power dispatch from different DERs while satisfying all equality and inequality constraints, to minimize the operation cost and operate the MG in economic mode. Many research papers have been worked in the field of operation cost minimization and economic operation of MG, considering the impact of the optimal size of BESS and DERs on economic operation cost, such as L. Xu et al 8 focused on determining the size of different DERs including BESS for MG operation.…”