Techno-Economic Control of Energy Storage System for Demand Side Management

Author(s):  
Francesco Grasso ◽  
Mostafa Abdollahi ◽  
Giacomo Talluri ◽  
Libero Paolucci
Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6292
Author(s):  
Kyo Beom Han ◽  
Jaesung Jung ◽  
Byung O Kang

In today’s power systems, the widespread adoption of smart grid applications requires sophisticated control of load variability for effective demand-side management (DSM). Conventional Energy Storage System (ESS)-based DSM methods in South Korea are limited to real-time variability control owing to difficulties with model development using customers’ load profiles from sampling with higher temporal resolution. Herein, this study thus proposes a method of controlling the variability of customers’ load profiles for real-time DSM using customer-installed ESSs. To optimize the reserved capacity for the proposed maximum demand control within ESSs, this study also proposes a hybrid method of load generation, which synthesizes approaches based on Markov Transition Matrix (MTM) and Artificial Neuron Network (ANN) to estimate load variations every 15 min and, in turn reserve capacity in ESSs. The proposed ESS-based DSM strategy primarily reserves capacity in ESSs based on estimated variation in load, and performs real-time maximum demand control with the reserved capacity during scheduled peak shaving operations. To validate the proposed methods, this study used load profiles accumulated from industrial and general (i.e., commercial) customers under the time-of-use (TOU) rate. Simulation verified the improved performance of the proposed ESS-based DSM method for all customers, and results of Kolmogorov-Smirnov (K–S) testing indicate advances in the proposed hybrid estimation beyond the stand-alone estimation using the MTM- or ANN-based approach.


2019 ◽  
Vol 11 (1) ◽  
pp. 186 ◽  
Author(s):  
Byuk-Keun Jo ◽  
Seungmin Jung ◽  
Gilsoo Jang

Energy storage systems are crucial in dealing with challenges from the high-level penetration of renewable energy, which has inherently intermittent characteristics. For this reason, various incentive schemes improving the economic profitability of energy storage systems are underway in many countries with an aim to expand the participation rate. The electricity charge discount program, which was introduced in 2015 in Korea, is one of the policies meant to support the economic feasibility of demand-side energy storage systems. This paper quantitatively evaluated the impact of the electricity charge discount program on the economic feasibility of behind-the-meter energy storage systems. In this work, we first summarized how electricity customers can benefit from behind-the-meter energy storage systems. In addition, we represented details of the structure that make up the electricity charge discount program, i.e., how the electricity charge is discounted through the discount scheme. An optimization problem that establishes a charge and discharge schedule of an energy storage system to minimize each consumer’s electricity expenditure was defined and formulated as well. The case study results indicated that the electricity charge discount program has improved the profitability of behind-the-meter energy storage systems, and this improved profitability led to investment in behind-the-meter energy storage systems in Korea. As a result of the electricity charge discount program, Korea’s domestic demand side energy storage system market size, which was only 27 billion dollars in 2015 in Korea, has grown to 825 billion dollars in 2018.


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