Homogenising the Design Criteria of a Community Battery Energy Storage for Better Grid Integration

Recent attention to industrial peak shaving applications sparked an increased interest in battery energy storage. Batteries provide a fast and high power capability, making them an ideal solution for this task. This work proposes a general framework for sizing of battery energy storage system (BESS) in peak shaving applications. A cost-optimal sizing of the battery and power electronics is derived using linear programming based on local demand and billing scheme. A case study conducted with real-world industrial profiles shows the applicability of the approach as well as the return on investment dependence on the load profile. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, peak-power tariff, and battery aging. This underlines the need for a general mathematical optimization approach to efficiently tackle the challenge of peak shaving using an energy storage system. The case study also compares the applicability of yearly and monthly billing schemes, where the highest load of the year/month is the base for the price per kW. The results demonstrate that batteries in peak shaving applications can shorten the payback period when used for large industrial loads. They also show the impacts of peak shaving variation on the return of investment and battery aging of the system.

<p><span>This paper proposes a methodology for designing and operating a microgrid (MG) for the main campus of the Technical Institution Hawija. In this MG, a battery energy storage system (BESS), photovoltaic (PV) generation system, and controllable loads are included. Due to the high penetration of the PVs, over-voltage issues may occur in this MG. A novel operation strategy is considered by coordinating the BESS, PVs, and loads to prevent power outages and accomplish a secure operation of this MG. In this proposed approach, droop controllers have been implemented to provide the appropriate references for the PVs and BESS to maintain the voltage of the MG within a secure range. The generation of the PVs may be curtailed to guarantee the fidelity of the voltage. The intended simulations will be based on MATLAB/Simulink to show the efficacy of the intended design.</span></p><script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML&amp;delayStartupUntil=configured"></script><script id="texAllTheThingsPageScript" type="text/javascript" src="chrome-extension://cbimabofgmfdkicghcadidpemeenbffn/js/pageScript.js"></script>

Due to the increased development of the smart grid, it is becoming crucial to have an efficient energy management system for a time-of-use (TOU) rate industrial user in Taiwan. In this paper, an extension of the direct search method (DSM) is developed to deal with the operating schedule of a TOU rate industrial user under the demand bidding mechanism of Taipower. To maximize the total incentive obtained from the Taiwan Power Company (TPC, namely Taipower), several operational strategies using a battery energy storage system (BESS) are evaluated in the study to perform peak shaving and realize energy conservation. The effectiveness of the proposed DSM algorithm is validated with the TOU rate industrial user of the TPC. Numerical experiments are carried out to provide a favorable indication of whether to invest in a BESS for the renewable energy-based TOU rate industrial user in order to execute the demand bidding program (DBP).