scholarly journals Design and simulation of a microgrid for TIH campus

2020 ◽  
Vol 19 (2) ◽  
pp. 729
Author(s):  
Zaid H. Ali ◽  
Ziyaad H. Saleh ◽  
Raid W. Daoud ◽  
Ahmed H. Ahmed
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Generation System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
High Penetration ◽  
Technical Institution ◽  
Battery Energy ◽  
Pv Generation

<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>

scholarly journals Capacity Configuration of Battery Energy Storage System for Photovoltaic Generation System Considering the High Chargerate

2020 ◽  
Vol 182 ◽  
pp. 03003
Author(s):  
Jiaming Li ◽  
Ying Qiao ◽  
Guojing Liu ◽  
Zongxiang Lu
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Storage System ◽  
Energy Storage System ◽  
Configuration Model ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Charge Rate ◽  
Battery Energy ◽  
Pv Generation

Battery energy storage system (BESS) is one of the important solutions to improve the accommodation of large-scale grid connected photovoltaic (PV) generation and increase its operation economy. However, the strong intra-day volatility and severe curtailment of PV power sets a high demand of BESS charge-rate that is a key factor in operation models but ignored in current planning researches. This paper proposes a BESS capacity configuration model for PV generation systems which takes BESS’s ability to (dis)charge exceeds its rated power into account. The best charge-rate and power & energy capacity of BESS are optimized by particle swarm optimization (PSO) algorithm. Through an analysis of the annual output statistics of PV power station in the northwest of China, the results show that when considering the high charge-rate of BESS, the optimal BESS capacity configuration rises and comprehensive income of the PV-BESS system will increase.

scholarly journals Simulation on power-flow dispatching cases for Microgrid with PVS and battery energy storage system

2020 ◽  
Vol 2 (3) ◽  
pp. 163-178
Author(s):  
Phuc Duy Le ◽  
Duong Bui Minh ◽  
Hoai Banh Duc ◽  
Hoan Nguyen Thanh ◽  
Minh Doan Ngoc ◽  
...  
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Power Flow ◽  
Storage System ◽  
Energy Storage System ◽  
Generation System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Distributed Generators ◽  
Battery Energy

Modern Microgrid (MG) mainly consists of distributed generators (DGs), energy storage systems (ESSs), different loads, and protection systems. Microgrid plays an important role not only to ensure the power supply reliability but also to improve the power quality in distribution network. Moreover, deployment of distributed generators such as Photovoltaic Generation System (PVS), wind turbine generation system, and energy storage systems diversifies operation and control modes of AC microgrid in order to meet local demand response. This paper studies on power-flow dispatching cases for a MG with PVS and Battery Energy Storage System (BESS), which considers the maximum power consumption generated by the PVS and minimizes the power received from the utility grid. Simulation results validate the effectiveness of BESS for actively dispatching power-flow of MG in case the PVSs cannot partially or fully meet the local demand response in peak hours. By using ETAP software, real data of the PVSs are used to do simulation and power-flow calculation for the MG, which is to evaluate the feasibility of power-flow dispatch solutions proposed in this paper.

scholarly journals Optimal Battery Energy Storage System Scheduling within Renewable Energy Communities

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8480
Author(s):  
Giacomo Talluri ◽  
Gabriele Maria Lozito ◽  
Francesco Grasso ◽  
Carlos Iturrino Garcia ◽  
Antonio Luchetta
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Mixed Integer ◽  
Baseline Scenario ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy ◽  
Pv Generation

In this work, a strategy for scheduling a battery energy storage system (BESS) in a renewable energy community (REC) is proposed. RECs have been defined at EU level by the 2018/2001 Directive; some Member States transposition into national legislation defined RECs as virtual microgrids since they still use the existing low voltage local feeder and share the same low-medium voltage transformer. This work analyzes a REC which assets include PV generators, BESS and non-controllable loads, operating under the Italian legislative framework. A methodology is defined to optimize REC economic revenues and minimize the operation costs during the year. The proposed BESS control strategy is composed by three different modules: (i) a machine learning-based forecast algorithm that provides a 1-day-ahead projection for microgrid loads and PV generation, using historical dataset and weather forecasts; (ii) a mixed integer linear programming (MILP) algorithm that optimizes the BESS scheduling for minimal REC operating costs, taking into account electricity price, variable feed-in tariffs for PV generators, BESS costs and maximization of the self-consumption; (iii) a decision tree algorithm that works at the intra-hour level, with 1 min timestep and with real load and PV generation measurements adjusting the BESS scheduling in real time. Validation of the proposed strategy is performed on data acquired from a real small-scale REC set up with an Italian energy provider. A 10% average revenue increase could be obtained for the prosumer alone when compared to the non-optimized BESS usage scenario; such revenue increase is obtained by reducing the BESS usage by around 30% when compared to the unmanaged baseline scenario.

Study of Efficiency of Battery Energy Storage System

2016 ◽  
Vol 136 (11) ◽  
pp. 824-832 ◽  
Author(s):  
Mami Mizutani ◽  
Takenori Kobayashi ◽  
Katsunori Watabe ◽  
Tomoki Wada
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy
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