Energy Management System of Microgrid using Optimization Approach

Sarda, Jigar; Lee, Kwang; Patel, Hirva; Patel, Nishita; Patel, Dhairya

doi:10.1016/j.ifacol.2022.07.049

Cited by 13 publications

(3 citation statements)

References 7 publications

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“…Heuristic and optimization strategies for clear and foggy days were both considered. The simulation outcomes revealed that the optimization approach decreased the COE by 6.6% on clear days and 13.7% on overcast days than heuristics 16 .…”

Section: Introductionmentioning

confidence: 96%

A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization

Jamal,

Pasupuleti,

Ekanayake

2024

Sci Rep

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A Nanogrid (NG) model is described as a power distribution system that integrates Hybrid Renewable Energy Sources (HRESs) and Energy Storage Systems (ESSs) into the primary grid. However, this process is affected by several factors, like load variability, market pricing, and the intermittent nature of Wind Turbines (WTs) and Photovoltaic (PV) systems. Hence, other researchers in the past have used a few optimization-based processes to improve the development of Energy Management Systems (EMSs) and ESSs, which further enhanced the operational performance of NGs. It was seen that EMS acts as the distributed energy source in the NG setup and assists in power generation, usage, dissemination, and differential pricing. Hence this study employed the MATLAB Simulink software for modelling the grid-connected NG that included HRES; such as wind and PV; in addition to 3 Battery Storage Devices (BSDs) to design an effective EMS for the NG system and decrease its overall costs. For this purpose, a Rule-Based EMS (RB-EMS) that employs State Flow (SF) to guarantee a safe and reliable operating power flow to the NG has been developed. In addition to that, a Genetic Algorithm (GA)-based optimization system and Simulated Annealing optimization Algorithm (SAA) were proposed to determine an economical solution for decreasing the cost of the NG system depending on its operational constraints. Lastly, comparison about the cost between RB-EMS, GA and SAA has been presented. According to the simulation results, the proposed GA displayed an economical performance since it could achieve a 40% cost saving whereas the SAA system showed a 19.3% cost saving compared to the RB-EMS. It can be concluded from the findings that the GA-based optimization technique was very cost-effective displays many important features, like rapid convergence, simple design, and very few controlling factors.

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Section: Introductionmentioning

confidence: 96%

A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization

Jamal,

Pasupuleti,

Ekanayake

2024

Sci Rep

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“…Energy storage systems are therefore of key importance in a microgrid because they allow an optimal use of the RES. In these microgrids, it is important to define an energy management system (EMS) that will have the role of controlling and guaranteeing the distribution and production of energy at lower costs (Sarda et al, 2022). This control system then has an essential function in increasing the reliability and efficiency of a microgrid.…”

Section: Introductionmentioning

confidence: 99%

Optimal Energy Management Strategy for Microgrids in Developing Countries: A Focus on Battery Energy Storage System

Molu,

Naoussi Dzonde,

Wira

et al. 2024

Chronicle of Computing

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Microgrid failure is a significant concern in developing countries and rural areas, necessitating effective energy management strategies to enhance post-failure reliability. The battery energy storage system plays a crucial role in microgrids by managing imbalances, mitigating voltages, and improving system reliability. This paper presents a method for optimizing the energy storage system in a photovoltaic-connected microgrid. The method controls battery discharge and charge operations based on load requirements, considering fluctuations in demand over a day. Simulations using MATLAB R2022a employed state flow analysis and linear programming to minimize variable electricity prices before and after islanding events. The results demonstrate significant improvements in energy management by reducing total variable electricity costs. The proposed method enhances the performance and resilience of microgrid systems, addressing challenges associated with intermittent renewable energy and potential system failures. Effective energy storage management enables risk mitigation, improved reliability, and enhanced utilization of renewable resources, ultimately contributing to sustainable and resilient energy systems.

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“…The work in 26 examined the efficiency during the under-voltage condition; and reported increased hydrogen production and considerable reductions in power fluctuations. Optimization approaches can increase the utilization of renewable energy sources, minimize the usage of fossil fuels, reduce energy expenditures, and improve the stability and reliability of the microgrid 27 .…”

Section: Introductionmentioning

confidence: 99%

Practical prototype for energy management system in smart microgrid considering uncertainties and energy theft

Saeed,

Sedhom,

Elbaghdadi

et al. 2023

Sci Rep

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The conventional electrical grid faces significant issues, which this paper aims to address one of most of them using a proposed prototype of a smart microgrid energy management system. In addition to relying too heavily on fossil fuels, electricity theft is another great issue. The proposed energy management system can simultaneously detect electricity theft and implement demand response tactics by employing time-of-use pricing principles and comparing real electricity consumption with grid data. The system uses the Al-Biruni earth radius (BER) optimization algorithm to make smart choices about how to distribute the load, intending to reduce energy consumption and costs without sacrificing comfort. As a bonus, it considers limitations imposed by battery charging/discharging and decentralized power generation. Incorporating sensors and SCADA-based monitoring, the system provides accurate measurement and management of energy usage through load monitoring and control. An intuitive mobile app also helps consumers connect, allowing for more active participation and better control over energy use. Extensive field testing of the prototype shows that by moving loads from peak period to another off-peak period, electricity expenditures can be reduced by up to 48.45%. The energy theft value was calculated to be 1199 W, proving that the system's theft detection model was effective.

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Energy Management System of Microgrid using Optimization Approach

Cited by 13 publications

References 7 publications

A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization

A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization

Optimal Energy Management Strategy for Microgrids in Developing Countries: A Focus on Battery Energy Storage System

Practical prototype for energy management system in smart microgrid considering uncertainties and energy theft

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