Trends in Energy Management System for Smart Microgrid—An Overview

Vaikund, Harini; Srivani, S. G.

doi:10.1007/978-981-15-8391-9_2

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…Outcomes [108]This article provides an overview of the distributed energy supply activity and various systems applied in the energy management system, such as demand response, demand‐side management, and power quality management. This article suggested that several cutting‐edge optimization recommendations would successfully be applied to smart homes, industry, and EV to improve the load curve.[107]The proposed article suggested a systematic controlling methodology based on EMS is analyze on an MG system.[109]The suggested article analyzes the actual problem thoroughly on the optimal energy management approach on the MG. Several objectives, different ESS and power sources are analyzes to how to improve the overall system efficiency.[110]This article discusses several EMS approaches that have been implemented using various technical methods for MG demand‐side management.[111]A valuable result for a deeper understanding of existing research‐specific problems, prospects, possible obstacles, and unanswered questions about future centralized and decentralized EMS innovations are thoroughly described in this article.[112]A large‐scale literature study on HRES outlines a system with broad goals for optimization methods to enable the MG system's efficiency. A study of modeling and implementations of renewable energy production, storage sources, and integration of RESs through future upcoming EMS problems is discussed in detail.[113]This article's primary focus is to summarize the control goals and development of the new methodologies in the MGSC and EMS, which was recently proposed.…”

Section: Current Literature Study On Emsmentioning

confidence: 99%

“…The suggested article analyzes the actual problem thoroughly on the optimal energy management approach on the MG. Several objectives, different ESS and power sources are analyzes to how to improve the overall system efficiency. [110] This article discusses several EMS approaches that have been implemented using various technical methods for MG demand-side management.…”

Section: Current Literature Study On Emsmentioning

confidence: 99%

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A systematic review of energy management system based on various adaptive controllers with optimization algorithm on a smart microgrid

Behera

Choudhury

2021

Int Trans Electr Energ Syst

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Energy management system (EMS) is a modern methodology in smart households' advancement that build collaboration among end-users with their home appliances to operate automatically, multifunctionally, adaptably, and efficiently. EMS is categorized into several applications; battery energy management is an eminent application on smart grid applications. Such an approach is responsible for cost minimization during peak hour operated loads with various optimization methods and different adaptive controllers, which are described. Applications of EMS based different topologies are recommended with issues on these techniques have also been analyzed. Results obtained on EMS using optimization methods and battery EMS using fuzzy and PI controllers are demonstrated. Finally, based on the review, potential future scopes in this topic have been identified, and future research directions in this context are pointed out.

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Section: Current Literature Study On Emsmentioning

confidence: 99%

Section: Current Literature Study On Emsmentioning

confidence: 99%

A systematic review of energy management system based on various adaptive controllers with optimization algorithm on a smart microgrid

Behera

Choudhury

2021

Int Trans Electr Energ Syst

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“…Numerous studies have addressed several MG-related subjects, such as reactive power compensation procedures in MGs, control techniques for enhancing microgrid stability, and MG protection and control schemes. In addition, they studied droop control strategies, voltage, frequency regulation methods, and control strategies for inverter-based MGs (Boujoudar et al, 2020;Vaikund and Srivani, 2021).…”

Section: Introductionmentioning

confidence: 99%

Microgrid energy management and monitoring systems: A comprehensive review

J.Albarakati

Boujoudar

Azeroual³

et al. 2022

Front. Energy Res.

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Microgrid (MG) technologies offer users attractive characteristics such as enhanced power quality, stability, sustainability, and environmentally friendly energy through a control and Energy Management System (EMS). Microgrids are enabled by integrating such distributed energy sources into the utility grid. The microgrid concept is proposed to create a self-contained system composed of distributed energy resources capable of operating in an isolated mode during grid disruptions. With the Internet of Things (IoT) daily technological advancements and updates, intelligent microgrids, the critical components of the future smart grid, are integrating an increasing number of IoT architectures and technologies for applications aimed at developing, controlling, monitoring, and protecting microgrids. Microgrids are composed of various distributed generators (DG), which may include renewable and non-renewable energy sources. As a result, a proper control strategy and monitoring system must guarantee that MG power is transferred efficiently to sensitive loads and the primary grid. This paper evaluates MG control strategies in detail and classifies them according to their level of protection, energy conversion, integration, benefits, and drawbacks. This paper also shows the role of the IoT and monitoring systems for energy management and data analysis in the microgrid. Additionally, this analysis highlights numerous elements, obstacles, and issues regarding the long-term development of MG control technologies in next-generation intelligent grid applications. This paper can be used as a reference for all new microgrid energy management and monitoring research.

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“…Microgrid system integrates power generation, energy storage, load and control devices [2], aiming to convert distributed energy into electric energy locally, and then supply local load nearby [3]. M icrogrid itself is either independent of large power grid, or interactive with large power grid, or both, which has the characteristics of flexible distribution and complex control [4].…”

Section: Introductionmentioning

confidence: 99%

Short-term Ultraviolet Index Forecasting Using ARIMA Model

Xiao¹,

Liu²,

Liu³

2021

Proceedings of the 8th EAI International Conference on Green Energy and Networking, GreeNets 2021, June 6-7, 2021, Dalian, Peop

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Solar energy is recognized as an ideal renewable energy. Solar photovoltaic power generation is an important way to use solar energy. Photovoltaic power generation can alleviate the existing energy crisis and alleviate various environmental problems. As a clean and renewable energy, photovoltaic power generation is playing a prominent role in smart micro-grid. The intensity of solar radiation is fluctuating, so the successful grid connection of solar power stations requires accurate power prediction. This paper focuses on the prediction of ultraviolet power index to solve the problem of power prediction of photovoltaic power station. Based on the analysis of cumulative autoregressive moving average model, the stationary of ultraviolet index time series was detected, the order of ultraviolet index model was estimated, and the ARIM A model of ultraviolet index was determined. The prediction accuracy of the model is determined by the root mean square error (RM SE) and mean absolute error (M AE).

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Trends in Energy Management System for Smart Microgrid—An Overview

Cited by 6 publications

References 27 publications

A systematic review of energy management system based on various adaptive controllers with optimization algorithm on a smart microgrid

A systematic review of energy management system based on various adaptive controllers with optimization algorithm on a smart microgrid

Microgrid energy management and monitoring systems: A comprehensive review

Short-term Ultraviolet Index Forecasting Using ARIMA Model

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