Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

Krishnan, Ashok; Sampath, L. P. Mohasha Isuru; Foo, Eddy Y. S.; Gooi, Hoay Beng

doi:10.1155/2018/9842025

Cited by 5 publications

(8 citation statements)

References 35 publications

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“…The mechanical failure rate of the PMSG arisen from the rotation of the rotor, considering the impact of the variation in the temperature can be calculated as ( 5) and (6). Besides, the dependency of the unavailability of the rotating part of the PMSG on the wind speed is linear [27,28]. The impact of the variation in the wind speed on the failure rate of the BTB converter used in the PMSG-based wind units is studied in [23].…”

Section: The Reliability Of the Wind Turbinementioning

confidence: 99%

Optimal scheduling of the stand‐alone micro grids considering the reliability cost

Nargeszar,

Ghaedi,

Nafar

et al. 2024

The Journal of Engineering

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In order to prevent wastage of generated power of renewable resources, the energy storage systems can be utilized in the stand‐alone micro grids to store the excess produced power of the renewable generation units. When the generated power of the renewable resources is less than the required load, the energy storage systems can help to compensate all or part of the power shortage. In the current study, a stand‐alone micro grid including wind and tidal turbines, PV systems, batteries and fuel‐based generation units is considered to supply the required load of the micro grid. The generated power of each dispatch‐able generation units is determined in such a way as to minimize the operating cost. In the operating cost of the micro grid, the operating cost of the fuel‐based generation units and the reliability cost associated to the penalty of the curtailed loads are considered. To calculate the reliability cost of the micro grid, a comprehensive reliability evaluation of the micro grid considering the resource‐dependent failure rates for all composed components is performed. To study the effectiveness of the proposed reliability‐based scheduling approach, the numerical results associated to a stand‐alone micro grid containing wind, tidal, PV and fuel‐based generation units connected to the batteries are given.

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Section: The Reliability Of the Wind Turbinementioning

confidence: 99%

Optimal scheduling of the stand‐alone micro grids considering the reliability cost

Nargeszar,

Ghaedi,

Nafar

et al. 2024

The Journal of Engineering

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show abstract

“…On the other hand, an EMS (Energy Management System) model is developed by Krishnan in [ 21 ] for the industry microgrid (MG) to fulfill the industry’s appliances’ peak time that consumes power. Here, MG includes renewable energy sources (RES), diesel generators (DG), interruptible loads (IL), battery energy storage systems (BEES), and flexible loads (FL).…”

Section: Energy Management Of Campus Microgrids With Distributed Gene...mentioning

confidence: 99%

Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges

Muqeet

Javed

Akhter

et al. 2022

Sensors

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Distributed generation connected with AC, DC, or hybrid loads and energy storage systems is known as a microgrid. Campus microgrids are an important load type. A university campus microgrids, usually, contains distributed generation resources, energy storage, and electric vehicles. The main aim of the microgrid is to provide sustainable, economical energy, and a reliable system. The advanced energy management system (AEMS) provides a smooth energy flow to the microgrid. Over the last few years, many studies were carried out to review various aspects such as energy sustainability, demand response strategies, control systems, energy management systems with different types of optimization techniques that are used to optimize the microgrid system. In this paper, a comprehensive review of the energy management system of campus microgrids is presented. In this survey, the existing literature review of different objective functions, renewable energy resources and solution tools are also reviewed. Furthermore, the research directions and related issues to be considered in future microgrid scheduling studies are also presented.

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“…It can be utilized to minimize the effects of GHG emissions and to improve system efficiency and reliability. However, DG consists of photovoltaics (PVs) [14], wind turbines (WTs) [15], biomass [16], and fuel cells (FCs) [17] as renewable units, whereas other sources such as diesel generators (DiGs) [18], microturbines (MTs) [19], and tidal and geothermal gas engines (GEs) [20] are the sources of conventional units [21]. The microgrid component model is depicted briefly in Figure 3.…”

Section: Introductionmentioning

confidence: 99%

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Muqeet¹,

Munir

Javed

et al. 2021

Energies

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The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.

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Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

Cited by 5 publications

References 35 publications

Optimal scheduling of the stand‐alone micro grids considering the reliability cost

Optimal scheduling of the stand‐alone micro grids considering the reliability cost

Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

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