Smart integration of renewable energy resources, electrical, and thermal energy storage in microgrid applications

Tooryan, Fahimeh; HassanzadehFard, Hamid; Collins, E.R.; Jin, Shuangshuang; Ramezani, Bahram

doi:10.1016/j.energy.2020.118716

Cited by 76 publications

(24 citation statements)

References 23 publications

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“…Similarly, the utility shall virtually pay FC for each unit of energy being discharged from the BESS. e FC, E F BESS , is kept fixed at the mean price with the consideration of (1) and (2). e action of introducing FCs avoids unwanted BESS scheduling, as explained as follows.…”

Section: Fictitious Charges (Fcs)mentioning

confidence: 99%

“…ese DG units may exist in a combination of nondispatchable sources, i.e., solar photovoltaics (PVs) and wind turbines (WTs), and dispatchable sources such as MT units and BEESs. e coordinate scheduling of deployed BESSs and MT units in the uncertain renewable energy source (RES) batteries and motor system can shift the peak load, improve the absorption level of intermittent renewable energy, enhance the reliability of power system, delay the investment of power equipment, and so on [1,2]. However, the escalating presence of BESSs requires scheduling and optimizing their coordination and management [3,4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Coordinated Energy Management in Active Distribution System with Battery Energy Storage and Price-Responsive Demand

Xing

Zhao

Shen

et al. 2021

Mathematical Problems in Engineering

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Contemporary distribution networks can be seen with diverse dispatchable and nondispatchable energy resources. The coordinated scheduling of these dispatchable resources, together with nondispatchable resources, can provide several technoeconomic and social benefits. Since battery energy storage systems (BESSs) and microturbine units (MT units) are capital-intensive, a thorough investigation of their coordinated scheduling under the economic criterion will be a challenging task while considering dynamic electricity prices and uncertainties of renewable power generation and load demand. This paper proposes a comprehensive methodological framework for optimal coordinated scheduling of BESSs with MT unit considering existing renewable energy resources and dynamic electricity prices to maximize the daily profit function of the utility by employing a recently explored modified African buffalo optimization algorithm. The key attributes of the proposed methodology are comprised of mean price-based adaptive scheduling embedded within a decision mechanism system (DMS) to maximize arbitrage benefits. DMS keeps track of system states as a priori, thus resulting in an artificial intelligence-based solution technique for sequential optimization. Further, a novel concept of fictitious charges is also proposed to restrict the counterproductive operational management of BESSs. The proposed model and method are demonstrated on the 33-bus distribution system, and the obtained results verify the effectiveness of the proposed methodology.

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Section: Fictitious Charges (Fcs)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Coordinated Energy Management in Active Distribution System with Battery Energy Storage and Price-Responsive Demand

Xing

Zhao

Shen

et al. 2021

Mathematical Problems in Engineering

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“…Data‐based modeling is used for each component of the microgrid 4 . The current electrical, cooling, and heat load demand, renewable source generated power, and grid energy price are taken online from the meters in the microgrid.…”

Section: System Modelingmentioning

confidence: 99%

Analysis of a linear programming‐based decision‐making model for microgrid energy management systems with renewable sources

Gassi

Baysal

2022

Intl J of Energy Research

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Summary With the increasing share of renewable energy sources in microgrids, systems enhancing the power flexibility at the demand side have become mandatory in microgrid architecture. Thus, the electrical energy storage system has been mostly integrated into microgrids although its capital and operating costs are very high. Hence, diversifying microgrid energy storage based on the end‐energy usage can improve the reliability, operating cost, and power demand flexibility of the microgrid. The hereby study integrates an absorption chiller and electrical heat pump coupled to a heat storage into a renewable energy resources‐based microgrid and develops its centralized energy management model for both off‐grid and on‐grid operation modes. The model considers the current energy level of energy storages in the microgrid, current, and forecasted information state to compute the vector‐valued decision minimizing a realistic microgrid operating cost. The operating cost includes the energy purchasing/generation, heating/electrical storage, and penalty cost due to load shedding. Hence, such an objective function leads to maximizing the consumption of the generated renewable power, minimizing the energy storage and load shedding cost. The load shedding has been allowed to increase the flexibility in microgrid energy management. However, a high penalty has been imposed on each electrical, heating, or cooling load shedding decision. The decision vector components are thermal and electrical power flow between each energy source to loads and energy storage systems. The problem has been modeled as a Linear Programming with forecasted multi‐parametric inputs at different prediction horizons. The effect of the charging/discharging rate and capacity of energy storages, coefficient of performance of absorption chiller and heat pump, prediction horizon, and energy level of storage devices provided to the myopic energy management model has been evaluated for better integration of renewable sources and thermal storage systems into microgrids. Suggestions have been made to improve the microgrid self‐consumption, energy efficiency, and myopic decision‐making model using the energy level of storage devices obtained from the full look‐ahead optimization model. Highlights The optimization problem combining electricity, heating, and cooling is formulated The electrical and thermal storage charging/discharging rate significantly affect the power supplied by the renewable power source decision of the microgrid energy management model. Accurate energy storage level information into the myopic energy management model improves the model decisions. The absorption chiller coefficient of performance greatly impacts the cooling and electrical loads shedding.

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“…Generally, a hybrid of energy storage devices for MGs have been proposed to balance the fluctuations inherent in RERs. A combination of battery units, supercapacitors, electric vehicles requiring effective and optimized control coordination using multiple techniques have been proposed [50]- [53]. The algorithms and techniques proposed in the works provide an opportunity for flexible and resilient implementation through the SDMG control approach.…”

Section: ) Energy Storage Managementmentioning

confidence: 99%

Software-Defined Power Grids: A Survey on Opportunities and Taxonomy for Microgrids

et al. 2021

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Future generation power grids will require the introduction and deployment of distributed energy resources to meet modern day load requirements. Consequently, we expect to see a rise in microgrids (MGs) existing as part of the main grid (grid-connected) or independent (islanded). Contained in these microgrids are a combination of energy resources such as solar, wind and fossil-fuels coupled with storage devices, electric vehicles and smart devices supporting prosumer operation. However, the addition of renewable energy resources would mean fluctuations in energy supply which would cause power system instability if not managed effectively. Hence, to maximize the management flexibility of MGs, the concept of microgrid software-definition is introduced. A concept that can be looked at as giving the microgrid an operating system to improve operation response and event detection by maintaining a global view of the network. This paper therefore critically analyses what this entails by presenting an architecture for Software-Defined Microgrids and discussing the management opportunities that softwarization of the MG introduces. We also highlight the design requirements and associated challenges in implementing and deploying SDMGs.INDEX TERMS Energy balancing, grid resiliency, microgrids, power grid management, software-defined networking, smart grids.

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Smart integration of renewable energy resources, electrical, and thermal energy storage in microgrid applications

Cited by 76 publications

References 23 publications

Optimal Coordinated Energy Management in Active Distribution System with Battery Energy Storage and Price-Responsive Demand

Optimal Coordinated Energy Management in Active Distribution System with Battery Energy Storage and Price-Responsive Demand

Analysis of a linear programming‐based decision‐making model for microgrid energy management systems with renewable sources

Software-Defined Power Grids: A Survey on Opportunities and Taxonomy for Microgrids

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