Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system

Sedighizadeh, Mostafa; Esmaili, Masoud; Jamshidi, Atefeh; Ghaderi, M.

doi:10.1016/j.ijepes.2018.09.037

Cited by 154 publications

(63 citation statements)

References 32 publications

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“…The multi-objective function aimed to minimize the total operating cost and emissions of the MG simultaneously using the ant lion optimizer. Sedighizadeh et al [27] presented a stochastic multi-objective-based model for optimal economic-environmental energy and reserve scheduling of a grid-connected MG, considering traditional energy resources, RESs, and BSS. The Weibull, beta, and normal probability distribution functions were utilized to model uncertainties of the wind speed, solar radiation, and demand, respectively.…”

Section: Grid−tmentioning

confidence: 99%

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

et al. 2020

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This paper presents the economic analysis and optimal energy management of a grid-connected MG that comprises renewable energy resources and different battery storage technologies with different characteristics such as initial charge, depth of discharge, and the number of charging/discharging cycles to minimize the total operating cost of the system by maximizing the benefits of BSS, minimizing the investment and replacement cost of BSS, and minimizing the operation and maintenance cost of DGs. Several constraints are considered, such as the output power limits of the distributed generators, the limits of power imported from or exported to the grid, load balance, and other sets of battery storage constraints. The general algebraic modeling system (GAMS) is used to solve the deterministic optimization problem. Second, stochastic optimization is used to solve the deterministic problem with market price uncertainty. Third, robust optimization using the information gap decision theory is presented to model the electric load uncertainty. The validity and effectiveness of the proposed solution are explained by comparing the results obtained by GAMS to the results obtained by other optimization techniques presented in the literature.

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Section: Grid−tmentioning

confidence: 99%

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

et al. 2020

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“…Distributed generations eliminate the need for the transmission system by being installed near the customers (Aboli et al, 2019). Integration and control of distributed generations s along with storage devices and flexible loads can constitute a low voltage distribution network, called a MG, which can be operated in isolated or gridconnected mode (Sedighizadeh et al, 2019). The generic concept of a MG is shown in Figure 1.…”

Section: Microgrid Conceptmentioning

confidence: 99%

Deep Reinforcement Learning for Energy Microgrids Management Considering Flexible Energy Sources

2019

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The problem of optimally activating the flexible energy sources (short-and long-term storage capacities) of electricity microgrid is formulated as a sequential decision making problem under uncertainty where, at every time-step, the uncertainty comes from the lack of knowledge about future electricity consumption and weather dependent PV production. This paper proposes to address this problem using deep reinforcement learning. To this purpose, a specific deep learning architecture has been used in order to extract knowledge from past consumption and production time series as well as any available forecasts. The approach is empirically illustrated in the case of off-grid microgrids located in Belgium and Russia.

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“…(17) in different operational years, and is modified at the different operating horizons as shown in Eq. (18). In these relationships, CG i DG is generation pro-…”

Section: Operating Costmentioning

confidence: 99%

“…In this paper, the stochastic operation scheduling of a MG consisting of non-dispatchable resources including WT and PV and dispatchable resources including Phosphoric Acid Fuel Cell (PAFC), Micro-gas Turbine (MT), and electrical storage as Battery Energy Storage System (BESS) is investigated to minimize operation cost and emissions [18]. Although the design of multiple microgrids is reported in the mentioned studies, the design of microgrids considering all economic, technical, environmental and reliability aspects regarding the uncertainty in system design parameters is not reported in previous references.…”

Section: Introductionmentioning

confidence: 99%

Scenario-Based Design for Multiple Microgrids with High DG Penetration Considering Uncertainty on Demand and Generation Side

Sedaghati

Soory

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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In this paper a new scenario-based approach is proposed to design optimized multiple-microgrids considering the uncertainty of load consumption and renewable DGs generation. The proposed method is used to determine the optimal capacity, type, number and location of renewable and controllable distributed generation resources along with the switch optimal location to cluster the traditional distribution network into a set of interconnected microgrids with economic and reliable structured. This study aims to decrease the total design costs including investment and operation costs, system loss cost, air pollution cost as well as the microgrids energy not supplied cost. Different considered objective functions have been modeled using weighted coefficients method as a singleobjective nonlinear mixed integer problem. In addition, the uncertainty of the problem input parameters is modeled using scenario generation method, and in order to decrease the computational burden and increase the program execution speed, the backward scenario reduction technique is used. The Cuckoo optimization algorithm is used to optimize the objective function, and also the effect of optimization coefficients on the design problem and the robustness of the proposed algorithm are investigated using sensitivity analysis. Finally, the efficiency and performance of the proposed method are evaluated on the standard 33-bus network and the results show that the proposed method is an effective tool to design interconnected microgrids with consideration of uncertainty.

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Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system

Cited by 154 publications

References 32 publications

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

Deep Reinforcement Learning for Energy Microgrids Management Considering Flexible Energy Sources

Scenario-Based Design for Multiple Microgrids with High DG Penetration Considering Uncertainty on Demand and Generation Side

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