A stochastic frequency security constrained optimization model for day‐ahead energy and reserve scheduling of islanded multi‐microgrids systems

Sarcheshmeh, Mohammad Sadeghi; Taher, Seyed Abbas; Mazidi, Mohammadreza

doi:10.1002/2050-7038.12386

Cited by 10 publications

(4 citation statements)

References 39 publications

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“…In [22], a robust decentralized energy-management approach was proposed for the optimal day-ahead scheduling of a MMG system in the presence of hydrogen refueling stations and EV parking. A two-stage probabilistic optimization framework for day-ahead scheduling of MMG systems was proposed in [23] to minimize the total operational cost. Applying a variable weighted multi-objective function in [24], the authors presented a coordinated energy-management approach for optimal operation of MMG systems.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Optimal Strategy for Power Management in Interconnected Multi-Microgrid Systems

et al. 2022

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A novel stochastic strategy for solving the problem of optimal power management of multi-microgrid (MMG) systems is suggested in this paper. The considered objectives are minimizing the total cost and emission of the system. The suggested algorithm is applied on a MMG consisting of four microgrids (MG), each including fossil fuel-based generator units, wind turbine (WT), photovoltaic (PV) panel, battery, and local loads. The unscented transformation (UT) method is applied to deal with the inherent uncertainties of the renewable energy sources (RES) and forecasted values of the load demand and electricity price. The proposed algorithm is applied to solve the power management of a sample MMG system in both deterministic and probabilistic scenarios. It is justified through simulation results that the suggested algorithm is an efficient approach in satisfying the minimization of the cost and the environmental objective functions. When considering uncertainties, it is observed that the maximum achievable profit is about 23% less than that of the deterministic condition, while the minimum emission level increases 22%. It can be concluded that considering uncertainties has a significant effect on the economic index. Therefore, to present more accurate and realistic results it is essential to consider uncertainties in solving the optimal power management of MMG system.

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Section: Introductionmentioning

confidence: 99%

Stochastic Optimal Strategy for Power Management in Interconnected Multi-Microgrid Systems

et al. 2022

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“…In Ref. 26, a day ahead, two‐stage stochastic multi‐MG DER optimization model is proposed to minimize costs with reserve scheduling with frequency stability. An optimal MG scheduling for cost‐emission objectives was presented in Ref.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective fuzzy rank based scheduling of utility connected microgrid with high renewable energy using differential evolution with dynamic mutation

Shukla

Pandit

2021

Int Trans Electr Energ Syst

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Summary With the rapid depletion of coal reserves and rising concern to reduce the harmful fossil fuel emissions, the inclusion of renewable energy sources like wind and solar is gaining acceptance worldwide. In this paper, a multi‐objective optimization (MOO) model of a wind‐solar integrated microgrid is solved using a mixed integer fuzzy membership based differential evolution algorithm with dynamically varying mutation rates. The idea is to determine the best compromise solution for minimizing total cost, emission, and power losses, together. Wind uncertainty is modeled by an additional probabilistic cost term to include the cost of storage/reserve and penalty imposed for curtailment of renewable power. The proposed model reduces the impact of the control parameters and maximizes the attainment level of all three objectives. The results obtained using the proposed approach are compared and validated with the traditional weighted sum price penalty method and some recently published algorithms. The solutions attained by all these methods are found to be non‐dominating. However, the best compromise solution obtained for the MOO problem by the proposed method is found to have a higher fuzzy rank than the solutions obtained by the other methods. Moreover, there are no tuning parameters in the proposed approach.

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“…The robust controller design for a community microgrid is presented in Reference 18 using structured uncertainty. A time‐delayed stabilizing secondary load frequency control of shipboard microgrids is presented in Reference 19. In literature survey, the analysis related to high penetration level of RESs into MG is missing.…”

Section: Introductionmentioning

confidence: 99%

Forecast‐based modeling and robust frequency control of standalone microgrids considering high penetration of renewable sources

Kumar

Mukherjee

Mathur

et al. 2020

Int Trans Electr Energ Syst

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Summary This article proposes forecast‐based modeling and robust frequency control strategy in isolated microgrids (MGs) to improve its stability. The intermittency and variability in renewable generation is problem for its smooth integration to MGs considering frequency stability. Continuous rise in penetration levels of renewable energy sources (RESs) is the main motivation behind forecast‐based modeling and controller design for MGs. The disturbances that affect the frequency in the MG may come from the load side and/or the generation sides. In MGs, at the generation side, the forecast of power from RESs is usually obtained to get a rough estimate of available renewable power. The forecasted power always differs from the actual one, so the secondary frequency controller may get overburdened due to forecast error resulting in abnormal frequency deviation that may lead to unstable power system. The proposed H∞ based robust control design considers the forecast error which improves the system stability and performance against disturbances coming from load/generation side. First, a long short term memory based recurrent neural network has been used to forecast the renewable power availability. Thereafter a H∞ controller is designed, and it is shown through extensive simulation studies that the H∞ controller outperforms optimized PID controllers so far as rejecting the effects of uncertainties in RESs, forecasting errors, and model parameter variations are concerned. The proposed robust controller design is also validated with real time simulator (OP4510) made by Opal‐RT. The controller hardware in the loop (CHIL) test has been done taking the simulation time step of 50 μS.

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A stochastic frequency security constrained optimization model for day‐ahead energy and reserve scheduling of islanded multi‐microgrids systems

Cited by 10 publications

References 39 publications

Stochastic Optimal Strategy for Power Management in Interconnected Multi-Microgrid Systems

Stochastic Optimal Strategy for Power Management in Interconnected Multi-Microgrid Systems

Multi‐objective fuzzy rank based scheduling of utility connected microgrid with high renewable energy using differential evolution with dynamic mutation

Forecast‐based modeling and robust frequency control of standalone microgrids considering high penetration of renewable sources

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