Co-optimization of energy and reserve in standalone micro-grid considering uncertainties

Bahramara, Salah; Sheikhahmadi, Pouria; Golpîra, Hêmin

doi:10.1016/j.energy.2019.04.057

Cited by 45 publications

(17 citation statements)

References 35 publications

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“…On load side, the reserve mainly derives from the incentive-based demand response [31], [32]. Load shedding can be executed to provide upward reserve support for IMG when it reveals the insufficient power supply.…”

Section: Multi-type Reserve Scheme For Imgsmentioning

confidence: 99%

“…VaRt directly according to its definition [25], [32]. An alternative approach is reported in [32], [35] by introducing auxiliary variable ξ and setting up a minimization problem for ξ to solve (5), which is expressed as:…”

Section: Vart and C -mentioning

confidence: 99%

“…A model of joint energy and reserve scheduling by considering risk management for IMG is presented in [31], and uncertainties of RES, demand loads, and electricity prices are modeled by adopting CVaR. In [32], the risk of IMG operator in decision-making is controlled by CVaR, and then an operation formulation is proposed to simultaneously schedule energy and reserve with the aim of compensating for uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…According to the above literature survey, through the optimal scheduling of joint energy and reserve, the problem of reserve scheduling for MGs is solved to some extent. In respect of reserve schemes, the existing studies mainly focus on single spinning reserve schemes provided by dispatchable generators only [10], [19] and generation-load joint reserve schemes provided by dispatchable generators and interruptible load (IL) [31], [32]. However, the uncertainties of RESs and the fluctuation of load will lead to a significant increase in the reserve requirement of IMGs with high penetration of RESs.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Day-ahead Scheduling of Islanded Microgrid Considering Risk-based Reserve Decision

Liu

et al. 2021

Journal of Modern Power Systems and Clean Energy

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Due to the lack of support from the main grid, the intermittency of renewable energy sources (RESs) and the fluctuation of load will derive uncertainties to the operation of islanded microgrids (IMGs). It is crucial to allocate appropriate reserve capacity for the economic and reliable operation of IMGs. With the high penetration of RESs, it faces both economic and environmental challenges if we only use spinning reserve for reserve support. To solve these problems, a multi-type reserve scheme for IMGs is proposed according to different operation characteristics of generation, load, and storage. The operation risk due to reserve shortage is modeled by the conditional value-at-risk (CVaR) method. The correlation of input variables is considered for the forecasting error modeling of RES and load, and Latin hypercube sampling (LHS) is adopted to generate the random scenarios of the forecasting error, so as to avoid the dimension disaster caused by conventional large-scale scenario sampling approaches. Furthermore, an optimal day-ahead scheduling model of joint energy and reserve considering riskbased reserve decision is established to coordinate the security and economy of the operation of IMGs. Finally, the comparison of numerical results of different schemes demonstrate the rationality and effectiveness of the proposed scheme and model. Index Terms--Day-ahead scheduling, risk-based reserve decision, conditional value-at-risk (CVaR), renewable energy source (RES), islanded microgrids.

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Section: Multi-type Reserve Scheme For Imgsmentioning

confidence: 99%

Section: Vart and C -mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Day-ahead Scheduling of Islanded Microgrid Considering Risk-based Reserve Decision

Liu

et al. 2021

Journal of Modern Power Systems and Clean Energy

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“…Optimal sizing and scheduling of remote microgrid assets operating in isolation have been addressed in several recent studies. For example, [3] proposes a risk-based stochastic approach to optimally scheduling microgrid assets. In [4], a Monte Carlo simulation-based stochastic programming approach is used to define an optimal design for a remote microgrid based on reliability and cost criteria.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of the Economic and Resilience Benefits of a Microgrid in Northampton, Massachusetts

Balducci

Mongird

et al. 2020

Energies

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Recent developments and advances in distributed energy resource (DER) technologies make them valuable assets in microgrids. This paper presents an innovative evaluation framework for microgrid assets to capture economic benefits from various grid and behind-the-meter services in grid-connecting mode and resilience benefits in islanding mode. In particular, a linear programming formulation is used to model different services and DER operational constraints to determine the optimal DER dispatch to maximize economic benefits. For the resiliency analysis, a stochastic evaluation procedure is proposed to explicitly quantify the microgrid survivability against a random outage, considering uncertainties associated with photovoltaic (PV) generation, system load, and distributed generator failures. Optimal coordination strategies are developed to minimize unserved energy and improve system survivability, considering different levels of system connectedness. The proposed framework has been applied to evaluate a proposed microgrid in Northampton, Massachusetts that would link the Northampton Department of Public Works, Cooley Dickenson Hospital, and Smith Vocational Area High School. The findings of this analysis indicate that over a 20-year economic life, a 441 kW/441 kWh battery energy storage system, and 386 kW PV solar array can generate $2.5 million in present value benefits, yielding a 1.16 return on investment ratio. Results of this study also show that forming a microgrid generally improves system survivability, but the resilience performance of individual facilities varies depending on power-sharing strategies.

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Hybrid risk‐averse energy management optimizer for large‐scale industrial building microgrids

Ali

Malik

Raza³

2020

Int Trans Electr Energ Syst

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Summary Energy system has been facing problems such as soaring energy cost and environmental concerns. Among different types of customers, large‐sized industrial building microgrids (μGs) with heavy load, that can contribute significantly to demand response and greenhouse gas (GHG) emissions reduction. Therefore, an optimal risk‐averse energy management strategy is required for this class of customers. The objective of this article is to devise an energy management system (EMS) for large‐scale industrial μG to reduce energy consumption cost and GHG emissions. Framework has been solved in MATLAB using conventional flower pollination algorithm (FPA). However, metaheuristic techniques such as FPA take large execution time and trap in local optimum. On the other hand, deterministic techniques cannot handle large problems, however, reach an optimum solution in a shorter time span. To address these issues of both classes of algorithms, article devises and validates hybrid modified FPA‐mixed‐integer linear programming solution algorithm. Simulations show that the proposed technique produces improved results with low execution time, providing a justification for the practical implementation of the concept in the smart energy distribution system.

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Co-optimization of energy and reserve in standalone micro-grid considering uncertainties

Cited by 45 publications

References 35 publications

Optimal Day-ahead Scheduling of Islanded Microgrid Considering Risk-based Reserve Decision

Optimal Day-ahead Scheduling of Islanded Microgrid Considering Risk-based Reserve Decision

An Evaluation of the Economic and Resilience Benefits of a Microgrid in Northampton, Massachusetts

Hybrid risk‐averse energy management optimizer for large‐scale industrial building microgrids

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