Joint optimization of day-ahead and uncertain near real-time operation of microgrids

Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids' EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.

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“…2 Extreme case by multiplying load demands by 2. 3 Extreme case by multiplying PV and WT generation by 4 and 5. 4…”

Section: 6mentioning

confidence: 99%

“…[2]. DGs eliminate the need for the transmission system by being installed near the customers [3]. Integration and control of DGs along with storage devices and flexible loads can constitute a low voltage distribution network, called a microgrid, which can be operated in isolated or grid-connected mode [4].…”

Section: Introductionmentioning

confidence: 99%

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

et al. 2019

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“…In this regard, few RT scheduling methods have been proposed for tracking unpredictable changes of generation in microgrids. In Aboli and Ramezani, a joint optimization of day‐ahead and uncertain near RT operations of microgrid was proposed. The study in Zhang et al presents a model for the two‐layer RT dispatch of microgrid considering hidden costs of discharging opportunity and marginal charging of energy storage system.…”

Section: Real‐time Control and Energy Managementmentioning

confidence: 99%

“…Microgrid energy management optimization with considering both renewable uncertainty and RT market price 71 Virtual queues from Lyapunov optimization A new auction model is presented for market RT operation 73 Fast learning optimiser (FlO) A two-layer optimization using model-free Q-learning is employed for knowledge learning and decision making is proposed for gridconnected microgrid, 57 Chance-constrained stochastic optimization New RT microgrid planning and control considering uncertainties of the PV power predictions 74 Fuzzy logic controller Decentralized reactive power control and stability improvement 47 Making a game with Nash equilibrium A new distributed RT electricity allocation (DRTA) scheme is presented 49 Heuristic optimization methods…”

Section: Robust Optimizationmentioning

confidence: 99%

A review on real‐time simulation and analysis methods of microgrids

Ahmadiahangar

Rosin

Niaki

et al. 2019

Int Trans Electr Energ Syst

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Summary Microgrid is a recently developed concept for future power systems. The main characteristics of the microgrid are the capability of integration of renewable energy sources and the ability to operate in two grid‐connected and islanded modes. A significant challenge of microgrid implementation is developing comprehensive control methods to ensure efficient, stable, and reliable operation. Real‐time studies are a promising approach in this case. In this paper, various real‐time energy management approaches have been thoroughly explained following a new categorization of them. A significant literature review of real‐time simulation and modeling methods has also been presented. A review of different applications of hardware‐in‐the‐loop testing of the microgrid is included in the present study. Finally, a discussion on demand for further research has been made. The presented work is organized to allow a reader to understand the importance of real‐time studies of microgrids and highlight trends in literary works without delving deeply into each one.

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“…In these studies, VPP aggregates different kinds of DER to operate as a single power plant. In Aboli et al, a day‐ahead (DA) robust optimization model is proposed to schedule DERs for the next day. Moreover, wind power generation, conventional DG units, and energy storage systems (ESSs) are considered for a microgrid which participates in DA and real‐time (RT) markets.…”

Section: Introductionmentioning

confidence: 99%

A two‐stage stochastic programming framework for risk‐based day‐ahead operation of a virtual power plant

Emarati

Keynia

Rashidinejad

2020

Int Trans Electr Energ Syst

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Summary With the increasing use of distributed energy resources (DERs), new technical and economic issues have been raised in power systems. Integration of DERs and energy storage systems (ESSs) in the form of virtual power plant (VPP) resolves an important part of these issues. This paper proposes a risk‐based two‐stage stochastic optimization framework to address the energy management problem for a VPP. The objective of the proposed framework is to optimize the operation of a VPP in day‐ahead (DA) and real‐time (RT) markets. In order to include the risk parameter in the proposed decision‐making problem, conditional value at risk (CVaR) index is applied in the objective function. The considered uncertain parameters in the model are price in DA market, as well as wind and solar generation for the next day. Markov chain Monte Carlo (MCMC) method is applied to model these uncertain parameters through generation of different scenarios. Also, the effects of using ESS on daily operation of considered VPP is investigated. The performance of the proposed method is illustrated through a case study using real data. The obtained results guarantee the appropriate operation of a VPP considering different values for level of the risk.

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Joint optimization of day-ahead and uncertain near real-time operation of microgrids

Cited by 46 publications

References 42 publications

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

A review on real‐time simulation and analysis methods of microgrids

A two‐stage stochastic programming framework for risk‐based day‐ahead operation of a virtual power plant

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