Optimal Operation of Multimicrogrids via Cooperative Energy and Reserve Scheduling

Li, Yuanzheng; Zhao, Tianyang; Wang, Ping; Gooi, Hoay Beng; Wu, Lei; Liu, Yun; Ye, Jian

doi:10.1109/tii.2018.2792441

Cited by 138 publications

(97 citation statements)

References 41 publications

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“…In [40], Wang et al has proposed a storage dispatch along with net capacity dispatched in a day-ahead electricity market using a two-stage optimization method. In [41], a co-operative operation of multiple micro-grids for energy and reserve capacity scheduling has been discussed. In [42], Cobos et al have proposed a mechanism within the context of co-optimized energy and reserve capacity with the penetration of bulk storage and uncertain wind energy.…”

Section: Related Workmentioning

confidence: 99%

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

et al. 2018

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This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability.

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Section: Related Workmentioning

confidence: 99%

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

et al. 2018

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“…In this way, the HSCA algorithm is able to produce solutions with higher quality in different cases as used to handle the peak operation of cascade hydropower reservoirs. Besides, it can be implied that the solution quality of the evolutionary algorithms can be improved by incorporating multiple beneficial strategies in the iterative search process [56,61,62], which can provide technical reference for similar engineering problems.…”

Section: Results Discussionmentioning

confidence: 99%

“…In the modeling process, the following equality and inequality constraints should be strictly satisfied to guarantee the safe operation of power system in the entire scheduling horizon [55][56][57][58].…”

Section: Operation Constraintsmentioning

confidence: 99%

Peak Operation Problem Solving for Hydropower Reservoirs by Elite-Guide Sine Cosine Algorithm with Gaussian Local Search and Random Mutation

et al. 2019

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In recent years, growing peak pressure is posing a huge challenge for the operators of electrical power systems. As the most important clean renewable energy, hydropower is often advised as a response to the peak loads in China. Thus, a novel hybrid sine cosine algorithm (HSCA) is proposed to deal with the complex peak operation problem of cascade hydropower reservoirs. In HSCA, the elite-guide evolution strategy is embedded into the standard sine cosine algorithm to improve the convergence rate of the swarm. The Gaussian local search strategy is used to increase the diversity of the population. The random mutation operator is adopted to enhance the search capability of the individuals in the evolutionary process. The proposed method is applied to solve the complex peak operation problem of two hydropower systems. The simulations indicate that in different cases, HSCA can generate the scheduling results with higher quality than several benchmark methods. Hence, this paper provides a feasible method for the complex peak operation problem of cascade hydropower reservoirs.

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“…Generally speaking, microgrid can be categorized into two types depending on whether connecting to the utility grid or not [23]. A microgrid disconnected to the utility grid operates as an islanded microgrid, while connected to the bulk power grid is called a grid-microgrid [24].…”

Section: B Microgrid Modelmentioning

confidence: 99%

Flexible Demand Resource Pricing Scheme: A Stochastic Benefit-Sharing Approach

Ding

Zhu

Wang

et al. 2019

2019 IEEE/IAS 55th Industrial and Commercial Power Systems Technical Conference (I&CPS)

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With the rapidly increased penetration of renewable generations, incentive-based demand side management (DSM) shows great value on alleviating the uncertainty and providing flexibility for microgrid. However, how to price those demand resources becomes one of the most significant challenges for promoting incentive-based DSM under microgrid environments. In this paper, a flexible demand resource pricing scheme is proposed. Instead of using the utility function of end users like most existing literatures, the economic benefit of flexible demand resources is evaluated by the operation performance enhancement of microgrid and correspondingly the resource is priced based on a benefit sharing approach. An iteration-based chance-constrained method is established to calculate the economic benefit and shared compensation for demand resource providers. Meanwhile, the financial risks for the microgrid operator due to uncertain factors are mitigated by the chanceconstrained criterion. The proposed scheme is examined by an experimental microgrid to illustrate its effectiveness.Index Terms-Demand side management, resource pricing, renewable energy integration, microgrid, risk management

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Optimal Operation of Multimicrogrids via Cooperative Energy and Reserve Scheduling

Cited by 138 publications

References 41 publications

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

Peak Operation Problem Solving for Hydropower Reservoirs by Elite-Guide Sine Cosine Algorithm with Gaussian Local Search and Random Mutation

Flexible Demand Resource Pricing Scheme: A Stochastic Benefit-Sharing Approach

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