Optimal operation of smart distribution networks in the presence of demand response aggregators and microgrid owners: A multi follower Bi-Level approach

Haghifam, Sara; Dadashi, Mojtaba; Zare, Kazem; Seyedi, Heresh

doi:10.1016/j.scs.2020.102033

Cited by 55 publications

(22 citation statements)

References 44 publications

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“…This approach combines a real/integer-coded JAYA algorithm to deal with the UL problem and a branch and bound algorithm to address the LL problem, which alternate iterations between the two levels to provide the solution to the BLO problem. Haghifam et al (2020) presented a multi-follower BLO framework for the operational scheduling of smart distribution networks. The leader is the DSO aiming to minimize operating costs, subject to active and reactive power balance, voltage limits, and line power constraints.…”

Section: Demand Response In Microgrid Planning and Operationmentioning

confidence: 99%

Bilevel optimization to deal with demand response in power grids: models, methods and challenges

Antunes

Alves

Ecer

2020

TOP

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This paper presents a review of selected models, methods, and challenges associated with the use of bilevel optimization in problems that involve consumers' demand response arising in the power sector. The main formulations and concepts of bilevel optimization are presented. The importance of demand response as a "dispatchable" resource in the evolution of power networks to smart grids is emphasized. The hierarchical nature of the interaction between decision-makers controlling different sets of variables in several problems involving demand response is highlighted, which establishes bilevel optimization as an adequate approach to decision support. The main concepts and solution approaches to those problems are underlined, in the context of the theoretical, methodological, and computational issues associated with bilevel optimization.

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Section: Demand Response In Microgrid Planning and Operationmentioning

confidence: 99%

Bilevel optimization to deal with demand response in power grids: models, methods and challenges

Antunes

Alves

Ecer

2020

TOP

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“…The Benders Decomposition technique was utilized in the robust‐stochastic framework to minimize renewable energy curtailment costs and total operating costs. A game theory‐based scheduling framework was developed in Haghifam et al 12 to model the interaction among distribution network operators (DNO), DR aggregators (DRA), and microgrid operators (MGO). A bi‐level leader versus multi‐follower model is proposed in the above research to minimize the DNO operating costs and maximize the profit among DRA and MGO.…”

Section: Introductionmentioning

confidence: 99%

Customer‐orientedenergy demand management of grid connected microgrids

et al. 2021

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Summary The consumers' active participation in production and energy consumption in response to market changes is an integral characteristic of the smart grid paradigm. In other words, their role in energy trading, either at the individual capacity or as aggregators, will shape the future of fulfilling energy needs. Despite the foreseen technological advancements, the design and implementation of demand response programs (DRPs) with accurate customer responsiveness have remained essential for network operators. Moreover, with non‐dispatchable energy sources' involvement, DRPs play a vital role in shaping the load profile and minimizing the operating costs. It calls for a need to develop a suitable energy management system (EMS) to promote consumers' active participation. With this sense, the incentive‐based DRPs are incorporated into the microgrid EMS to investigate their impact on day‐ahead scheduling costs and managing consumers load profile. A stochastic‐based EMS framework is proposed to this end, and five distinct types of DRPs are implemented on a practical microgrid network, including commercial, industrial, and residential loads. The flexible price elasticity concept is adopted to model the realistic behavior of price responsive loads under different DRPs. Finally, the recently reported novel optimizer is employed to solve the proposed EMS problem and investigate the flexible price model's impact on optimizing the grid‐connected microgrid's daily operating costs. The obtained simulation results are compared with the existing state‐of‐the‐art metaheuristic optimizers to test the attributes related to solution efficiency and convergence rate.

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“…Several researchers proposed various approaches to handle the distribution networks include optimal network reconfiguration (ONR), optimal allocation of DG, and simultaneous optimization of both ONR and DG allocation. ONR is an approach to change the configuration of distribution system by changing the opening/closing status of the sectionalizing (normally closed) and the tie (normally open) switches of the network, so that the radiality and connectivity are well maintained [2]. The distribution networks need to be expanded to meet the increasing demand, however, it is a big issue as it is associated with various economic and environmental factors.…”

Section: Introductionmentioning

confidence: 99%

Optimal Operation of Smart Distribution Networks using Gravitational Search Algorithm

Salkuti¹

2021

IJACSA

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This paper proposes a methodology for an optimal operation of smart distribution network considering the network reconfiguration, distributed generation (DG) units allocation and optimally placing the shunt capacitors for reactive power compensation. In this work, the total power losses minimization objective is considered. By optimizing this objective, it can also results in the reduction of voltage deviation. The proposed problem is solved using evolutionary-based gravitational search algorithm (GSA). Simulation studies are performed on 33 bus radial distribution system (RDS). Simulation results reveal that there is a drastic reduction in the power losses by utilizing the network reconfiguration, DG allocation, and reactive power compensation.

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Optimal operation of smart distribution networks in the presence of demand response aggregators and microgrid owners: A multi follower Bi-Level approach

Cited by 55 publications

References 44 publications

Bilevel optimization to deal with demand response in power grids: models, methods and challenges

Bilevel optimization to deal with demand response in power grids: models, methods and challenges

Customer‐orientedenergy demand management of grid connected microgrids

Optimal Operation of Smart Distribution Networks using Gravitational Search Algorithm

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