Analytical Approach for Active Distribution Network Restoration Including Optimal Voltage Regulation

Sekhavatmanesh, Hossein; Cherkaoui, Rachid

doi:10.1109/tpwrs.2018.2889241

Cited by 60 publications

(40 citation statements)

References 28 publications

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“…However, the results obtained by the heuristic algorithm are inconsistent each time, and it is necessary to avoid falling into the local optimal situation, which requires the optimization of the limitations of the various algorithms, or the combination of the advantages of a variety of algorithms, to obtain the intelligent algorithm with a better solving performance. In addition, there are many solvers for convex optimization problems that can be used directly, such as Nairobi, Cplex, and Mosek, or in combination with toolkits, such as Yalmip (Sekhavatmanesh and Cherkaoui, 2019) and CVX.…”

Section: Solving Methodsmentioning

confidence: 99%

Review on Coordinated Planning of Source-Network-Load-Storage for Integrated Energy Systems

Fan

Xia

et al. 2021

Front. Energy Res.

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The integration of electricity, gas, and heat (cold) in the integrated energy system (IES) breaks the limitation of every single energy source, which is the development trend of future energy systems. To realize the coordinated planning of “source-network-load-storage,” the IES has to be conducive to improving energy efficiency, bringing economic and environmental benefit, and achieving sustainable development of energy. In this paper, the techniques and methods involved in IES planning are summarized. First, the structure and characteristics of the IES are briefly introduced. Second, the key findings of the IES planning are summarized from four perspectives: source, network, load, and storage. Then, the modeling methods of the IES collaborative planning are summarized, and the optimization methods for solving complex planning problems are analyzed. Compared with previous reviews, this paper focuses on the modeling of multi-energy coupling of each part of source-network-load-storage and modeling of the overall collaborative planning. Finally, the future research direction of IES planning is forecast.

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Section: Solving Methodsmentioning

confidence: 99%

Review on Coordinated Planning of Source-Network-Load-Storage for Integrated Energy Systems

Fan

Xia

et al. 2021

Front. Energy Res.

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“…In [23], service restoration was achieved through self-healing actions at the de-energized nodes of the system. The problem has been formulated as an analytical approach based on mixed-integer second-order cone programming (MISOCP).…”

Section: Introductionmentioning

confidence: 99%

Cost-Effective Outage Management in Smart Grid under Single, Multiple, and Critical Fault Conditions through Teaching–Learning Algorithm

Srinivasan

Kim

2020

Energies

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A distribution system becomes the most essential part of a power system as it links the utility and utility customers. Under abnormal conditions of the system, a definitive goal of the utility is to provide continuous power supply to the customers. This demands a fast restoration process and provision of optimal solutions without violating the power system operational constraints. The main objective of the proposed work is to reduce the service restoration cost (SRC) along with the elimination of the out-of-service loads. In addition, this work concentrates on the minimal usage and finding of optimal locations for additional equipment, such as capacitor placement (CP) and distributed generators (DGs). This paper proposes a two-stage strategy, namely, the service restoration phase and optimization phase. The first phase ensures the restoration of the system from the fault condition, and the second phase identifies the optimal solution with reconfiguration, CP, and DG placement. The optimization phase uses the teaching–learning algorithm (TLA) for optimal restructuring and optimal capacitor and DG placement. The robustness of the algorithm is validated by addressing the test cases under different fault conditions, such as single, multiple, and critical. The effectiveness of the proposed strategy is exhibited with the implementation to IEEE 33-bus radial distribution system (RDS) and 83-bus Taiwan Power Distribution Company (TPDC) System.

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“…In Sekhavatmanesh and Cherkaoui, a novel mathematical formulation was presented for the ADN reconfiguration in order to decrease the number of required binary variables while covering more practical scenarios compared with the existing models. Zhang et al proposed a novel DG planning methodology in ADN considering both DSM and network reconfiguration aiming to minimize the total cost over the planning horizon.…”

Section: Introductionmentioning

confidence: 99%

Optimal planning in active distribution networks considering nonlinear loads using the MOPSO algorithm in the TOPSIS framework

Ebrahimi

Rezaeian‐Marjani

Talavat

2019

Int Trans Electr Energ Syst

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Summary In recent years, harmonic distortion has sharply increased because of injecting harmonic components caused by using nonlinear loads in the distribution system. Uncontrolled harmonic distortion can bring damage to equipment of the power system, reduce the power system efficiency, and interrupt protection and measurement devices. This parameter can be managed using various resources and control programs in active distribution networks. This paper presents active distribution networks (ADNs) with multiple objective particle swarm optimization (MOPSO) algorithm using the technique for order of preference by similarity to ideal solution (TOPSIS) framework in the presence of nonlinear loads. The presented planning model manages the sample network to minimize the total harmonic distortion (THD) of the system while minimizing the operational and investment costs. Four active management schemes, network reconfiguration, distributed generation (DG) dispatch, demand‐side management (DSM), and reactive power compensation are considered for this purpose. Optimal sizing and siting of the energy storage system (ESS) is used to reduce peak load and operational costs. The IEEE 33 node distribution network is used to verify the proposed planning model.

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Analytical Approach for Active Distribution Network Restoration Including Optimal Voltage Regulation

Cited by 60 publications

References 28 publications

Review on Coordinated Planning of Source-Network-Load-Storage for Integrated Energy Systems

Review on Coordinated Planning of Source-Network-Load-Storage for Integrated Energy Systems

Cost-Effective Outage Management in Smart Grid under Single, Multiple, and Critical Fault Conditions through Teaching–Learning Algorithm

Optimal planning in active distribution networks considering nonlinear loads using the MOPSO algorithm in the TOPSIS framework

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