Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives

Kianmehr, Ehsan; Nikkhah, Saman; Rabiee, Abbas

doi:10.1016/j.renene.2018.08.032

Cited by 79 publications

(37 citation statements)

References 30 publications

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“…A multistate variable WT is modeled using wind speed and its different intervals as scenario intervals. After determining the probability of each scenario, mean value of wind speed and generated power in terms of wind speed are calculated . In Martins and Borges, two methods are introduced to analyze multiple scenarios.…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration of distribution systems in the presence of distributed generation considering protective constraints and uncertainties

Fathi

Seyedi

Mohammadi‐Ivatloo

2020

Int Trans Electr Energ Syst

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Summary Distribution network reconfiguration is a common method to achieve objectives such as minimization of power loss and voltage deviations. There exist several different algorithms to find the optimal configuration of network. Almost all of these algorithms consider the main operational constraints such as voltage, current, and power limits. Although it is crucially important to incorporate protective devices and their constraints in the reconfiguration problem, there are few works in network reconfiguration considering protection system. Accordingly, this paper presents a new reconfiguration algorithm considering protective constraints in the presence of distributed generation (DG) units. The objective function of this paper is power loss, which is minimized subject to both operation and protection constraints. In addition to the protection constraints, the effects of DG units on the reconfiguration are considered in this work. Uncertainties in loads and power generation of DG units are also investigated, using a new scenario‐based algorithm. Two test systems are utilized to illustrate the efficiency of the proposed method and to compare it with conventional approaches. Moreover, in order to evaluate the performance of new scenario‐based algorithm, it is compared with Monte Carlo simulations.

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Section: Introductionmentioning

confidence: 99%

Reconfiguration of distribution systems in the presence of distributed generation considering protective constraints and uncertainties

Fathi

Seyedi

Mohammadi‐Ivatloo

2020

Int Trans Electr Energ Syst

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“…Another way to cope with unbalances of microgrid production and consumption is to utilize DSM programs [1]. All activities aiming to match the supply and demand by modifying time and/or shape of customers' demand profile is called DSM [30].…”

Section: Category 3: Dsm-based Emsmentioning

confidence: 99%

“…There are strong incentives to utilize distributed generations (DGs) for reducing greenhouse gases, improving power system efficiency as well as its reliability, competitive energy policies and postponement of transmission and distribution system upgrading [1]. In fact, DGs are composed of renewable units such as wind turbines (WTs), photovoltaic (PV), fuel cells (FCs), biomass along with non-renewable ones such as micro-turbines (MTs), gas engines (GEs), diesel generators (DiGs), etc.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

et al. 2019

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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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“…All of the abovementioned papers demonstrate the multiobjective reconfiguration of distribution networks based on specific types of metaheuristic and some new techniques to achieve different objectives, which are converted to a single objective aiming to find a trade-off solution by the most common methods, such as the compromise model [22]- [25], the entropy method [26], and the analytic hierarchy process [21], [27], without considering the mutual constraints among the objectives. However, the simple multiobjective traditional methods are no longer applicable for an automated distribution system with multiple conflicting objectives for scheduling known optimized solutions simultaneously.…”

Section: Introductionmentioning

confidence: 99%

A Chaos Disturbed Beetle Antennae Search Algorithm for a Multiobjective Distribution Network Reconfiguration Considering the Variation of Load and DG

Wang

Yuan

et al. 2020

IEEE Access

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As the distributed generation (DG) in a power supply and the user load demand constantly change in an actual distribution network, multiobjective optimal network reconfiguration considering variations in load and DG has become a major concern, which is important and required to make system operations safe and economical. The aim is to minimize the sum of the active power loss, the sum of the load balancing index and the sum of the maximum node voltage deviation index simultaneously during the reconfiguration period. Here, this article proposes a new Chaos Disturbed Beetle Antennae Search (CDBAS) algorithm to reduce the computational time and solve the multiobjective optimal problem of network reconfiguration. To adopt the Chaos Disturbed Beetle Antennae Search algorithm for solving this multiobjective problem, grey target decision-making technology is used to rank the beetles. Additionally, to the enhance the system static voltage stability and voltage quality, a grey target decision-making model is established to achieve a layer relationship between each index and the switching operation index. The plausibility and effectiveness of the presented methodology is verified on the modified IEEE 33, 69 and 118-Bus Test Radial Distribution Network. Finally, compared with other research methods in the literature, the CDBAS algorithm outperforms other algorithms and produces a quality decision solution. INDEX TERMS Distribution system, load and distributed generation variation, multiobjective optimization, grey target decision-making, CDBAS algorithm. HAIYUN WANG received the B.E. degree in electric power systems and automation from Xin

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Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives

Cited by 79 publications

References 30 publications

Reconfiguration of distribution systems in the presence of distributed generation considering protective constraints and uncertainties

Reconfiguration of distribution systems in the presence of distributed generation considering protective constraints and uncertainties

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

A Chaos Disturbed Beetle Antennae Search Algorithm for a Multiobjective Distribution Network Reconfiguration Considering the Variation of Load and DG

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