DG allocation for benefit maximization in distribution networks

Shaaban, Mostafa F.; Atwa, Y.M.; El-Saadany, Ehab F.

doi:10.1109/tpwrs.2012.2213309

Cited by 268 publications

(127 citation statements)

References 25 publications

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“…For planning purpose, wind speed can be normally regarded following the Weibull distribution, the expression of which can be found in [10].…”

Section: Wind Generationmentioning

confidence: 99%

“…S g w ), and binary decision for feeder upgrade (i.e. τ ij ), which is same to [8]- [10]. Besides, as DR option is incorporated, the contract design should be considered.…”

Section: Decision Variablesmentioning

confidence: 99%

“…The electricity purchase cost is assumed to be 3.9cent/kWh. The technical parameters of DWG units are extracted from [10].…”

Section: Test System and Basic Datamentioning

confidence: 99%

“…As such, two types of strategies, i.e., integrated planning [8]- [10] and demand response (DR) [11]- [14] have been suggested. The former group mainly aims to mitigate the network bottleneck by combining RDG installation into network planning to support higher RDG penetration without violating the system constraints.…”

Section: Introductionmentioning

confidence: 99%

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Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

Zeng¹,

Zhang²,

Zhang³

et al. 2014

Journal of Electrical Engineering and Technology

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-In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and CO 2 emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

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“…For planning purpose, wind speed can be normally regarded following the Weibull distribution, the expression of which can be found in [10].…”

Section: Wind Generationmentioning

confidence: 99%

“…S g w ), and binary decision for feeder upgrade (i.e. τ ij ), which is same to [8]- [10]. Besides, as DR option is incorporated, the contract design should be considered.…”

Section: Decision Variablesmentioning

confidence: 99%

“…The electricity purchase cost is assumed to be 3.9cent/kWh. The technical parameters of DWG units are extracted from [10].…”

Section: Test System and Basic Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

Zeng¹,

Zhang²,

Zhang³

et al. 2014

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

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“…Another study in [70] developed a GA-based multiobjective framework to locate and size DG units to find the best compromise between the network upgrade deferral and the costs related to energy losses, unserved energy, and imported energy. In addition, a recent study in [71] proposed a GA-based approach to place and size renewable DG units (i.e., biomass, wind and solar)…”

Section: Network Upgrade Deferralmentioning

confidence: 99%

Smart integration of distributed renewable generation and battery energy storage

Hung¹

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Renewable energy (i.e., biomass, wind and solar) and Battery Energy Storage (BES) are emerging as sustainable solutions for electricity generation. In the last decade, the smart grid has been introduced to accommodate high penetration of such renewable resources and make the power grid more efficient, reliable and resilient. The smart grid is formulated as a combination of power systems, telecommunication communication and information technology. As an integral part of the smart grid, a smart integration approach is presented in this thesis. The main idea behind the smart integration is locating, sizing and operating renewable-based Distributed Generation (DG) resources and associated BES units in distribution networks strategically by considering various technical, economical and environmental issues. Hence, the aim of the thesis is to develop methodologies for strategic planning and operations of high renewable DG penetration along with an efficient usage of BES units.The first contribution of the thesis is to present three alternative analytical expressions to identify the location, size and power factor of a single DG unit with a goal of minimising power losses. These expressions are easily adapted to accommodate different types of renewable DG units for minimizing energy losses by considering the time-varying demand and different operating conditions of DG units. Both dispatchable and nondispatchable renewable DG units are investigated in the study. Secondly, a methodology is also introduced in the thesis for the integration of multiple dispatchable biomass and nondispatchable wind units. The concept behind this methodology is that each nondispatchable wind unit is converted into a dispatchable source by adding a biomass unit with sufficient capacity to retain the energy loss at a minimum level. Thirdly, the thesis studies the determination of nondispatchable photovoltaic (PV) penetration into distribution systems while considering time-varying voltage-dependent load models and probabilistic generation. The system loads are classified as an industrial, commercial or residential type or a mix of them with different normalised daily patterns. The Beta probability density function model is used to describe the probabilistic nature of solar irradiance. An analytical expression is proposed to size a PV unit. This expression is based on the derivation of a multiobjective index (IMO) that is formulated as a combination of iii three indices, namely active power loss, reactive power loss and voltage deviation. The IMO is minimised in determining the optimal size and power factor of a PV unit. Fourthly, the thesis discusses the integration of PV and BES units considering optimal power dispatch. In this work, each nondispatchable PV unit is converted into a dispatchable source by adding a BES unit with sufficient capacity. An analytical expression is proposed to determine the optimal size and power factor of PV and BES units for reducing energy losses and enhancing voltage stability. A self-correction algorith...

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A novel multiobjective chaotic symbiotic organisms search algorithm to solve optimalDGallocation problem in radial distribution system

Saha

Mukherjee

2019

Int Trans Electr Energ Syst

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Summary This article presents a new method to decide the optimal locations and sizes of distributed generators (DGs) in radial distribution system (RDS). This task is associated with minimization of total voltage deviation and power loss and maximization of voltage stability index of the RDS. To solve this multiobjective DG allocation problem, a novel metaheuristic algorithm, namely, multiobjective chaotic symbiotic organisms search (SOS) (MOCSOS), is proposed in this article. The proposed MOCSOS is an improved version of the traditional SOS, where a chaotic local search technique is incorporated within the traditional SOS framework. The MOCSOS utilizes a fast nondominated sorting strategy to achieve the Pareto solutions. The constraints associated with this DG allocation problem are handled using a binary tournament selection–based approach. The performance of MOCSOS is validated on 33‐ and 69‐node RDSs. The efficacy of the MOCSOS is established by comparing its performance with other nature‐inspired state‐of‐the‐art algorithms.

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DG allocation for benefit maximization in distribution networks

Cited by 268 publications

References 25 publications

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

Smart integration of distributed renewable generation and battery energy storage

A novel multiobjective chaotic symbiotic organisms search algorithm to solve optimalDGallocation problem in radial distribution system

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