Optimal Allocation of Combined Renewable Distributed Generation and Capacitor Units for Interconnection Cost Reduction

Ouali, Saad; Cherkaoui, Abdeljebbar

doi:10.1155/2020/5101387

Cited by 15 publications

(7 citation statements)

References 41 publications

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“…In [25], a simplified heuristic method was studied for this problem, aiming for simplicity in the implementation and application to large distribution systems. An analytical optimization method is developed in [26] to minimize interconnection costs.The optimization considered geographical data of the network topology for the generation landuse and network infrastructure, which are neglected in most works.…”

Section: Related Workmentioning

confidence: 99%

Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations

et al. 2022

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The allocation of distributed generation and capacitor banks is critical for success in the planning of power grids. A methodology is developed for the optimal placement of distributed renewable generation (wind and photovoltaic powers) and capacitor banks is developed based on technical and economic parameters. In order to preserve the horoseasonal and stochastic dependence nature of the wind and solar power, the methodology uses a model that integrates the sequential Monte Carlo method and the diagonal band Copula model, integrating historical data of wind speed, solar radiation and feeder load from the region of study. An efficient algorithm based on Genetic Algorithms is proposed to implement the optimization. The algorithm validation demonstrates a reduction of up to 71.7% in annual losses of active power in the Bandeira feeder and 73.4% in the Recife feeder, with adequate voltage levels and a return on investment of 6-7 years."

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Section: Related Workmentioning

confidence: 99%

Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations

et al. 2022

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“…In the present scenario, nature-inspired algorithms have gained attention and eventually became a powerful tool to solve complex power system optimization problems easily. A recent meta-heuristic algorithm, "Bat Algorithm", is proposed by Xin-She Yang in 2010 [33], which is based on the behavior of natural bats using echo signals for locating their food sources. Bats have an interesting way of determining obstacles even in complete darkness by radiating sound waves from their wings.…”

Section: Bat Algorithmmentioning

confidence: 99%

Optimal Integration of Capacitor and Distributed Generation in Distribution System Considering Load Variation Using Bat Optimization Algorithm

et al. 2021

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In this article, an efficient long-term novel scheduling technique is proposed for allocating capacitors in a combined system involving distributed generation (DG) along with radial distribution systems (RDS). We introduce a unique multi-objective function that focuses on the reduction of power loss with the maximization of voltage stability index (VSI) subjected to constraints of equality and inequality systems. Loss sensitivity factor and VSI together are involved in pre-identifying the locations of capacitors and DG. Determination of the optimal size of capacitor and DG is performed by utilizing the Bat algorithm (BA) for all the loads in RDS. The conventional approach considers the medium load of (1.0) condition generally, but the proposed method changes the feeder loads linearly, ranging from light load (0.5) to peak load (1.6) with the value of step size as 1%. BA determines the optimal size of the capacitor and DG for each step load. The curve fitting technique is used for deducing the generalized equation of capacitor size and DG for all conditions of the load with the various loading condition sized by distributed network operators (DNOs). Further, various load models such as industrial, residential, and commercial loads have been considered to show the efficiency of the present approach. Validation of results is performed in different scenarios on a 69-bus test system and on a standard IEEE 33-bus system. The results exhibit improved accuracy with less power loss value, superior bus voltage, and stability of system voltage with a higher rate of convergence.

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“…The considered objectives are technical, and the total investment cost is for the allocation of both non-dispatchable and dispatchable DG units. The analytical approach discussed by Ouali and Cherkaoui (2020) considers the practical considerations such as network topology reconfiguration, geographical data of the generator land use and network infrastructures. This encourages private investors to build renewable DG by minimizing the cost of interconnecting the generation units in public networks.…”

Section: Introductionmentioning

confidence: 99%

Optimal location and sizing of various DG units in real distribution substation using heuristic approach

M.L.¹,

Suja²,

2022

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Purpose The purpose of the study is distributed generation planning in a radial delivery framework to identify an appropriate location with a suitable rating of DG units energized by renewable energy resources to scale back the power loss and to recover the voltage levels. Though several algorithms have already been proposed through the target of power loss reduction and voltage stability enhancement, further optimization of the objectives is improved by using a combination of heuristic algorithms like DE and particle swarm optimization (PSO). Design/methodology/approach The identification of the candidate buses for the location of DG units and optimal rating of DG units is found by a combined differential evolution (DE) and PSO algorithm. In the combined strategy of DE and PSO, the key merits of both algorithms are combined. The DE algorithm prevents the individuals from getting trapped into the local optimum, thereby providing efficient global optimization. At the same time, PSO provides a fast convergence rate by providing the best particle among the entire iteration to obtain the best fitness value. Findings The proposed DE-PSO takes advantage of the global optimization of DE and the convergence rate of PSO. The different case studies of multiple DG types are carried out for the suggested procedure for the 33- and 69-bus radial delivery frameworks and a real 16-bus distribution substation in Tamil Nadu to show the effectiveness of the proposed methodology and distribution system performance. From the obtained results, there is a substantial decrease in the power loss and an improvement of voltage levels across all the buses of the system, thereby maintaining the distribution system within the framework of system operation and safety constraints. Originality/value A comparison of an equivalent system with the DE, PSO algorithm when used separately and other algorithms available in literature shows that the proposed method results in an improved performance in terms of the convergence rate and objective function values. Finally, an economic benefit analysis is performed if a photo-voltaic based DG unit is allocated in the considered test systems.

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Optimal Allocation of Combined Renewable Distributed Generation and Capacitor Units for Interconnection Cost Reduction

Cited by 15 publications

References 41 publications

Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations

Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations

Optimal Integration of Capacitor and Distributed Generation in Distribution System Considering Load Variation Using Bat Optimization Algorithm

Optimal location and sizing of various DG units in real distribution substation using heuristic approach

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