Optimal allocation of multiple DG units in radial distribution system using modified differential evolution technique

Kumar, Sajjan; Mandal, Debasis; Chakraborty, Nilanjan

doi:10.1109/ciec.2014.6959114

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…The above-listed objectives can be obtained by the allocation of DG which can be carried out in several ways, including versatile types of variables. The significant majority of optimisation methods focus on the DG sizing and placing only [9,[17][18][19]22,25,36,37]. Some methods also consider the selection of the DG type [3,7,20,22,23,31,38] but none of the mentioned methods combine the allocation of RES and ES or the allocation of RES and energy curtailment.…”

Section: Novelty Of the Papermentioning

confidence: 99%

“…Optimization can be carried out for different time horizons and with different time resolutions. Most of the papers present methods optimising the DG structure for a single moment, omitting the dimension of time [2,5,[8][9][10][11][17][18][19]22,23,25,36,[39][40][41]. This static approach does not allow us to include crucial aspects of daily demand changes or intermittent RES generation, which are included in the presented paper.…”

Section: Novelty Of the Papermentioning

confidence: 99%

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Comparison of the Use of Energy Storages and Energy Curtailment as an Addition to the Allocation of Renewable Energy in the Distribution System in Order to Minimize Development Costs

Andrychowicz

2020

Energies

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This paper presents a comparison of the efficiency of energy storage and energy curtailment as an addition to the allocation of renewable energy in the distribution system in order to minimize development costs using a Mixed Integer-Linear Programming (MILP). Energy sources and energy storages are selected, sized and allocated under operational circumstances such as grid congestions and weather conditions. Loads and power units are modeled by daily consumption and generation profiles respectively, to reflect the intermittent character of renewable generation and consumption of energy. The optimization is carried out for a one-year time horizon using twenty-four representative days. The method is verified on three main simulation scenarios and three sub-scenarios for each of them, allowing for the comparison of the efficiency of each used tool. The main scenarios differ in their share of energy from renewable energy sources (RES) in total consumption. In the sub-scenarios, different tools (RES sizing and allocation, energy storages (ES) sizing and allocation and energy curtailment) are used. The results of this research confirm that energy curtailment is a more efficient additional tool for RES sizing and allocation than energy storages. This method can find practical application for Distribution System Operators in elaborating grid development strategies.

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Section: Novelty Of the Papermentioning

confidence: 99%

Section: Novelty Of the Papermentioning

confidence: 99%

Comparison of the Use of Energy Storages and Energy Curtailment as an Addition to the Allocation of Renewable Energy in the Distribution System in Order to Minimize Development Costs

Andrychowicz

2020

Energies

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“…Kumar, D. Pal, et. al., [17] has discussed in the year 2014, the optimal allocation of multiple DG units in Radial Distribution System (RDS) using Modified Differential Evolution Technique. In this paper the DG units are integrated with the conventional radial distribution system, it provides several advantages like reduction of power losses, voltage improvement and the reliability of the system gets increased.…”

Section: Evolutionary Techniquesmentioning

confidence: 99%

Optimal Allocation and Sizing of DG in Radial Distribution System-A Review

Niveditha¹,

Sujatha²

2018

IJGDC

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Distributed Generation (DG) plays a vital role in modern power systems to achieve the requirements and satisfaction of end users while transmitting and distributing power from one to another point. It is a small scale generation which is also known as the embedded generation, dispersed generation or the decentralized generation. The optimal allocation of distributed generation (DG) on distributed network plays a crucial role in maximizing the benefits such as reduction of network losses and voltage profile improvement. There are many techniques used for the optimal allocation and sizing of DG in Radial Distribution System (RDS). The paper presented an overview and review the techniques used in some of the most popular methods includes load flow based methods, numerical techniques, intelligent techniques and evolutionary techniques. The evolutionary techniques include various optimization techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Ant Colony Optimization and so on. The paper also provides advantages and disadvantages of each method and useful guidelines for the further research in this area.

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“…A methodology for obtaining the optimal allocation of DG in radial distribution systems has been introduced by Hassan et al using multi‐objective function for minimizing power loss and improving voltage profile. In Kumar et al, the optimal placement and sizing of multiple DGs are reached by a new modified differential evolution technique. In Maya and Jasmin, the optimum sizing of PV sources is investigated in unbalanced distribution systems.…”

Section: Introductionmentioning

confidence: 99%

Switching strategy for DG optimal allocation during repairing fault periods on loop distribution networks

Hamad

el‐Ghany

Azmy

2017

Int Trans Electr Energ Syst

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Summary It is expected that the use of distributed generation (DG) will increase sharply in distribution systems, especially with the realization of smart grids. In spite of the benefits of DG in distribution systems, high penetration level of DGs could cause some challenges for the network. Therefore, the optimal sizing and siting of DGs should be identified carefully. In addition, different operating conditions have to be taken into account in this process. The DGs are usually installed depending on optimal siting and sizing techniques considering normal operating periods. During repairing fault periods, different locations and capacities of DGs may be preferable. In this paper, 2 scenarios of switching strategies are presented for attaining the optimal sizing and siting of DGs during repairing fault period starting from the optimal allocation obtained for normal operating period. Genetic algorithm is used for solving the optimization problem that is implemented for an actual loop distribution system in Egypt.

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Optimal allocation of multiple DG units in radial distribution system using modified differential evolution technique

Cited by 7 publications

References 7 publications

Comparison of the Use of Energy Storages and Energy Curtailment as an Addition to the Allocation of Renewable Energy in the Distribution System in Order to Minimize Development Costs

Comparison of the Use of Energy Storages and Energy Curtailment as an Addition to the Allocation of Renewable Energy in the Distribution System in Order to Minimize Development Costs

Optimal Allocation and Sizing of DG in Radial Distribution System-A Review

Switching strategy for DG optimal allocation during repairing fault periods on loop distribution networks

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