Energy Saving Maximization of Balanced and Unbalanced Distribution Power Systems via Network Reconfiguration and Optimum Capacitor Allocation Using a Hybrid Metaheuristic Algorithm

Mohamed, Mohamed Abd‐El‐Hakeem; Ali, Ziad M.; Ahmed, Mahrous; Al-Gahtani, Saad F.

doi:10.3390/en14113205

Cited by 15 publications

(14 citation statements)

References 56 publications

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“…[8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] Among the recent studies that dealt with the best ways to implement this strategy. There are other strategies, such as system reconfiguration [27][28][29][30][31][32] as well as distributed generation, [33][34][35][36][37][38][39][40][41] that need high capital to proceed with their implementation, which may not be available. In recent years, series capacitors have been used high-voltage networks, and it gives many profits.…”

Section: Enhancing Distribution System Performance Strategiesmentioning

confidence: 99%

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Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

Mohamed

Abdelaziz

Darwish

et al. 2023

Energy Science & Engineering

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As the load on distribution networks grows, system operators and planners are constantly challenged with the issue of voltage regulation or enhancing the quality of supply to customers at the load end of lengthy distribution lines. This paper presents the optimum determination of series capacitor units in a distribution system to maximize energy-saving and enhance voltage levels. Interestingly, series capacitors can enhance the capability of transmission lines, reduce line losses, enhance the performance of buses with large induction motor loads and reduce voltage flicker. At the same time, the limitations of series compensation are taken into consideration while calculating its optimum values. To achieve the planning objective and optimal load flow objective, two strategies: The Improved Grey Wolf Optimization method (I-GWO) and Tabu Search (TS), are hybridized to get the benefit of their advantages. The I-GWO has a movement strategy called dimension learning-based hunting for enhancing the balance between global and local search and maintaining diversity. The proposed (I-GWO-TS) algorithm can solve mixed-integer programming to achieve the planning and the optimal load flow objectives. The proposed method can be applied to a real Egyptian distribution system that is heavily loaded, with poor voltage regulation, and also has high-power losses. The obtained results demonstrate the capability of the proposed approach to determine optimal series capacitors' location and sizing for maximization of energy saving. Further, the proposed method improves the network performance regarding the voltage profile and power losses, although the limitations of including series compensation were considered in the distribution system.

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Section: Enhancing Distribution System Performance Strategiesmentioning

confidence: 99%

“…These are constantly developed. Recently, two or more algorithms have been integrated so that they support each other to reach the optimal solution to our problems, [20][21][22][23][24][25]30,35,37…”

Section: Enhancing Distribution System Performance Strategiesmentioning

confidence: 99%

Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

Mohamed

Abdelaziz

Darwish

et al. 2023

Energy Science & Engineering

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“…Hence, very scattered results are available to consider the balanced three-bus system. Mohamed et al [28] has considered both balanced and unbalanced IEEE-123 bus systems for NR with optimal DGU and SCU choices using the Harper sphere and modified Tabu search algorithm. Gangwar et al [10] also present multiobjective planning for balanced and unbalanced IEEE-33 and 123-bus systems considering Monte Carlo simulation.…”

Section: For Phase 3 (123-bus System)mentioning

confidence: 99%

Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Mehroliya,

Arya

2023

Comp Applic In Engineering

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In the transmission and distribution networks, both active and reactive power play significant roles. While active power does the beneficial work, reactive power maintains the voltage that necessitates management from a system reliability perspective. The voltage variation from the nominal range may result in unintentional operation and early component failure. To maximize the amount of real power that can be transported over the power‐transmitting media, the system must also control reactive power flow. In a three‐phase unbalanced distribution system reinforced with distributed generator units (DGUs) and shunt capacitor units (SCUs), this paper suggests a teaching learning‐based optimization (TLBO) approach to be applied to combinatorial problems for simultaneous reduction of real power loss and net reactive power flow, enhance voltage stability index (VSI) and minimize aggregated voltage deviation index. A multiobjective formulation based on TLBO has been implemented to choose the ideal sizes and placements of DGUs and SCUs in large distribution networks. The case studies have been carried out on an IEEE 33‐bus standard system and a large 123‐bus unbalanced system. The analysis of the IEEE 33‐ and 123‐bus test systems reveals the economic efficiency of the suggested TLBO algorithm. Notably, by applying DG and capacitor simultaneously in the 33‐bus system, a significant reduction of 59.35%, 55.05%, and 50.76% (phases a, b, and c), and for the 123‐bus system, a significant reduction of 43.65%, 19%, and 48.65% (phases a, b, and c) in total active power losses have been achieved. The results suggest that the proposed method renders significant improvement in voltage stability and reduces power losses concerning the base case for both test systems.

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“…In addition, the majority of studies were carried out considering the power demand fixed, i.e., without load variations over time. Some examples that present unbalanced systems with variable demand are [31][32][33][34][35]. In [31,32], the DNR problem for unbalanced systems is solved through a heuristic approach, while in [33][34][35], the authors applied, respectively, a heuristic together with GA [33], GA [34] and TSA, together with a harper search sphere (HSS) [35].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some examples that present unbalanced systems with variable demand are [31][32][33][34][35]. In [31,32], the DNR problem for unbalanced systems is solved through a heuristic approach, while in [33][34][35], the authors applied, respectively, a heuristic together with GA [33], GA [34] and TSA, together with a harper search sphere (HSS) [35]. In the majority of cases, although dealing with unbalanced networks, unbalance indexes are not taken into consideration, with only some papers dealing with this aspect, for example [29,36].…”

Section: Literature Reviewmentioning

confidence: 99%

Distribution Network Reconfiguration Considering Voltage and Current Unbalance Indexes and Variable Demand Solved through a Selective Bio-Inspired Metaheuristic

2022

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Operation of distribution networks involves a series of criteria that should be met, aiming for the correct and optimal behavior of such systems. Some of the major drawbacks found when studying these networks is the real losses related to them. To overcome this problem, distribution network reconfiguration (DNR) is an efficient tool due to the low costs involved in its implementation. The majority of studies regarding this subject treat the problem by considering networks only as three-phase balanced, modeled as single-phase grids with fixed power demand, which is far from representing the characteristics of real networks (e.g., unbalanced loads, variable power and unbalance indexes). Due to the combinatorial nature of the problem, metaheuristic techniques are powerful tools for the inclusion of such characteristics. In this sense, this paper proposes a study of DNR considering balanced and unbalanced systems with variable power demand. An analysis of the direct influence of voltage unbalance index (VUI) and current unbalance index (CUI) is carried out for unbalanced cases. To solve the DNR problem, a selective bio-inspired metaheuristic based on micro bats’ behavior named the selective bat algorithm (SBAT) is used together with the EPRI-OpenDSS software (California, US, EPRI). Tests are initially conducted on balanced systems, aiming to validate the technique proposed for both demands and state their differences, and then they are conducted on unbalanced systems to study the influence of VUI and CUI in the DNR solution.

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Energy Saving Maximization of Balanced and Unbalanced Distribution Power Systems via Network Reconfiguration and Optimum Capacitor Allocation Using a Hybrid Metaheuristic Algorithm

Cited by 15 publications

References 56 publications

Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Distribution Network Reconfiguration Considering Voltage and Current Unbalance Indexes and Variable Demand Solved through a Selective Bio-Inspired Metaheuristic

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