DSTATCOM Positioning in Radial Distribution Networks Using BVSI and Genetic Algorithm
Hassane Ousseyni Ibrahim,
François-Xavier Fifatin,
Arouna Oloulade,
Adolphe Moukengue Imano,
Antoine Cokou Vianou
Issue:
Volume 11, Issue 2, March 2022
Pages:
23-30
Received:
25 April 2022
Accepted:
11 May 2022
Published:
19 May 2022
Abstract: The distribution networks of African cities are for the most part in degradation of the required quality due to the exponential evolution of the loads due to demography and industry. In this paper, a hybrid approach based on an analytic-metaheuristic method called (BVSI-GA) developed in the MATLAB environment was used to dimension and position in an ultra-optimal way a DSTATACOM in a quasi-disaster network of Maradi in Niger. Indeed, the positioning of a DSTATCOM with a power of 1840 kVAr at node 40 in this 123-bus distribution network has contributed to reduce the losses in this network by 19.08% with a voltage profile improvement of 2.44%. On the other hand, the exploration of a multiple positioning in order to better secure and make this 123-node network more reliable in case of failure of any of the multiple DSTATACOMs contributed to reducing losses by 25.76%, i.e., a performance improvement of 6.68% compared to the mono-DSTATACOM. As for the tension profile in this case was improved by 2.78% compared to the initial case and by 0.34% to the mono positioning case. The method used in this study is accessible to operators and is effective in predicting and performing distribution networks in African countries, which are nowadays confronted with various contingencies that must be controlled within the limits of tolerable time.
Abstract: The distribution networks of African cities are for the most part in degradation of the required quality due to the exponential evolution of the loads due to demography and industry. In this paper, a hybrid approach based on an analytic-metaheuristic method called (BVSI-GA) developed in the MATLAB environment was used to dimension and position in a...
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Hydro Backed-up Hybrid Renewable System for Off-grid Power in Nigeria
Chidiebere Diyoke,
Lesodah Esther Eja,
Ugwu Kenneth Chikwado
Issue:
Volume 11, Issue 2, March 2022
Pages:
31-47
Received:
29 April 2022
Accepted:
16 May 2022
Published:
26 May 2022
Abstract: This paper reports on a hydro backed-up (HPBU) hybrid renewable energy system (HRES) for a rural off-grid community in Kwara State Nigeria with an average demand load of 550.9 kWh (90.7 kW peak) per day. By using HOMER Pro software, the formulation and identification of the best reliable system architecture for attaining technical and economic viability while using nearby existing RE sources such as hydro, wind and solar energy are appropriately modelled and optimized based on the minimal net present cost (NPC) and cost of energy (COE). It was determined that the three best feasible configurations of a HPBU-HRES for the site have an annual output ranging from 1,642,979 – 1,749,272 kWh/yr and a cost of electricity (COE) in the range of 0.34 – 0.64 $/kWh. The best optimal HPBU-HRES (system 1) is a combination of 184 kW of solar PV (PV), 4,545 kWh of battery capacity (BB), 81.3 kW of converter (Conv) and 277 kW of hydro generation capacity (HPP). A comparison study undertaken to illustrate the economic benefits of the studied systems shows that about 288,116, 88,342 and 53, 88 kg/yr of CO2 savings is possible against diesel only, grid extension and first best equivalent diesel engine backed-up (DEBU) system respectively. In furtherance of the study, a sensitivity analysis of the likely variation associated with the metrological parameters, load and cost of components was undertaken. The Outcomes show that system 1 (PV/HPP-BB) is the optimal system for small to medium loads (≤600 kWh/day), irrespective of the solar radiation. In addition, it is established that a decrease in the system’s total initial cost by half will lead to a decline of COE to $0.177 per kWh at a corresponding NPC of $3,029.
Abstract: This paper reports on a hydro backed-up (HPBU) hybrid renewable energy system (HRES) for a rural off-grid community in Kwara State Nigeria with an average demand load of 550.9 kWh (90.7 kW peak) per day. By using HOMER Pro software, the formulation and identification of the best reliable system architecture for attaining technical and economic viab...
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