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EN
This article presents the optimization implemented to give the optimal architecture for a microgrid (MG) with minimum cost. In this framework, three configurations had created using HOMER software. The first MG1 consists of a PV system, wind turbine, and a battery, all of the systems connected to a residential load of 11.2 kWh/d with a peak load demand of 2.11 kW in Saida, Algeria. The second MG2 is the same as MG1 with the addition of a diesel generator. The third MG3 is MG1 connected to the electrical grid. The results show that MG3 is the best configuration, with a TNPC of 14,054$, a COE (Cost Of Energy) of 0.269$/kWh, and a renewable fraction (RF) of 87.9%.
PL
W artykule przedstawiono optymalizację wdrożoną w celu uzyskania optymalnej architektury mikrosieci (MG) przy minimalnych kosztach. W ramach tego projektu stworzono trzy konfiguracje za pomocą oprogramowania HOMER. Pierwszy MG1 składa się z systemu fotowoltaicznego, turbiny wiatrowej i baterii, przy czym wszystkie systemy są podłączone do obciążenia mieszkalnego wynoszącego 11,2 kWh/d przy szczytowym zapotrzebowaniu na obciążenie 2,11 kW w miejscowości Saida w Algierii. Drugi MG2 jest taki sam jak MG1 z dodatkiem generatora diesla. Trzeci MG3 to MG1 podłączony do sieci elektrycznej. Wyniki pokazują, że MG3 jest najlepszą konfiguracją, z TNPC na poziomie 14 054 USD, COE (Koszt Energii) na poziomie 0,269 USD/kWh i frakcją odnawialną (RF) na poziomie 87,9%.
EN
One of the pillars for the development of isolated communities is electricity, however the implementation of conventional networks is limited as a result of the difficulties of the terrain. This paper aims to analyze the technical-economic feasibility of implementing a hybrid off-grid solar photovoltaics (PV)/diesel generator (DG)/battery (BATT) based power system for the electrification of rural communities, using a case study in Bameno, Ecuador. The simulation and optimization of the system is done using Hybrid Optimization of Multiple Energy Resources (HOMER) software. As a result, the optimal sizing is composed of 23 kW PV modules, a DG 27 kW, 88.4 kWh storage batteries and 9.4 kW converter system, obtaining a levelized cost of energy (LCOE) of 0.359 $/kWh. After the optimization is executed, a sensitivity analysis is performed to establish the effects of the variations of solar radiation, demand, fuel, and component costs on the system. The PV/DG/BATT system is considered the best choice for fuel prices up to $0.83 per liter. For higher values the optimal system is the PV/BATT. It is also established that the LCOE is mostly affected by the cost of technological components, followed by variations in solar radiation and demand.
EN
Renewable energy application is gaining a wide acceptance by end users; however, considering the fact that renewable energy is intermittent, variable and cannot be predicted, the need of storage systems is becoming a necessity at both micro and macro levels. Fuel cell technology is one of the most promising storage systems due to the fact that hydrogen has high energy density. This paper presents a design of stand-alone PV-PEMFC hybrid system for a small house under Amman climate. The simulation results show that the optimal size of PV array, fuel cell (PEMFC), inverter, electrolyzer (ELE) and H2 Tank capacity were 10 kW, 1 kW, 5 kW, 6 kW, and 5 kg respectively. Hydrogen proved itself as a low carbon energy source, which is environmental friendly and characterized with high energy content per unit mass. Due to fuel cells technology, hydrogen can be used for inter-season storage.
EN
This paper presents the optimal sizing of PV/Wind/Fuel Cell/Battery Hybrid Energy System for energizing a Small Scale Industrial Application or a village domestic load of 200 kW. HOMER software is used for simulation of the complete system. The solar radiation data and wind speed data used in this paper are for the place of Coimbatore, Tamil Nadu, India which is located 11.0183° N longitude and 76.9725° E latitude. The optimized sizes of components of Hybrid Power System (HPS) are found based on Levelised Cost of Energy (LCE) and total Net Present Cost (NPC). The results are presented and compared for five different combinations of HPS components. Suggestions are also presented to choose the low cost system which produces energy at low LCE.
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