PV System Design for Off-Grid Applications

Mohanty, Parimita; Sharma, Karnamadakala Rahul; Gujar, Mukesh; Kolhe, Mohan Lal; Azmi, Aimie Nazmin

doi:10.1007/978-3-319-14663-8_3

Cited by 17 publications

(14 citation statements)

References 18 publications

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“…The capital cost of the 14.4kWh battery is calculated as 2880$ at a rate of 200$/kWh. The battery lifespan is calculated by (21) as 13.5 years and the battery recovery factor is found as 0.100143 by (17). The annualized battery cost or real battery capacity loss cost is then estimated as 288.4$ using the expression in (18).…”

Section: A Grid-connected With Battery Energy Storagementioning

confidence: 99%

“…The capital recovery factor and the annualized battery cost can be calculated by ( 17) and ( 18 (17) where ݅ is the annual interest rate and ܰ is the battery lifetime, and…”

mentioning

confidence: 99%

“…where ‫ܤ‬ ሺ݀, ‫ݐ‬ሻ is the battery capacity loss on day ݀ at time ‫,ݐ‬ ‫ܤ‬ ௩௦௧ି௦௧ is the battery investment cost and ‫ܪܱܵ‬ is the battery minimum state of health.The battery has the following dynamic equation[17]: www.etasr.com Regis et al: Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost ……”

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confidence: 99%

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Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost Minimization using PSO Algorithm

Regis¹,

Muriithi

Ngoo

2019

Eng. Technol. Appl. Sci. Res.

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This paper proposes a new optimization technique that uses Particle Swarm Optimization (PSO) in residential grid-connected photovoltaic systems. The optimization technique targets the sizing of the battery storage system. With the liberation of power systems, the residential grid-connected photovoltaic system can supply power to the grid during peak hours or charge the battery during non-peak hours for later domestic use or for selling back to the grid during peak hours. However, this can only be achieved when the battery energy system in the residential photovoltaic system is optimized. The developed PSO algorithm aims at optimizing the battery capacity that will lower the operation cost of the system. The computational efficiency of the developed algorithm is demonstrated using real PV data from Strathmore University. A comparative study of a PV system with and without battery energy storage is carried out and the simulation results demonstrate that PV system with battery is more efficient when optimized with PSO.

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Section: A Grid-connected With Battery Energy Storagementioning

confidence: 99%

“…The capital recovery factor and the annualized battery cost can be calculated by ( 17) and ( 18 (17) where ݅ is the annual interest rate and ܰ is the battery lifetime, and…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost Minimization using PSO Algorithm

Regis¹,

Muriithi

Ngoo

2019

Eng. Technol. Appl. Sci. Res.

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“…The PV system's efficiency variation is based on different factors where climate conditions, PV module's sort, an inverter's efficiency, and type are majors. Apart from the above-said parameters, site area is also important for a PV plant design [10]. A systematic approach is required and important when designing and modelling off systems.…”

Section: Introductionmentioning

confidence: 99%

Design and Modelling of PV Power Plant for Rural Electrification in Kayonza, Rwanda

Bakundukize

Twizerimana

Bernadette

et al. 2021

JENRR

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Aims: This study aimed to design and model an off-grid SPV power plant with a storage system to meet the load required in Rwisirabo village. Study Design: PV modules, inverter, charge controller, and Batteries have been designed, reproduced/simulated, and optimized for the rural area of Rwisirabo village in Kayonza district, Eastern Province, Rwanda. Place and Duration of Study: The experiment has been done in the University of Rwanda/ African Centre of Excellence in Energy Studies for Sustainable Development (UR/ACE-ESD) High E-Tech Smart Grid Laboratory, Kigali, Rwanda between October 2020 and February 2021. Methodology: Different methodologies have been applied to address the objective of this work. The site was identified, problems of the community were clearly stated, data required for the work was collected through various data collection mechanisms, and different literature was reviewed to identify the way to do this work. The data were collected from different sources and were analysed using a software tool (HOMER software) and simulated for getting a solution for the problems and challenged accordingly. An Off-grid Solar Photovoltaic Power Plant was established in Rwisirabo village in Kayonza District, Rwanda. This site has been chosen because, in the Mwiri sector, Kageyo cellule in Rwisirabo (Rwisirabo II) village is listed by National Electrification Plan (NEP) as the site to construct an off-grid solar PV Power Plant. Results: Based on the load assessment and the design of the SPV system, the primary AC load of the village was 551,718 kWh/day with a peak load of 85.10 kW, the deferrable load was about 9.99 kWh/day and a deferrable peak load of 2.00 kW with the cost of energy (COE) $0.200/kWh were involved during optimization of the power plant. It also found that the peak demand of the community occurs from 18:00 to 20:00 hours because most of the household members would expect to be at their homes. The system items such as PV module, batteries, and inverter size have been found as an optimum system with 220 kW, 860 BAE PVS 210 batteries, and 110 kW respectively with a lifespan of 25 years of the project. The total net present cost (NPC), initial capital, operating cost, and Levelized COE for this off-grid SPV system were $903,829, $517,000, $17,522, and $0.200/kWh respectively. The monthly results of power generation in kW obtained after stimulation with software showed that the solar radiation is high in March, July, August, and September which brings more electric power generation. However, all months the power electricity remain generated. Results from simulation showed that this system generated mean power output of 220 kW and total production of 297,291 kWh/year. It approved that the system converter contributed the lowest NPC with $52,888.25 (6%), followed by PV modules that cost $244,284.28 (27%) and battery bank the first for this SPV system with a cost of $606,656.60 (67%). This optimal system uses 100% renewable energy. Conclusion: It found that the implementation of an SPV system with battery storage in residential, commercial, and institutions in the area where the solar irradiance is concentrated across a country will reduce the cost of electricity and power interruption on the national grid. Therefore, further work is needed to optimize this system for rural electrification as well by integrating with other renewable sources available in the country and also extend the electrification to another area that is detached from the national grid.

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“…Grid connection is infeasible as the people are sparsely populated, less energy demand during peak times [10]. Off grid SPV technologies could be best alternative for such kinds of places to deliver modern energy source for lighting [11].…”

Section: Introductionmentioning

confidence: 99%

The Status and Determinants of Solar Photovoltaic Technology Utilization by Rural Households in Gozamin Woreda, Amhara National Regional State, Ethiopia

Alehegn¹

2019

IJEES

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Solar Photovoltaic technology has been advanced in the world as a renewable energy source many years ago. The progress of the technology is due to its social, economic and environmental benefits. However, utilization of solar photovoltaic technology by rural households in Ethiopia is a recent phenomenon with low rates of use. Hence, this study was conducted to meet the aim of exploring the status and determinants of solar photovoltaic technology utilization by rural households in Gozamin woreda. Three kebeles were purposively selected to conduct the study. Simple random and stratified sampling methods were used to get representative samples. Primary data and secondary information were also collected from households and reports, magazines, journals, etc. A total of 190 representative household samples were selected. Binary logit model was used to analyze the correlation between utilization of solar photovoltaic technology and explanatory variables. Descriptive statistics was also conducted to analyze the functionality, patterns and constraints of SPV technologies. The result of descriptive statistics showed that all the diffused technologies were functional. Despite this, 23.4 percent of SPV technologies fail to function once or twice per month due to weather conditions and technical incapability. Lighting was the major pattern of use by all (60) users. Additionally, 78.3 and 18.3 percent of the users use the technology for mobile charging and making petty trades respectively. The major constraints of SPV utilization were awareness gap, price increment and SPV providers shortage comprising of 70, 26.7 and 3.3 percent respectively. Moreover, the result of the binary logit model showed that age and income affected utilization of solar photovoltaic technology significantly with (P<0.01 and P<0.1) respectively. Similarly, wealth status, awareness creations made, providers of the technology, house quality and price of the technology also affected utilization significantly (P<0.05). Conversely, family size, agricultural land size, education level, market access, human capital and quality of technology explanatory variables were assumed to affect utilization, but they do not affected utilization of the technology. Suggesting distribution, financial and government institutions to make awareness, encourage more individuals to be provider of SPV technologies and avail long term credit access in order for the technologies to be bought.

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PV System Design for Off-Grid Applications

Cited by 17 publications

References 18 publications

Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost Minimization using PSO Algorithm

Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost Minimization using PSO Algorithm

Design and Modelling of PV Power Plant for Rural Electrification in Kayonza, Rwanda

The Status and Determinants of Solar Photovoltaic Technology Utilization by Rural Households in Gozamin Woreda, Amhara National Regional State, Ethiopia

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