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Assessing the use of hybrid renewable energy system with battery storage for power generation in a University in Nigeria

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Abstract

This paper analyzes the adoption of an off-grid hybrid renewable energy system (HRES) for a high-rise building owned by a public institution in Nigeria. The analysis is based on the comparison between the use of a single criterion and multiple criteria in the selection of the most feasible energy system. The proposed HRES comprises of a wind turbine, diesel generator, photovoltaic (PV), and battery storage system. Hybrid optimization of multiple energy resources (HOMER) software was used to design the HRES for a case study (based on a single criterion-total net present cost), while Evaluation Based on Distance from Average Solution (EDAS) method was used to evaluate the effect of choosing an optimal system based on multiple criteria. Based on the simulations conducted with HOMER, eight feasible HRES (ES1-ES8) were identified. When the feasible HRES were ranked based on total (NPC), the optimal configuration comprises 70 kW PV modules, 20 kW diesel generating set, 40 kW converter, and 70, 3000 Ah batteries. The results obtained from the optimization process were subjected to a multi-criteria analysis based on sustainability principles. The ranking of the first two systems (ES1 and ES2) returned by single criterion (total NPC) remained the same, while changes were observed in the ranks of the remaining systems (ES3–ES8). This modular feasibility study shows that it would be economical to power the entire university using HRES. It is expected that this study would help the university communities and other stakeholders make informed decision during the planning stage of similar projects.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

HRES:

Hybrid Renewable Energy System

PV:

Photovoltaic

HOMER:

Hybrid optimization of multiple energy resources

EDAS:

Evaluation Based on Distance from Average Solution

NPC:

Net Present Cost

ES:

Energy System

SDG:

Sustainable Development Goal

IEA:

International Energy Agency

NASA:

National Aeronautics and Space Administrative

USAID:

United States Agency for International Development

REA:

Rural Electrification Agency

EEP:

Energizing Education Programme

TNPC:

Total Net Present Cost

CRITIC:

Criteria Importance Through Intercriteria Correlation

P pv :

Output of a PV panel

Y pv :

PV derating factor (%)

\( \overline{G_T} \) :

Solar irradiation incident on the PV array ((kW)/m2)

G T, STC :

Solar irradiation incident at standard condition

α P :

Temperature coefficient of power (%/°C)

T C :

PV cell temperature (°C)

T C, STC :

PV cell temperature under standard test conditions (°C)

P WT :

The output of a wind turbine

C e :

The maximum power extraction efficiency of the wind generator

A:

The swept area of turbine

ρ:

The density of air

v:

The wind speed

F:

The output of the diesel generator

F o :

The fuel curve intercept coefficient

Y gen :

The rated capacity of the generator (Kw)

F 1 :

The generator fuel curve slope\( \left(\frac{\frac{L}{hr}}{kW}\right) \)

P gen :

The output of generator in a specific time step which is usually 1 hour

E gen :

The generator’s total annual electrical production (kWh/year)

m fuel :

The generator’s total annual fuel consumption(kg/yr),

LHV fuel :

The lower heating value of the fuel (MJ/kg)

Batt aut :

The battery autonomy

D pry, ave :

The average primary energy demand

SOS min :

The minimum state of charge (%)

Q n :

The nominal capacity of a single battery (Ah)

V n :

The nominal voltage of a single battery (v)

n b :

The number of battery

Batt life :

The battery bank life

Q lifetime :

The lifetime throughput of a single battery (kWh)

Q thrpt :

The annual throughput of battery (kWh/yr)

f c :

The number of cycles to failure

DOD :

The depth of discharge

q max :

The maximum capacity of the battery (Ah)

f ren :

The fraction of energy delivered to the load that originated from renewable power sources

E nonren :

The non-renewable electrical production (kWh/yr)

E served :

The total electrical load served

E tot :

The total electrical production

C t :

The net inflow during the period t

ICC:

The initial capital cost

N:

The project life time

i:

The discount rate

C ann :

Total annualized cost ($/yr)

COE:

Cost of Energy (cost paid for purchasing a kilowatt-hour of energy)

C boiler :

The boiler marginal cost (kWh)

H served :

The total thermal load served

Batt e, c :

The battery storage cost

C cc, i :

The cost of cycle charging the battery in time step i ($)

E cc, i :

The amount of energy that went into the battery bank in time step i (kWh)

MCDM:

Multi-criteria decision-making

x ij :

The performance of alternative i for criterion j.

m ij :

Correlation matrix

W j  :

Criteria weight

C j  :

Criterion j information

PDA:

Positive distance from average

NDA:

Negative distance from average

AV:

Average solution of criterion

AS:

Appraisal Score

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Acknowledgements

The First Author acknowledges the support received from the African-German Network of Excellence in Science (AGNES), the Federal Ministry of Education and Research (BMBF) and the Alexander von Humboldt Foundation (AvH). Opinions expressed and conclusions arrived at, are those of the authors and are not necessarily to be attributed to AGNES, BMBF and AvH.

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Authors and Affiliations

  1. Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa

    Olubayo Babatunde

  2. Department of Electrical and Electronics Engineering, University of Lagos, Lagos, Nigeria

    Olubayo Babatunde, Iheanacho Denwigwe & Adaeze Ohiaeri

  3. Royal HaskoningDHV, Woodmead, Johannesburg, 2191, South Africa

    Oluwaseun Oyebode

  4. Department of Mechanical and Biomedical Engineering, Bells University of Technology, Ota, Nigeria

    Desmond Ighravwe

  5. Department of Chemical Engineering, Covenant University, Ota, Nigeria

    Damilola Babatunde

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  1. Olubayo Babatunde
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  2. Iheanacho Denwigwe
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  3. Oluwaseun Oyebode
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  4. Desmond Ighravwe
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  5. Adaeze Ohiaeri
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Contributions

Olubayo Babatunde conceived the study and wrote part of the manuscript. Iheanacho Denwigwe wrote part of the manuscript. Oluwaseun Oyebode, Desmond Ighravwe, and Damilola Babatunde wrote part of the manuscript and read the revised manuscript and Adaeze Ohiaeri participated in data collection. All authors participated in the preparation of the final manuscript.

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Correspondence to Olubayo Babatunde.

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Highlights

• Modeling and sizing of feasible hybrid renewable energy systems for an administrative building in an academic environment is performed based on single criterion (economic).

• Eight energy systems (ES1-ES8) were obtained as feasible for powering the building

• CRITIC-EDAS is applied to rank and select the optimal systems (ES1-ES8) based on multiple criteria

• The ranking of the first two systems (ES1 and ES2) returned by single criterion total NPC remained the same while changes were observed in the ranks of the remaining systems (ES3 – ES8).

• Hybrid PV-DG-battery energy system (ES1) is ranked the best system when single criterion and multiple criteria were considered separately

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Babatunde, O., Denwigwe, I., Oyebode, O. et al. Assessing the use of hybrid renewable energy system with battery storage for power generation in a University in Nigeria. Environ Sci Pollut Res 29, 4291–4310 (2022). https://doi.org/10.1007/s11356-021-15151-3

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