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Design and feasibility analysis of grid-connected hybrid renewable energy system: perspective of commercial buildings

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Abstract

Green energy technologies have been widely acknowledged as a supplement to conventional power sources due to the finite nature of fossil fuels, ever-increasing load demand and GHG emissions. This paper proposes a HRES that encompasses photovoltaic, electric vehicle, battery system and grid. The viability analysis of the HRES is implemented in this paper by using the load profile of Tucson Mall, U.S. and the meteorological data from the NASA. This study seeks to create a framework for sustainable energy that enhances the performance of the conventional power system by reducing the NPC, payback period, GHG emissions, COE and energy obtained from the grid by using HOMER application. The NPC, COE, payback period and return on investment for the best configuration of the proposed HRES are $1,600,623.00, $0.0420, 4.10 years and 19.0%. The outcomes of the study demonstrate that the most feasible configuration achieved 60.38% of COE and 39.48% of NPC better than case study 1. The optimal HRES has been subjected to a sensitivity analysis to establish the influence of several parameters such as interest rate, load demand, capital cost, inflation rate, solar radiation and temperature on the COE and NPC. The findings of the study demonstrate that the PV system plays an important role in decreasing GHG emissions, NPC and COE as well as achieving the optimal operation of the HRES. The incorporation of green energy technologies into the utility grid can sustainably address the global energy crisis and improve access to electricity. The government agencies can use the findings of this study as a crucial step in increasing the proportion of green energy technology in the global’s energy mix.

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Data availability

The data that support the findings of this study are openly available in repository of NASA at https://power.larc.nasa.gov/data-access-viewer.

Abbreviations

\(A_{batt}\) :

Battery autonomy (h)

\(ACF_{current}\) :

Annual nominal cash flow for the current system

\(ACF_{reference}\) :

Nominal cash flow for reference system

\(ACS_{base\,system,i}\) :

ACS of the base case system

\(ACS_{proposed,i}\) :

ACS of the proposed system

AOMCc;i :

Annualized operation and maintenance cost for each HES component

ARCc;i . :

ARC of each component of HES

AR s C :

Annualized resources cost

\(BA_{day}\) :

Battery system’s days autonomy

BScap :

Capacity of the battery system

\(BS_{s}\) :

Size of the battery system

\(BS^{\max }\) :

Maximum size of battery system

\(BS_{cap}^{\max }\) :

Maximum capacity of the BS (Ah)

\(C_{bw}\) :

Wear cost of the battery system ($/kWh)

Cb mc :

Boiler marginal cost ($/kWh)

\(C_{cap}\) :

Capital cost of the current system

\(C_{cap,\,ref}\) :

Capital cost of the reference system

C CL :

Lifetime of the component (yr)

CC base :

Energy charge of the base power system

CCF in :

Cumulative cash inflow

CCF out :

Cumulative cash outflow

CC proposed :

Energy charge of the proposed power system

\(C_{demand,i}\) :

Grid demand rate for rate i ($/kW/month)

\(C_{NPC,tot}\) :

Total NPC ($)

Crep :

Replacement cost of the component ($)

\(C_{rep,bs}\) :

Replacement cost of the battery system ($)

C s :

Component's salvage value

C temp :

Power temperature coefficient of the panel (%/°C)

\(COE_{grid\,price,\,i}\) :

\(COE_{grid\,price,\,i}\) Is the grid power price for rate i ($/kWh)

\(COE_{grid\,sell\,back,i}\) :

Sellback rate for rate i ($/kWh)

\(CO_{2,Gi\,\,\,(t)}\) :

Carbon dioxide emission obtained from the conventional generating units

\(D_{load}\) :

Load demand

DC ,i :

Demand charge ($)

DC base :

Demand charge of the base power system ($)

DC proposed :

Demand charge of the proposed power system

DOBD max :

Maximum DOBD (%)

\(E_{grid\,purchases,i,j}\) :

Sum of energy purchased from the grid in month j when the time rate i is applied (kWh)

\(E_{grid\,sales,i,j}\) :

Sum of energy sold to the grid in month j when the time rate i is applied (kWh)

\(E_{gs}\) :

Energy sold to the utility grid (kWh/yr)

\(E_{nonren}\) :

Nonrenewable electrical production (kWh/yr)

\(E_{npg,i,j}\) :

Purchases made in month j when rate i is in effect (kWh)

E served :

Total electrical load served (kWh/yr)

\(E_{served,AC}\) :

AC primary load served (kWh/yr)

\(E_{served,DC}\) :

DC primary load served (kWh/yr)

\(E_{served,def}\) :

Deferrable DC load served (kWh/yr)

f :

Annual inflation rate (%)

\(f_{i}\) :

Number of cycles to failure

Energy purchased; i :

Energy purchased in a month i (kWh)

Energysold;i :

Energy sold in the month i (kWh)

FR base :

Fixed rate of the base power system

FR proposed :

Fixed rate of the proposed power system.

\(H_{nonren}\) :

Nonrenewable thermal production (kWh/y)

H served :

Total thermal load served (kWh/yr)

i :

Real interest rate or annual real discount rate

i i :

Nominal interest rate

I nom :

Nominal solar irradiance (W/m2)

investment intial :

Initial investment

I (t) :

Solar irradiance (W/m2)

I r :

REference irradiance

\(k_{ci}\) :

Clearness index

\(Lp,a\) :

Average primary load (kWh/d)

N :

Expected life of the components or lifetime of the project or number of months

n,bss :

Number of battery storage system

n,conv :

Number of converters

n,pv , :

Number of PV panels

\(N_{bs}\) :

Number of battery systems in the storage bank

\(NO_{x,Gi\,\,\,(t)}\) :

Nitrogen oxide emission obtained from the conventional generating units

NCF n :

Net cash flow

NEP kwh :

Net energy purchased (kWh) in a month

\(P_{grid,peak,i,j}\) :

Peak hourly grid demand in month j when the time rate i is applied (kWh)

P i :

Power produced by the conventional generating units of the utility

\(P_{input}\) :

Input of the converter

\(P_{out}\) :

Output of the converter

\(P_{proj}\) :

Project lifetime (yr)

P R :

Total electrical power generated from renewable energy sources (kW)

\(P_{pv} (t)\) :

PV power panel generation at time t (W)

P PV ,nom :

Nominal output power of the PV panel (W)

P T :

Total electrical load served (kW)

\(Q_{lifetime,i}\) :

Lifetime throughput (kWh)

\(Q_{nom}^{bs}\) :

Nominal capacity of a single battery system (Ah)

\(Q_{tp}\) :

Annual battery system throughput (kWh/yr)

R av :

Monthly average radiation (kWh/m2/day)

\(R_{bs}\) :

Battery bank life (yr)

\(R_{bs,f}\) :

Battery system float life (yr)

R RL :

The component's remaining life at the end of the project's lifespan

Ro,av:

Extra-terrestrial horizontal radiation (k (Wh/m2/day)

Rt :

Net balance of the year (t)

\(R_{proj}\) :

Lifetime of the project (years)

\(SOC^{\max }\) :

Maximum SOC of the BS (%)

\(SOC^{\min }\) :

Minimum SOC of the BS (%)

\(SO_{2,Gi\,\,\,(t)}\) :

Suphur dioxide emission obtained from the conventional generating units

T a :

AMbient temperature (°C)

T c :

Tc Is the cell temperature of the PV module (°C)

T (t) :

PV cell temperature of the panel at time t (°C)

\(V_{n}\) :

Battery system's nominal voltage (V)

\(\eta_{BSr}\) :

Round-trip efficiency of the battery system (fractional)

\(\eta_{inv}\) :

Conversion efficiency of inverter

η PV :

PV derating factor (%)

\(\eta_{trip}\) :

Round trip of efficiency of the BS

\(\eta_{inv}\) :

Conversion efficiency of inverter

A:

Is Annual worth

AC:

Annualized cost or Alternating current

ACC:

Annualized capital cost of the system

ACS:

Annualized cost of the system

AOMC:

Annualized operation and maintenance cost

APP:

Annual power production

ARC:

Annualized replacement cost

AS:

Annualized cost savings

AUB:

Annual utility bill

BS:

Battery system

BSS:

Battery storage system

BTS:

Base transceiver station

CC:

Capital cost of each component of the HRES

COE:

Cost of energy

COH:

Cost of hydrogen

CRF:

Capital recovery factor

DC:

Direct current

DF:

Duty Factor

DG:

Diesel generator

DOBD :

Depth of the battery discharge (%)

EC:

Energy charge ($)

F:

Future worth

FC:

Fuel cells

FR:

Fixed rate

GHI:

Global horizontal irradiance

ENS:

Energy not supply

EMERAL:

Energy modeling and energy resources assessment Lab.

EV:

Electric vehicle

GA:

Genetic algorithm

GETs:

Green energy technologies

GHG:

Greenhouse gas

GHI:

Global horizontal irradiance

GSM:

Global system for mobile communication

GWO:

Grey wolf optimizer

HES:

Hybrid energy system

HRES:

Hybrid renewable energy system

HOMER:

Hybrid optimization of multiple energy sources

IRR:

Internal rate of return

LCE:

Life cycle emissions

LEV:

Low emission vehicle

LPSP:

Loss of power supply probability

MBA:

Modified Bat Algorithm

MGT:

Micro gas turbine

MILP:

Mixed integer linear programming

MOPSO:

Multi-objective particle swarm optimization

MOSaDE:

Multi-objective self-adaptive differential evolution

N:

Total number of time periods

NASA:

National Aeronautics and Space Administration

NOCT:

Normal cell temperature (oC)

NPC:

Net present cost

NPV:

Net present value

OC:

Operation cost

O&M:

Operation and maintenance

RF:

Renewable friction

RP :

Renewable penetration

P:

Base case

PSO:

Particle swarm optimization

PV:

Photovoltaic

ROI:

Return on investment

SOC:

State of charge

VRE:

Variable renewable electricity

WHO:

Wild horse optimizer

WT:

Wind turbine

ZEVs:

Zero-emission of vehicles

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Federal University Oye Ekiti, Oye Ekiti, Ekiti State, Nigeria

    T. Adefarati

  2. Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, 19716, USA

    G. D. Obikoya

  3. Department of Electrical Engineering and Technology, University of Johannesburg, Johannesburg, South Africa

    G. Sharma

  4. Department of Electrical Power Engineering, Durban University of Technology, Durban, South Africa

    A. K. Onaolapo & K. T. Akindeji

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  1. T. Adefarati
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  2. G. D. Obikoya
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  3. G. Sharma
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  4. A. K. Onaolapo
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  5. K. T. Akindeji
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Appendix

Appendix

Appendix A Utility monthly summary for case study 1
Full size table
Appendix B Utility monthly summary for case study 2
Full size table
Appendix C Utility monthly summary for case study 3
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Adefarati, T., Obikoya, G.D., Sharma, G. et al. Design and feasibility analysis of grid-connected hybrid renewable energy system: perspective of commercial buildings. Energy Syst 15, 403–462 (2024). https://doi.org/10.1007/s12667-023-00578-z

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