Implementing single- and multi-year sensitivity analyses to propose several feasible solutions for meeting the electricity demand in large-scale tourism sectors applying renewable systems

Abstract

The tourism sectors consume a high amount of electrical power, which in most cases is supplied by the electrical grid and diesel generator. As a result, the electricity supply of large-scale tourism sectors is an important challenge in many countries. In current study, the feasibility study for applying the hybrid renewable energy systems to provide the power demand in social areas is investigated. Since Iran has a lot of tourism areas with a high amount of electricity consumption, a popular and crowded tourism sector in the Qom (a city in the center of Iran) is selected as the case study. The electricity consumption of this social area is found to be 23,808.91 kWh/day, which in the current system is supplied by the electricity grid. Also, the values of cost of energy and carbon dioxide emissions of current system are calculated to be 0.0931$/kWh and 5,741,214 kg/year, respectively. Regarding the available renewable resources of Qom city and the space limitations of this tourism sector, several combined renewable scenarios are simulated and assessed applying the HOMER Pro simulator. In continue, to identify the optimal scenarios, the techno–economic–environmental evaluation is implemented. The hybrid photovoltaic (PV)/wind turbine (WT)/battery (Bat)/diesel generator (DG)/biogas generator (BG), and grid/PV/WT are found as the optimum configurations for the off-grid and grid-connected systems, respectively. It was found that the Grid/PV/WT has a net present cost of 6.63 M$ and a cost of energy of 0.0234 $/kWh. Also, the cost of energy and net present cost of hybrid PV/WT/Bat/DG/BG are accounted for 0.1251$/kWh and 18.1 M$, respectively. By using this stand-alone system instead of current system, the CO2 emissions reduce by 61.87% (2,189,231 kg/year). In following, to assess the effects of load growth and PV degradation on system performance, the multi-year module of this software is employed. Based on the obtained findings, by applying the hybrid PV/WT/Bat/DG/BG instead of the current system, the contribution of emissions penalties to the overall net present cost diminishes from 15.47% to 0.73%. Finally, the heat map sensitivity analyses are applied to the economic and environmental parameters.

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Abbreviations

COE:

Cost of Energy ($/kWh)

COD:

Chemical Oxygen Demand

NPC:

Net Present Cost ($)

SS:

Suspended Solid (kg/person/year)

O&M:

Operating and Maintenance

OC:

Operating Cost ($)

RF:

Renewable Fraction (%)

CRF:

Capital Recovery Factor (%)

NOCT:

Nominal Operating Cell Temperature (°C)

WT:

Wind Turbine

DG:

Diesel Generator

BG:

Biogas Generator

CO2 :

Carbon Dioxide

CO:

Carbon Monoxide

UHC:

Unburned Hydrocarbons

PM:

Particulate Matter

SO2 :

Sulfur Dioxide

NOX :

Nitrogen Oxides

α:

Solar absorptance of the PV array (%)

τ:

Solar transmittance of the cover over PV array (%)

µ :

Temperature coefficient (–)

C ann . to t :

Total annualized cost ($)

E ann . tot :

Served energy in a year (kWh)

C ann . capital :

Total capital cost of components ($)

Tp:

Lifetime of project (year)

f :

Annual inflation rate (%)

n:

Number of year (–)

Pw:

Output power of wind turbine (kW)

i:

Annual real interest rate (%)

i´:

Nominal interest rate (%)

V:

Wind speed (m/s)

Vcutin :

Cut-in wind velocity (m/s)

Vrated :

Rated wind velocity (m/s)

Vcutoff :

Cutoff wind (m/s)

Prated :

Rated power of wind turbine (kW)

PPV :

PV panel capacity (kW)

Y PV :

Rated capacity of PV (kW)

fPV :

Derating factor (%)

G T :

Solar irradiation incident (kW/m2)

GT.STC:

Solar irradiation at the standard test conditions (kW/m2)

Tc :

PV module temperature at the operating conditions (°C)

Tc.STC:

PV cell temperature under standard conditions (298 K)

P R :

Rated power of diesel generator (kW)

I max :

Battery’s maximum charging current (A)

Vbatt :

Voltage of single battery (V)

Nbatt :

Number of batteries

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Correspondence to Mohammad Hossein Jahangir.

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Jahangir, M., Mousavi, S. & Asayesh Zarchi, R. Implementing single- and multi-year sensitivity analyses to propose several feasible solutions for meeting the electricity demand in large-scale tourism sectors applying renewable systems. Environ Dev Sustain (2021). https://doi.org/10.1007/s10668-021-01254-x

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Keywords

  • Techno-economic analysis
  • Environmental analysis
  • Feasibility study
  • CO2 emissions
  • Hybrid energy system
  • Cost of energy
  • PV degradation