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Optimal design and sensitivity analysis of the stand-alone hybrid energy system with PV and biomass-CHP for remote villages

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  • Ji, Ling
  • Liang, Xiaolin
  • Xie, Yulei
  • Huang, Guohe
  • Wang, Bing

Abstract

Reliable access to electricity is still a serious problem for remote villages, however, abundant solar radiation and biomass have the potentials to provide energy supply in a sustainable way. This paper focuses on the optimal design and techno-economic analysis of the stand-alone hybrid energy system for a typical rural village in the northwest of China. Based on the estimation of local renewable energy potential and the investigation of heat and power consumption patterns, a mixed-integer linear programming optimization model is presented with the aim of minimum total annualized cost. The techno-economic analysis of different system configurations is conducted and compared. Particularly, the levelized cost of energy production and levelized cost of energy consumption is proposed to evaluate the economic-cost of energy from both supply and demand-side respectively. Furthermore, sensitivity analysis and scenario analysis is conducted to demonstrate the influences of the variations and uncertain environmental policy on total system cost and performance. The results demonstrate that the PV/biomass-CHP/diesel generator/gas boiler/battery/thermal energy storage hybrid energy system is the most economical option with a total annualized cost of 652 × 103 $. The levelized cost of energy consumption (0.355 $/kWh) is greater than that of energy production (0.275 $/kWh), implying a great potential for local electrification and more flexible heat/power output equipment.

Suggested Citation

  • Ji, Ling & Liang, Xiaolin & Xie, Yulei & Huang, Guohe & Wang, Bing, 2021. "Optimal design and sensitivity analysis of the stand-alone hybrid energy system with PV and biomass-CHP for remote villages," Energy, Elsevier, vol. 225(C).
  • Handle: RePEc:eee:energy:v:225:y:2021:i:c:s0360544221005727
    DOI: 10.1016/j.energy.2021.120323
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