Integrated supply–demand energy management for optimal design of off-grid hybrid renewable energy systems for residential electrification in arid climates - Mokhtara, Charafeddine; Negrou, Belkhir; Bouferrouk, Abdessalem; Yao, Yufeng; Settou, Noureddine; Ramadan, Mohamad (Energy conversion and management, 2020)
[Display omitted] •An optimal design of an off-grid hybrid renewable energy system (HRES) is suggested.•Techno-economic feasibility study of the hybrid PV-wind-battery-diesel energy system.•The effects of demand-side management on the energy demand–supply is investigated.•Test the impact of battery technology on the design of HRES through a sensitivity analysis.•Comparison between particle swarm optimization and HOMER software is made. The growing research interest in hybrid renewable energy systems (HRESs) has been regarded as a natural and yet critical response to address the challenge of rural electrification. Based on a Bibliometric analysis performed by authors, it was concluded that most studies simply adopted supply-side management techniques to perform the design optimization of such a renewable energy system. To further advance those studies, this paper presents a novel approach by integrating demand–supply management (DSM) with particle swarm optimization and applying it to optimally design an off-grid hybrid PV-solar-diesel-battery system for the electrification of residential buildings in arid environments, using a typical dwelling in Adrar, Algeria, as a case study. The proposed HRES is first modelled by an in-house MATLAB code based on a multi-agent system concept and then optimized by minimizing the total net present cost (TNPC), subject to reliability level and renewable energy penetration. After validation against the HOMER software, further techno-economic analyses including sensitivity study are undertaken, considering different battery technologies. By integrating the proposed DSM, the results have shown the following improvements: with RF = 100%, the energy demand and TNPC are reduced by 7% and 18%, respectively, compared to the case of using solely supply-side management. It is found that PV-Li-ion represents the best configuration, with TNPC of $23,427 and cost of energy (COE) of 0.23 $/kWh. However, with lower RF values, the following reductions are achieved: energy consumption (19%) and fuel consumption or CO2 emission (57%), respectively. In contrast, the RF is raised from 15% (without DSM) to 63% (with DSM). It is clear that the optimal configuration consists of wind-diesel, with COE of 0.21 $/kWh, smaller than that obtained with a stand-alone diesel generator system. The outcomes of this work can provide valuable insights into the successful design and deployment of HRES in Algeria and surrounding regions.