Integrated supply–demand energy management for optimal design of off-grid hybrid renewable energy systems for residential electrification in arid climates
| Autor: | Mohamad Ramadan, Noureddine Settou, Abdessalem Bouferrouk, Belkhir Negrou, Charafeddine Mokhtara, Yufeng Yao |
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| Rok vydání: | 2020 |
| Předmět: |
Optimal design
Engineering Modelling and Simulation Research Group Renewable Energy Sustainability and the Environment Computer science Energy management 020209 energy Building energy consu Energy Engineering and Power Technology 02 engineering and technology Energy consumption Hybrid renewable energy system Grid Net present value Reliability engineering Fuel Technology Electrification 020401 chemical engineering Nuclear Energy and Engineering 0202 electrical engineering electronic engineering information engineering Fuel efficiency Diesel generator Rural electrification 0204 chemical engineering |
| Zdroj: | Energy Conversion and Management. 221:113192 |
| ISSN: | 0196-8904 |
| DOI: | 10.1016/j.enconman.2020.113192 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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