A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Optimal sizing of a residential PV-battery backup for an intermittent primary energy source under realistic constraints
Highlights A PV-battery backup for an intermittent grid supplying a high load demand is sized. The GA and PSO are used to solve the sizing optimization under realistic conditions. Neglecting the technical constraints and standards will induce misleading results. Detailed comparison of the proposed PV based backup with diesel generators solution. The system is fit for the case study especially when coupled with a load management.
Abstract This paper addresses the issue of an intermittent primary energy source in several developing countries. A PV-battery backup system is modeled and assessed as a replacement of the utility energy during daily power outage periods in a residential house. This paper focuses on the sizing of the PV system. The main objective is the minimization of the overall cost of the system over a 20 year period. One prime innovation in this study is that this system operates in conjunction with the grid, allowing it to charge the battery bank along with the PV panels whenever needed. Therefore, the optimization procedure takes into account more severe conditions compared to a classic standalone PV-battery system. The optimization is conducted based on real weather data, realistic residential load profiles and power outage schedules. Technical constraints are integrated in the algorithm. Two robust optimization techniques are used for comparison and validation purposes: the Genetic Algorithm and the Particle Swarm Optimization. In addition, two different situations are considered: harsh and moderate conditions. The simulation results validate the feasibility of this installation, and prove that such systems are affordable and well suited for the studied case.
Optimal sizing of a residential PV-battery backup for an intermittent primary energy source under realistic constraints
Highlights A PV-battery backup for an intermittent grid supplying a high load demand is sized. The GA and PSO are used to solve the sizing optimization under realistic conditions. Neglecting the technical constraints and standards will induce misleading results. Detailed comparison of the proposed PV based backup with diesel generators solution. The system is fit for the case study especially when coupled with a load management.
Abstract This paper addresses the issue of an intermittent primary energy source in several developing countries. A PV-battery backup system is modeled and assessed as a replacement of the utility energy during daily power outage periods in a residential house. This paper focuses on the sizing of the PV system. The main objective is the minimization of the overall cost of the system over a 20 year period. One prime innovation in this study is that this system operates in conjunction with the grid, allowing it to charge the battery bank along with the PV panels whenever needed. Therefore, the optimization procedure takes into account more severe conditions compared to a classic standalone PV-battery system. The optimization is conducted based on real weather data, realistic residential load profiles and power outage schedules. Technical constraints are integrated in the algorithm. Two robust optimization techniques are used for comparison and validation purposes: the Genetic Algorithm and the Particle Swarm Optimization. In addition, two different situations are considered: harsh and moderate conditions. The simulation results validate the feasibility of this installation, and prove that such systems are affordable and well suited for the studied case.
Optimal sizing of a residential PV-battery backup for an intermittent primary energy source under realistic constraints
Khoury, J. (author) / Mbayed, R. (author) / Salloum, G. (author) / Monmasson, E. (author)
Energy and Buildings ; 105 ; 206-216
2015-07-18
11 pages
Article (Journal)
Electronic Resource
English