Abstract
The energy allocation at the building level is a complex decision making process. To cope with the uncertainties introduced by the user behavior, new energy-intensive technologies, and renewable energy sources, a real-time adaptation of the building energy management system is required. This paper presents a benchmark of energy resource optimization system for smart buildings, and examines different solution approaches, such as MiniMax Algorithm (MM), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Quantum Particle Swarm Optimization (Q-PSO). These mathematical and heuristic optimization techniques are all able to find the optimal tradeoff between various resources and demands in the system. The proposed method and solution algorithms were tested on a simulated office building, which is powered by two sources of energy, one conventional, and one renewable, i.e. rooftop photovoltaics.
Original language | English |
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Title of host publication | 2015 IEEE Eindhoven PowerTech, PowerTech |
Publisher | IEEE |
ISBN (Electronic) | 9781479976935 |
DOIs | |
Publication status | Published - 31 Aug 2015 |
Externally published | Yes |
Event | IEEE Eindhoven PowerTech, PowerTech 2015 - Eindhoven, Netherlands Duration: 29 Jun 2015 → 2 Jul 2015 |
Conference
Conference | IEEE Eindhoven PowerTech, PowerTech 2015 |
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Country/Territory | Netherlands |
City | Eindhoven |
Period | 29/06/15 → 2/07/15 |
Keywords
- Particle Swarm Optimization
- Genetic Algorithm
- Resource allocation
- Building Energy Management System