Integrated optimization of energy costs and occupants’ productivity in commercial buildings: Fid-Bau Portal

Integrated optimization of energy costs and occupants’ productivity in commercial buildings

Mofidi, Farhad / Akbari, Hashem

Highlights • Proposing a method for intelligent energy and comfort management. • Providing situation-specific economic optimum indoor conditions, based on the combination of thermal comfort, indoor air quality and energy costs. • Significantly improving occupants productivity in commercial buildings, while reaching energy savings objectives. • Studying benefits of personalized energy and comfort management.

Abstract Indoor Environment Quality (IEQ) of an office has significant effects on the performance and productivity of its occupants. There are several factors that have positive or negative impacts on occupants’ overall satisfaction, including the level of thermal comfort, visual comfort, aural comfort and Indoor Air Quality (IAQ). While keeping energy savings objectives, energy management system can provide acceptable thermal comfort, visual comfort, and IAQ levels, by taking energy-related decisions. Several inputs that are changing continuously, such as energy prices, sets of indoor and outdoor environment parameters, occupants’ presence, activities and preferences are required for timely energy-related decision-making. Therefore, there is a need for a well-structured method to reach optimum decisions for energy costs and occupants’ IEQ. The main interest of this research is to propose a Multi-Objective Optimization (MOOP) method for energy and comfort management in commercial buildings. The proposed method is capable of providing situation-specific economic optimum indoor conditions, based on the combination of thermal comfort, IAQ, and energy costs, as well as energy prices, occupancy information and types of occupants’ activities. Operation of the proposed method is analyzed by annual energy performance simulation of a commercial building in Montreal, Canada. Based on provided results, the proposed MOOP method is capable of improving productivity of occupants, by up to $1000 per year per person, while reaching energy savings objectives. It is observed that potential for productivity improvement is higher during the swing and warm seasons, compared to the cold season. Having ability of flexible decision-making, the proposed MOOP method is suitable for Intelligent Energy Management Systems (IEMSs), with objectives of maximizing energy costs and comfort conditions.