Building Energy Management through a Distributed Fuzzy Inference System

Buildings consume significant world's energy resources, approximately 32% of the total primary energy. The rapid depletion of energy resources, has imparted researchers to focus on energy conservation and wastage. The next generation of smart buildings is becoming a trend to cope with the needs of energy and environmental ease in buildings. This advances the intelligent control of building to fulfill the occupants' need. Intelligent system control for sustainable buildings is dynamic and highly complex. Building information accuracy with an effective controller scheme is a challenging task. This paper presents the fuzzy control system architecture (FCSA) for resolving the conflict of maintaining the inhabitants comfort index and the energy consumption in buildings. It also infers the graphical relationship between energy consumption and comfort parameters. With a distributed fuzzy inference system (FIS), control has been developed for temperature, air quality and artificial lighting comfort parameters. Model simulation has been carried out and control factors have been discussed. The FIS models have also been validated with implication of change function. The presented control system is capable of achieving energy conservation in the buildings. Keyword-Fuzzy control, Energy management, Comfort management, Energy consumption, Sustainable buildings I. INTRODUCTION The alarming environmental threats and the depletion of fossil resources have increased the awareness of the need to decrease energy consumption for sustainable energy development (1). Energy efficiency, thus, has become a requirement inside buildings for both climate preservation and economic stability. Around 80-90 % of inhabitants spend their utmost time in buildings (2). Therefore, an occupant's satisfaction is highly dependent on the indoor ambient comfort. The building energy management is primarily concerned in attaining the maximum indoor environment comfort in contrast tp the least energy consumption. Attainment of indoor comfort, keeping in view the consumer's preferences, is an important aspect. This will certainly influence the efficiency of the occupants and ultimately energy consumption. For reduction of power consumption and waste in buildings, an intelligent control system is needed, since energy consumption has been directly related to comfort and ultimately to operational costs. A building's indoor environmental primary comfort factors, according to the consumers' preferences are thermal, visual and indoor air quality (3). Therefore, satisfaction of energy prerequisites in efficient buildings has been focused on by assuring operational requirements with the least possible energy cost and the most environmental protection. An indoor building environment is quite sensitive to variations and will closely follow the change. The non- linear fuzzy linguistic mapping model of an input data set to a scalar output data will overcome this. A FIS contains four basic blocks: fuzzifier, rule sets, inference engine and defuzzifier. The general architecture is shown in Fig. 1. Initially, an input set of crisp data is accumulated and turned into a fuzzy set utilizing fuzzy linguistic variables and membership functions called fuzzification. An inference is developed based on the rule set and finally, the fuzzy output is mapped to crisp values using the membership function called defuzzification (4). The study presents the implementation of fuzzy control system architecture (FCSA) using a fuzzy inference system. The control functions employed for attaining energy conservation and improved level of comfort included thermal, visual and air quality as parameters. In a building envelope, the indoor thermal is the temperature (3), visual means the brightness level and the CO2 concentration represents the air quality; these are regarded to be the main comfort parameters (5). The user's preferences need to be considered in the design of the controller. This research is primarily focused on building towards the inhabitant's comforts and energy efficiency through actuator control.