Optimization of Net-Zero Energy Solar Communities: Effect of Uncertainty due to Occupant Factors
Abstract
This paper presents an optimization methodology for a net-zero energy (NZE) community which accounts for the impact of energy-related behaviour on the net-energy consumption and peak electrical loads of a community. A NZE community is defined as a community which generates as much on-site renewable energy as it consumes over a year. Variability in end-user energy consumption, which depends on the number of occupants per home, financial situation, age, and other factors, is an important aspect to take into account in a community energy system simulation model. Despite the difficulty of accounting for user behaviour, passive and active solar strategies can aid in mitigating its impact by reducing the electricity demand from the grid. Thus, there is a need to estimate the impact of energy-related behaviour on a community of NZE homes. In this study, the effects of three types of occupant behaviour were considered: i) variations in heating set points, ii) variations in cooling set points, and iii) electricity consumption for lighting, domestic hot-water (DHW), appliance usage and their corresponding internal gains. Since the end- user electrical demand can only be estimated, this investigation used consumption profiles derived from Canadian national statistics of energy use in households [1]. Profiles were based on percentages of national energy consumption and were scheduled using normal distributions during occupied hours. It was assumed that a home with high appliance loads would also consume a proportionately large amount of electricity for DHW and lighting. Due to the vast number of possible design combinations, an optimization methodology was used to facilitate the identification of individual building designs used to form the community with constrained orientations and footprint areas. An optimization approach ensures that energy conservation measures have been fully exploited prior to sizing building integrated energy generation using photovoltaics (PV) on the near-south facing roof surface. The impact of variable user behaviour was conducted on these pre-optimized home designs. For this paper, it was assumed that community sizes had equal ratios of all orientations ranging from -45 to 45 degrees of due south. Such orientations were selected to allow for acceptable passive solar performance and to consider communities in variable configurations. Diversifying building orientations has the notable property of reducing peak loads in communities [2, 3]. It is understood that an all south-facing community would have higher PV generation due to energy generation limited to roof-top area only. The optimization methodology used in this study consists of a hybrid algorithm, a deterministic- evolutionary approach [4]. The objective of the optimization search is to maximize the amount of