Investigating the probability of designing net-zero energy buildings with consideration of electric vehicles and renewable energy

Abstract

PurposeDue to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.Design/methodology/approachFirst, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.FindingsThe results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.Originality/valueConsidering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

Are Commercial EV Chargers Ready to Aid with Household Power Consumption?

“…EVs have gained a lot of attention in recent years as a solution to this problem and they are becoming increasingly popular due to their environmental and economic benefits. The government's tax incentives and lower fuel costs per mile are the main driving forces for growing the number of EVs on the road [1][2][3]. In just three years, the number of EVs on the road tripled to over 16.5 million in 2021.…”

“…It can theoretically be utilized to meet nearly zero energy building (NZEB) goals by merging EV and renewable energy sources (RES), e.g., solar, wind, or biomass. An NZEB, according to the US Department of Energy, is an energy-efficient building that meets its energy requirements by its own energy generation [3]. According to authors of [7], the PV and V2H combination can fully meet the energy demand of a household on sunny and cloudy days without the need for grid power purchase.…”

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

“…However, these optimization methods cannot adapt to the environment's stochastic nature, including unpredictable driving patterns, load profiles, and pricing. The global search technique, that uses genetic algorithms [16] and swarm intelligence [17] to resolve power management issues, is another model-based optimization strategy. However, the application of these methods in real-time systems is limited due to extensive computations, which makes them slow.…”