Enhanced Sizing Methodology for Renewable Sources and Battery System in a Nearly Zero Energy Building

Abstract

This work aims to offer a new approach to determining the optimal amount of energy stored in batteries and other RES systems (BSS) for transforming a traditional residential building into a nearly-Zergy-Energy-structure (nZEB). This is accomplished by taking the building's location's weather history into account, as well as the efficiency of the building's appliances and mechanism for managing energy use. All of the above are parts of a cost function that takes into account the factors that have a major impact regarding the size and longevity of the RES and BSS in a nZEB. Some of these factors include the rate of feed-in and self-consumption, the influence of discharge power and measure of depth-of-discharge on the state-of-health (SoH) of the BSS, the rate of wear and tear on the original expenditure, and the simultaneous generation and consumption of energy. Thus, taking into account both the economic and efficacy aspects allows when it comes to the best RES and BSS sizes to be reached. Installing solar panels, making batteries, and buying power from the grid all work together to reduce the previously mentioned cost function. To make the model more adaptable on behalf of the building's desire to pay for environmental damages, we've introduced an adjustable parameter. For this, the genetic algorithm method is employed. A pilot nZEB has confirmed the practicality, ease of use, and efficacy of the suggested method.