Abstract

Recently, a worldwide movement to reduce greenhouse gas emissions has emerged, and includes efforts such as the Paris Agreement in 2015. To reduce greenhouse gas emissions, it is important to reduce unnecessary energy consumption or use environmentally-friendly energy sources and consumer products. Many studies have been performed on building energy management systems and energy storage systems (ESSs), which are aimed at efficient energy management. Herein, a heating, ventilation, and air-conditioning (HVAC) system peak load reduction algorithm and an ESS peak load reduction algorithm are proposed. First, an HVAC system accounts for the largest portion of building energy consumption. An HVAC system operates by considering the time-of-use price. However, because the indoor temperature is constantly changing with time, load shifting can be expected only immediately prior to use. Therefore, the primary objective is to reduce the operating time by changing the indoor temperature constraint at the forecasted peak time. Next, numerous research initiatives on ESSs are ongoing. In this study, we aim to systematically design the peak load reduction algorithm of ESS. The structure is designed such that the algorithm can be applied by distinguishing between the peak and non-peak days. Finally, the optimization scheduling simulation is performed. The result shows that the electricity price is minimized by peak load reduction and electricity usage reduction. The proposed algorithm is verified through MATLAB simulations.

Highlights

  • Over the past 40 years, the global consumption of primary energy has increased by approximately2.4 times

  • We study the peak load reduction algorithm with the two systems above

  • Our simulation is performed by modeling a real building and HVAC system using MATLAB

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Summary

Introduction

Over the past 40 years, the global consumption of primary energy has increased by approximately. The HVAC system can control the set temperature; if it is controlled according to the electricity price and outdoor temperature by time, it has the potential to reduce the power consumption or peak load [2]. Another method to efficiently utilize the energy that is being used is via an energy storage system (ESS). In the first of the two energy management strategies, the HVAC system schedules an uptime to reduce the day’s peak load This does not stop the system at the peak time, but aims to maintain the proper indoor temperature considering user convenience.

Thermal Model and User Convenience in HVAC System
Simulation of HVAC System Optimization Algorithm of HV
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Summary of Case
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August 2017
The results demonstrate that the charges from
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