Energy management and optimization in smart grid

Name: Prum, Puthisovathat

keyword: Smart home

; Battery energy storage system

; Photovoltaic

; Electric vehicle

; Optimization

; Home energy management

Abstract: Advancements in technology, infrastructure, and global development have spurred a notable surge in energy consumption worldwide. Recent attention has been particularly directed toward residential areas, known for their substantial energy consumption. To address this, a Demand Side Management (DSM) system has been proposed as a solution. It involves the scheduling of household appliances, the integration of Renewable Energy Sources (RESs), and the incorporation of Battery Energy Storage Systems (BESS). However, these measures alone may not fully optimize the economic and environmental aspects. Another significant challenge lies in the growing prevalence of Electric Vehicles (EVs) and their potential to contribute to power management. Integrating EVs into existing Home Energy Management (HEM) systems within the Smart Grid (SG) presents an exciting avenue for future research. This thesis study introduces a unique HEM design that accommodates BESS, RESs, and EVs. A Mixed-Integer Linear Programming (MILP) approach is employed to minimize electricity costs. The optimization model factors in Real-Time Pricing (RTP) tariffs and delivers efficient scheduling of appliances, as well as optimal BESS and EV charging and discharging patterns. The simulation encompasses various scenarios, including individual and multiple Smart Home (SH), accounting for diverse user preferences, user consumption patterns, and EV driving activities. Both case studies showcase noteworthy reductions in electricity costs compared to a traditional SH scenario lacking PV, BESS, and EV integration. In the case of multiple SHs, a remarkable cost reduction of 46.38% is achieved compared to a traditional SH scenario. Moreover, the multiple SHs scenario as a centralized architecture shows a better result in total electricity cost reduction than the individual SH scenario in a distributed architecture, which is by 10.67% for all three SHs in the simulation and it ensures fairness in using a central BESS and PV for all users involved in the system.

Thammasat University. Thammasat University Library

Address: BANGKOK

Email: preserv@tu.ac.th

Name: Chalie Charoenlarpnopparut

Role: advisor

Created: 2024

Modified: 2568-05-15

Issued: 2025-04-21

วิทยานิพนธ์/Thesis

application/pdf

DOI: 10.14457/TU.the.2024.93

eng

DegreeName: Master of Science

Level: Master's Degree

Descipline: Engineering and Technology

Grantor: Thammasat University

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