DEMAND-SIDE MANAGEMENT IN POWER DISTRIBUTION SYSTEM

Abstract

In the age of new smart technology, the traditional power system is becoming smarter and smarter for dynamic energy management. In this perspective, involving the participation of end-use energy consumers, Demand-Side Management (DSM) is an innovative concept for a power distribution system. The main aim of this thesis is to develop robust, multi-functional coordinated, and integrated algorithms, identifying demand-side resources for home and building energy management to reduce energy consumption and electricity bills. The research work is divided into three major parts: 1) identifying suitable models and methods for optimization, 2) a set of case studies for Home Energy Management (HEM), and 3) 3-House and 100-House case studies for Building Energy Management (BEM). In this thesis, initially, the basic principles of demand-side management are explained. This work adopts a scenario-based approach. This approach identifies energy efficient and feasible models for schedulable and non-schedulable electric devices. Moreover, this thesis considers the behaviors and actions of energy consumers, policies, and intelligent computational techniques adaptable to a smart grid. This research considers models of Heating Ventilating and Air Conditioning (HVAC) systems, Electric Water Heater (EWH), Electric Water Pumps (EWP), Uninterrupted Power Supply (UPS) systems, Plug-in Hybrid Electric Vehicle (PHEV), and rooftop solar Photo-Voltaic (PV) systems. This thesis work builds optimal coordination and integration through the development of simulation models in 15- Minute timeslots under a Real-Time Price (RTP) based demand response policy for assessing various effects of incorporation and contribution of each resource for optimal scheduling. This work considers the influence of each resource such as temperature sensitiveness, charging-discharging, price, PV-generation, utility supply situations, temperature settings, lifestyle factors, users’ behavior for minimizing energy consumption, and operational cost of a distribution system. This thesis provides the usage of energy in appropriate quantity and best quality for every universal and absolute need of consumers in different situations as well as in curtailment duration, incorporating Distributed Energy Resources (DERs). This work develops computational modeling tools optimization of various available resources in different time slots for energy management. This research develops the simulation models of a normal ON-OFF and optimum scheduling of devices. The study results and i analysis are compared based on ON-OFF and smart optimization-based simulation models. The thesis discuss the comprehensive framework with bottom-up decision-making study in technological, economical, and environmental conditions to manage energy in a power distribution system. The proposed work influences home and building energy consumers towards efficient and smart use of available energy resources in a power distribution system. In this thesis, DSM strategies such as load reduction, peak clipping, valley fillings, load shifting, and flexible load shape are applied by developing different algorithms according to situations and available resources for HEM. This study ensures the energy supply for household loads during curtailment. This research work develops four case studies. The purpose of this study is to assist with the impact of different situations considered in the case studies. The research methodology and simulation provide a comparative performance in dynamic energy demand and supply under demand response and distributed energy resources for home energy management in a power distribution system. The research shows the implementation of DSM strategies for a house significantly reduces 31.79 % consumption and 37.30 % cost in different situations over a day without violating the consumer set of comfort preferences. The research further expands the scope to consider building energy management in different situations. This study develops an algorithm for scheduling DSR for BEM under consumer satisfaction constraints. This algorithm is simple and can be applied to medium or large buildings. In this research, electric water pumps and electric water heaters are considered common devices in a building. These are the major energy-consuming devices and they provide flexibility to obtain an optimized schedule with other devices at all the houses in a building. In this research, an efficient building energy management system is proposed, which takes into account the load priorities and preferences of the comfortable settings of the consumers. The limits imposed on the net demand consumption make the algorithm shift the load from system peak to off-peak periods. The consumers individually decide their load priorities and their privacy. The results and discussion presented in this thesis show that the proposed models, framework, and methodology have a great energy-saving potential and flexible incorporation capacity with energy storage, distributed generations, consumer behaviors, and modern energy policies in a power distribution system for home and building energy management in the smart grid environment.