Abstract

The fast emerging smart grid technology provides greater information flow, flexibility and control to both electricity consumers and electricity suppliers. Of these benefits, the two way flow of information between consumer and electricity producer in smart grid opened new vistas of applications. Smart home appliances are connected to home area network (HAN) to co-ordinate power usage demanded for the home under control. We are, therefore, witnessing an increasing interest in smart homes from the point of view of optimal energy management, renewable green energy sources and smart appliances. Hence, the problem of scheduling of smart appliances operations in a given time range with set of energy sources like national grid and local generation micro-grid is investigated in this thesis. Renewable energy source that is adopted in this thesis is a photovoltaic panel as a power producing appliance. Appliance operation is modeled in terms of un-interruptible sequence phases, given in load demand profile with a goal of minimizing electricity cost fulfilling duration, energy requirement, and user preference constraints. An optimization algorithm which can provide a schedule plan for smart home appliances usage is proposed based on the mixed integer linear programming technique. The effect of adding a photovoltaic system in the home results in reduction of electricity bill and the peak demand of the home and export of energy to the national grid in times when solar energy production is more than the demand of the home. The situation is modeled using Matlab with Yalmip library to exploit the state-of-the-art Gurobi solver for obtaining the timing of appliance scheduling in the smart home in comparable time to be true as real time process for demand side management.

Highlights

  • As per the Ontario government’s Green Energy Green Economy Act (GEGEA), conserving energy saves money for the consumers and businesses and lowers the demand on the electricity system and helps reduce greenhouse gas emissions [1]

  • There are programs that are being worked upon to tie up and motivate the consumers to strictly abide with the program features, which are: 1) Making consumer well aware with the Time of Use (TOU) features and rates, 2) Effective demand response programs to help reduce the consumption during peak demand and 3) Innovative energy efficiency and cost effective programs for residential, commercial and industrial sectors and offering alternative options and incentives to consumers who cooperate with the utility and assists in demand side management (DSM)

  • The objective function for minimizing the cost of energy in time varying tariff and minimizing peak load for leveling of appliance demand curve are given as problems in P1A and P2 respectively

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Summary

Introduction

As per the Ontario government’s Green Energy Green Economy Act (GEGEA), conserving energy saves money for the consumers and businesses and lowers the demand on the electricity system and helps reduce greenhouse gas emissions [1]. There are programs that are being worked upon to tie up and motivate the consumers to strictly abide with the program features, which are: 1) Making consumer well aware with the Time of Use (TOU) features and rates, 2) Effective demand response programs to help reduce the consumption during peak demand and 3) Innovative energy efficiency and cost effective programs for residential, commercial and industrial sectors and offering alternative options and incentives to consumers who cooperate with the utility and assists in demand side management (DSM). Recent advances in smart metering technology enable bidirectional communication between the utility operator and the end-users and facilitate the option of dynamic load adaptation. Toward this direction, demand-response (DR) programs provide incentives to major consumers of electricity, usually in the form of monetary rewards, to reduce their electricity consumption in peak-demand periods. In the study of dynamic demand side management, different techniques and algorithms have been proposed, where the basic idea has been to reduce the energy bill corresponding

Energy Management Levels
Load Shaping Techniques in DSM
Related Work
Thesis Contribution
Thesis Organization
Dynamic Pricing/Smart Pricing Signal
Dynamic Pricing for Micro-Grid
Characteristics and Type of Load
Central Controlling Device
Sources of Energy
Description of Major Home Appliances
Scheduling Home Appliances
Defining Problem
Decision Variables
Objective Function
Constraints
Mathematical Programming Approach
Appliances Assigned to the Full Time Range
Appliances with Fixed Time Range
Appliances with Mixed Time Range
Appliances with Fixed Time Range with PV Panel
Appliances with Mixed Time Range with PV Panel
Findings
Conclusion and Future Work
Full Text
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