Demand side management in smart grid: A review and proposals for future direction

doi:10.1016/j.scs.2013.11.001

Sustainable Cities and Society

Volume 11, February 2014, Pages 22-30

https://doi.org/10.1016/j.scs.2013.11.001 Get rights and content

Highlights

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An overview, drivers and benefits for demand side management in smart grid.
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Review of demand side management techniques seen in literature.
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We model a novel technique where load responds to price.
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Learn the behaviour and control load using price signal.
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This increases efficiency, reduces carbon emissions and cuts down costs.

Abstract

This paper mainly focuses on demand side management and demand response, including drivers and benefits, shiftable load scheduling methods and peak shaving techniques. Demand side management techniques found in literature are overviewed and a novel electricity demand control technique using real-time pricing is proposed. Currently users have no means to change their power consumption to benefit the whole system. The proposed method consists of modern system identification and control that would enable user side load control. This would potentially balance demand side with supply side more effectively and would also reduce peak demand and make the whole system more efficient.

Introduction

Even in the most developed countries electricity grid that is used today was designed more than 50 years ago and is becoming outdated. By modernising electricity grids it is possible to increase the efficiency of electricity production and the use of grid assets, to decrease carbon footprint and to make the whole power network more reliable and secure. New technologies are currently being developed that will enable so called smart grid. Although smart grid does not have a single clear definition, the European Technology Platform (European Commission, 2006) defines it as follows: “A smart grid is an electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers and those that do both in order to efficiently deliver sustainable, economic and secure electricity supplies.”

The idea of a smart grid has been around for a while and recent technological advancement in communications and sensing areas enables the development of smart grid. The traditional power grid landscape consists of centralised generation, where energy is pushed one-way through transmission and distribution networks to the end users. Currently this paradigm evolves by adding distributed renewable energy generation, distributed energy storage, utility scale renewable, utility scale energy storage, etc. It is also converting from radial networks to mesh networks with the possibility to reconfigure and self-heal. On top of the existing power network layer there will be a new communications layer for information exchange and control. The whole landscape is dramatically changing from what it has been historically.

From the global perspective, main drivers behind smart grid are capacity, efficiency, reliability, sustainability and customer engagement. Higher capacity electricity grid is needed in most developing countries. At the same time electric vehicles will also demand some changes on the grid in most developed countries. Electricity throughput can be increased by enhancing efficiency. At the same time the virtual capacity would be increased using peak-shaving techniques (Zhuo, Gao, & Li, 2008). Reliability is another big issue. Most of the system failures that lead to outages occur as a result of problems in the distribution system. Information from advanced sensors through supervisory control and data acquisition (SCADA) system might help to prevent accidents or react to the fault more rapid. Smart grid also looks at sustainability problem, where one of the major elements is the interconnection of renewable generation and how that generation is managed in order to meet the demand. Finally, residential customer engagement would enable demand side management to reduce the peak load, thus decreasing the required capacity and cost as well as increasing the overall efficiency.

Two main elements when considering efficiency are losses in the system and how the assets are deployed/used. Losses often depend on the load shape in the system, for example partially loaded transformers are less efficient, so it is desired that system operates at near capacity level. Utilization of system is a major factor when considering investment in system assets. Optimal planning of how system assets should be deployed and used (energy management) plays a key role when considering overall system efficiency.

Smart grid technologies mainly focus on advancements in distribution side of electricity network. Many people associate smart grid term to smart meters placed at the end users. The main goal of this paper is to overview demand side management technologies focusing on demand response (DR) and user engagement techniques.

Section snippets

Demand side management (DSM)

Demand side management is the planning, implementation and monitoring of utility activities that are designed to influence customer use of electricity. As a result, it changes the time pattern and magnitude of utility's load. Usually, the main objective of demand side management is to encourage users to consume less power during peak times or to shift energy use to off-peak hours to flatten the demand curve. Sometimes instead of flattening the curve it is more desirable to follow the generation

Demand side management techniques

Loganthiran, Srinivasan, and Shun (2012) present demand side management strategy for load shifting based on heuristic optimisation. The proposed optimisation algorithm aims to shape the final load curve as close as possible to the desired load curve. The restriction of this strategy is compliance in the number of shiftable loads in the system, which users are willing to use at a different time. From the user point of view, this implies to a dramatic loss of comfort. Minimisation technique

Proposed DSM strategy and method

The proposed demand side management strategy is based on advanced control theory. It involves system identification and model design to achieve the desired load. Fig. 4 shows block diagram of the proposed system created using MATLAB Simulink.

The block diagram consists of four major subsystems namely generation, weather and time information, controller and the system (also referred as the plant). Each of these parts plays a distinguished role that is explained in the following section.

Simplified one house simulation

In the first case, the simulations were simplified to a single house and only the price signal was fluctuating. Fig. 7 shows the results of single residential HVAC load response to price change including temperature information. The outside temperature was set to a constant 10 °C and other values of the climate object were set to default. Attributes like HVAC comfortability settings, default temperature set point, house size, window to wall ratio, etc. define the transient and steady state

Summary

Current electricity grid is outdated and needs a complete makeover. There are many aspects that could be improved but this paper is focused on changes at the user side – demand side management and demand response. Using existing technology and implementing new strategies it is possible to increase grid capacity, efficiency, reliability, power quality, reduce carbon footprint and increase sustainability. Demand side management ideas seen in literature and new proposed strategy was presented. All

Acknowledgements

The authors would like to acknowledge the financial support of Engineering Department and Faculty of Science and Technology, Lancaster University, UK. We also would like to acknowledge help and support of Dr. James Taylor at Engineering Department, Lancaster University, and Dr. David Lund at HW Communications Ltd, Lancaster.

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The concept of demand-side management for electric utilities
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Demand side management: Concepts and methods
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View full text

Demand side management in smart grid: A review and proposals for future direction

Highlights

Abstract

Introduction

Section snippets

Demand side management (DSM)

Demand side management techniques

Proposed DSM strategy and method

Simplified one house simulation

Summary

Acknowledgements

Energy Policy

Demand response in electricity markets: An overview

Primer on demand side management with an emphasis on price-responsive programs

European smart grids technology platform: Vision and strategy for Europes electricity networks of the future

Analysis of residential demand response and double-auction markets

The concept of demand-side management for electric utilities

Proceedings of the IEEE

Demand side management: Concepts and methods