The smart grid is conceived of as an electric grid that can deliver electricity in a controlled, smart way from points of generation to active consumers. Demand response (DR), by promoting the interaction and responsiveness of the customers, may offer a broad range of potential benefits on system operation and expansion and on market efficiency. Moreover, by improving the reliability of the power system and, in the long term, lowering peak demand, DR reduces overall plant and capital cost investments and postpones the need for network upgrades. In this paper a survey of DR potentials and benefits in smart grids is presented. Innovative enabling technologies and systems, such as smart meters, energy controllers, communication systems, decisive to facilitate the coordination of efficiency and DR in a smart grid, are described and discussed with reference to real industrial case studies and research projects.

Demand response and smart grids—A survey

A summary of demand response in electricity markets

A survey of index decomposition analysis in energy and environmental studies

The smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.

A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms

This tutorial paper discusses some aspects of electricity markets from the perspective of the demand-side. It argues that increasing the short-run price elasticity of the demand for electrical energy would improve the operation of these markets. It shows, however, that enhancing this elasticity is not an easy task. The tools that consumers and retailers of electrical energy need to participate more actively and effectively in electricity markets are discussed. The paper also describes how consumers of electricity can take part in the provision of power system security.

Demand-side view of electricity markets

Since the energy crisis of 2000–2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a change out of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40% may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, this paper surveys the evidence from the 15 most recent pilots, experiments and full-scale implementations of dynamic pricing of electricity. It finds conclusive evidence that households respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way programmable communicating thermostats and always-on gateway systems that allow multiple end-uses to be controlled remotely. In addition, the design of the studies, the tools used to analyze the data and the geography of the assessment influence demand response. Across the range of experiments studied, time-of-use rates induce a drop in peak demand that ranges between 3 and 6% and critical-peak pricing (CPP) tariffs induce a drop in peak demand that ranges between 13 and 20%. When accompanied with enabling technologies, the latter set of tariffs lead to a reduction in peak demand in the 27–44% range.

Household response to dynamic pricing of electricity: a survey of 15 experiments

The impact of informational feedback on energy consumption—A survey of the experimental evidence

In theory, In-Home Displays (IHDs) can revolutionize the way utilities communicate information to customers because they can induce changes in customer behavior even when they are not accompanied by a change in electric prices or rebates for purchasing efficient equipment. IHDs provide consumers with direct feedback - real-time information on energy consumption and costs - and turn a once opaque and static electric bill into a transparent, dynamic, and controllable process. However, to what extent do consumers actually respond to the direct feedback provided by IHDs?In this paper, we seek to empirically answer this question by reviewing a dozen utility pilot programs in North America and abroad that either focus on the energy conservation impact of IHDs or study demand-side management technologies and include IHDs as one of the tools. We also review overall customer opinions and attitudes towards IHDs and direct feedback to the extent that this information is available from the pilot studies.Our review indicates that the direct feedback provided by IHDs encourages consumers to make more efficient use of energy. We find that consumers who actively use an IHD can reduce their consumption of electricity on average by about seven percent when prepayment of electricity is not involved. When consumers both use an IHD and are on an electricity prepayment system, they can reduce their electricity consumption by about twice that amount. In regard to demand response impacts, we find that the impact of time-of-use rates is augmented by direct feedback from IHDs.

The Impact of Informational Feedback on Energy Consumption -- A Survey of the Experimental Evidence

We estimate the cost of installing smart meters in the EU to be €51 billion, and that operational savings will be worth between €26 to 41 billion, leaving a gap of €10 to 25 billion between benefits and costs Smart meters can fill this gap because they enable the provision of dynamic pricing, which reduces peak demand The present value of savings in peaking infrastructure could be as high as €67 billion for the EU if policy-makers can overcome barriers to consumers adopting dynamic tariffs, but only €14 billion otherwise We outline a number of ways to increase the adoption of dynamic tariffs

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=1527165

Unlocking the €53 Billion Savings from Smart Meters in the EU - How Increasing the Adoption of Dynamic Tariffs Could Make or Break the EU’s Smart Grid Investment

Ahmad Faruqui

Papers

Household response to dynamic pricing of electricity: a survey of 15 experiments

The impact of informational feedback on energy consumption—A survey of the experimental evidence

The Impact of Informational Feedback on Energy Consumption -- A Survey of the Experimental Evidence

Unlocking the €53 Billion Savings from Smart Meters in the EU - How Increasing the Adoption of Dynamic Tariffs Could Make or Break the EU’s Smart Grid Investment

Quantifying Customer Response to Dynamic Pricing