scholarly journals An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective

2021 ◽  
Vol 13 (11) ◽  
pp. 6066
Author(s):  
Thamer Alquthami ◽  
Ahmad H. Milyani ◽  
Muhammad Awais ◽  
Muhammad B. Rasheed
Keyword(s):  
Demand Response ◽  
Dynamic Pricing ◽  
Optimization Problem ◽  
End Users ◽  
Electricity Price ◽  
Monetary Incentives ◽  
Electricity Pricing ◽  
Pricing Policy ◽  
Load Shifting ◽  
Demand And Supply

Price based demand response is an important strategy to facilitate energy retailers and end-users to maintain a balance between demand and supply while providing the opportunity to end users to get monetary incentives. In this work, we consider real-time electricity pricing policy to further calculate the incentives in terms of reduced electricity price and cost. Initially, a mathematical model based on the backtracking technique is developed to calculate the load shifted and consumed in any time slot. Then, based on this, the electricity price is calculated for all types of users to estimate the incentives through load shifting profiles. To keep the load under the upper limit, the load is shifted in other time slots in such a way to facilitate end-users regarding social welfare. The user who is not interested in participating load shifting program will not get any benefit. Then the well behaved functional form optimization problem is solved by using a heuristic-based genetic algorithm (GA), wwhich converged within an insignificant amount of time with the best optimal results. Simulation results reflect that the users can obtain some real incentives by participating in the load scheduling process.

A Research into Probabilistic Electricity Load Prediction Based on Demand Response Feature under Smart Grid Environment

2013 ◽  
Vol 380-384 ◽  
pp. 3098-3102
Author(s):  
Ning Lu ◽  
Ying Liu
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Electricity Market ◽  
Electricity Price ◽  
Electricity Pricing ◽  
Load Prediction ◽  
Characteristics Analysis ◽  
System Risk ◽  
Probabilistic Load ◽  
Demand Changes

The construction of grid plays an important role in national economic development, social stability and peoples life. In case that electricity market adopts real time electricity price, users active participation and real time response to electricity price will change the traditional load prediction from rigid forecasting to flexible forecasting which takes electricity demand response into consideration. By using wavelet analysis and error characteristics analysis, the researches into the probabilistic predicting method for demand changes under the real time electricity pricing is carried out. The probabilistic load prediction result shall enable decision makers to better understand the load change range in the future and make more reasonable decision. Meanwhile, it shall provide support to electricity system risk analysis.

scholarly journals Fostering Residential Demand Response through Dynamic Pricing Schemes: A Behavioural Review of Smart Grid Pilots in Europe

2016 ◽  
Vol 8 (9) ◽  
pp. 929 ◽  
Author(s):  
Kris Kessels ◽  
Carolien Kraan ◽  
Ludwig Karg ◽  
Simone Maggiore ◽  
Pieter Valkering ◽  
...  
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Dynamic Pricing ◽  
Energy Use ◽  
Considerable Effect ◽  
End Users ◽  
Automated Control ◽  
Survey Paper ◽  
Residential Demand ◽  
Pricing Schemes

Many smart grid projects make use of dynamic pricing schemes aimed to motivate consumers to shift and/or decrease energy use. Based upon existing literature and analyses of current smart grid projects, this survey paper presents key lessons on how to encourage households to adjust energy end use by means of dynamic tariffs. The paper identifies four key hypotheses related to fostering demand response through dynamic tariff schemes and examines whether these hypotheses can be accepted or rejected based on a review of published findings from a range of European pilot projects. We conclude that dynamic pricing schemes have the power to adjust energy consumption behavior within households. In order to work effectively, the dynamic tariff should be simple to understand for the end users, with timely notifications of price changes, a considerable effect on their energy bill and, if the tariff is more complex, the burden for the consumer could be eased by introducing automated control. Although sometimes the mere introduction of a dynamic tariff has proven to be effective, often the success of the pricing scheme depends also on other factors influencing the behavior of end users. An important condition to make dynamic tariffs work is that the end users should be engaged with them.

Time-of-Use Pricing in the Electricity Market: An Application of Stackelberg Game

2019 ◽  
Author(s):  
Atharva Ketkar ◽  
Joselyn Koonamparampath ◽  
Mayur Sawant
Keyword(s):  
Power Consumption ◽  
Demand Response ◽  
Electricity Market ◽  
Stackelberg Game ◽  
Electrical Power ◽  
Electricity Industry ◽  
Electricity Price ◽  
Electricity Pricing ◽  
Best Response ◽  
Time Of Use Pricing

Abstract Electrical power, generated and consumed, is perhaps, one of today’s most important construct in determining the progress of a people. The power mismatch between the generated and consumed power is one of the major issues faced in the electricity industry. This can be addressed by analysing user behaviour and manipulating it. This paper attempts to put forth a demand response (DR) technique using the concept of Time-of-Use (ToU) electricity pricing. The utilities have an upper hand of quoting the electricity price whereas the users must follow this price and give their best response of power consumption. This process is similar to a leader-follower setting as in a Stackelberg game where the follower acts according to the leader’s strategy and gives its best response in every situation. This paper proposes a pricing technique where the users are charged according to the amount of power consumed in the specific period of time.

scholarly journals A User-Oriented Pricing Design for Demand Response in Smart Grid

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yanglin Zhou ◽  
Lin Cheng ◽  
Song Ci ◽  
Yang Yang ◽  
Shiqian Ma
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Stackelberg Game ◽  
Equilibrium Points ◽  
End Users ◽  
Pricing Policy ◽  
Utility Company ◽  
Pricing Scheme ◽  
High Satisfaction ◽  
Cooperative Relationship

Demand response (DR) programs are designed to affect the energy consumption behavior of end-users in smart grid. However, most existing pricing designs for DR programs ignore the influence of end-users’s diversity and personal preference. Thus, in this paper, we investigate an incentive pricing design based on the utility maximization rule with consideration of end-users’ preference and appliances’ operational patterns. In particular, the utility company determines the pricing policy by trading off the budget revenue and social obligation, while each end-user aims to maximize their own utility profits with high satisfaction level by scheduling multiclass appliances. We formulate the conflict and cooperative relationship between the utility company and end-users as a Stackelberg game, and the equilibrium points are obtained by the backward induction method, which exists and is unique. At the equilibrium, the utility company adopts real-time pricing (RTP) scheme to coordinate end-users to fulfill the benefit of themselves, i.e., under such price, end-users automatically maximize overall utility profits of the overall system. We propose a distributed algorithm and an adaptive pricing scheme for the utility company and end-users to jointly achieve the best performance of the entire system. Finally, extensive simulation results based on real operation data show the effectiveness of the proposed scheme.

Dynamic Pricing of Electricity

2012 ◽  
Vol 102 (3) ◽  
pp. 381-385 ◽  
Author(s):  
Paul L Joskow ◽  
Catherine D Wolfram
Keyword(s):  
Demand Response ◽  
Dynamic Pricing ◽  
Time Varying ◽  
Electricity Pricing ◽  
Marginal Costs ◽  
Technological Advances ◽  
The Us ◽  
Recent Developments ◽  
End Use

As both a regulator and an academic, Fred Kahn argued that end-use electricity consumers should face prices that reflect the time-varying marginal costs of generating electricity. This has been very slow to happen in the US, even in light of recent technological advances that have lowered costs and improved functionality for meters and automated demand response technologies. We describe these recent developments and discuss the remaining barriers to the proliferation of time-varying electricity pricing.

Modeling of unforced demand response programs

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hassan Jalili ◽  
Pierluigi Siano
Keyword(s):  
Demand Response ◽  
Load Shifting ◽  
Response Models ◽  
Temperature Changes ◽  
Proposed Model ◽  
Equipment Failures ◽  
Demand Response Programs ◽  
Simultaneous Implementation ◽  
Long Term Studies

Abstract Demand response programs are useful options in reducing electricity price, congestion relief, load shifting, peak clipping, valley filling and resource adequacy from the system operator’s viewpoint. For this purpose, many models of these programs have been developed. However, the availability of these resources has not been properly modeled in demand response models making them not practical for long-term studies such as in the resource adequacy problem where considering the providers’ responding uncertainties is necessary for long-term studies. In this paper, a model considering providers’ unavailability for unforced demand response programs has been developed. Temperature changes, equipment failures, simultaneous implementation of demand side management resources, popular TV programs and family visits are the main reasons that may affect the availability of the demand response providers to fulfill their commitments. The effectiveness of the proposed model has been demonstrated by numerical simulation.

scholarly journals How Can Floor Covering Influence Buildings’ Demand Flexibility?

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3658
Author(s):  
Hyeunguk Ahn ◽  
Jingjing Liu ◽  
Donghun Kim ◽  
Rongxin Yin ◽  
Tianzhen Hong ◽  
...  
Keyword(s):  
Demand Response ◽  
Radiant Heat ◽  
Response Strategy ◽  
Sensitivity Analyses ◽  
Thermal Mass ◽  
Cooling Load ◽  
Floor Covering ◽  
Load Shifting ◽  
Concrete Floor ◽  
Floor Surface

Although the thermal mass of floors in buildings has been demonstrated to help shift cooling load, there is still a lack of information about how floor covering can influence the floor’s load shifting capability and buildings’ demand flexibility. To fill this gap, we estimated demand flexibility based on the daily peak cooling load reduction for different floor configurations and regions, using EnergyPlus simulations. As a demand response strategy, we used precooling and global temperature adjustment. The result demonstrated an adverse impact of floor covering on the building’s demand flexibility. Specifically, under the same demand response strategy, the daily peak cooling load reductions were up to 20–34% for a concrete floor whereas they were only 17–29% for a carpet-covered concrete floor. This is because floor covering hinders convective coupling between the concrete floor surface and the zone air and reduces radiative heat transfer between the concrete floor surface and the surrounding environment. In hot climates such as Phoenix, floor covering almost negated the concrete floor’s load shifting capability and yielded low demand flexibility as a wood floor, representing low thermal mass. Sensitivity analyses showed that floor covering’s effects can be more profound with a larger carpet-covered area, a greater temperature adjustment depth, or a higher radiant heat gain. With this effect ignored for a given building, its demand flexibility would be overestimated, which could prevent grid operators from obtaining sufficient demand flexibility to maintain a grid. Our findings also imply that for more efficient grid-interactive buildings, a traditional standard for floor design could be modified with increasing renewable penetration.

scholarly journals Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1378
Author(s):  
Ildar Daminov ◽  
Rémy Rigo-Mariani ◽  
Raphael Caire ◽  
Anton Prokhorov ◽  
Marie-Cécile Alvarez-Hérault
Keyword(s):  
Ambient Temperature ◽  
Demand Response ◽  
Thermal Model ◽  
Critical Period ◽  
Optimization Problem ◽  
Integrated Management ◽  
Critical Periods ◽  
Network Access ◽  
Maximal Amplitude ◽  
Demand Response Program

(1) Background: This paper proposes a strategy coupling Demand Response Program with Dynamic Thermal Rating to ensure a transformer reserve for the load connection. This solution is an alternative to expensive grid reinforcements. (2) Methods: The proposed methodology firstly considers the N-1 mode under strict assumptions on load and ambient temperature and then identifies critical periods of the year when transformer constraints are violated. For each critical period, the integrated management/sizing problem is solved in YALMIP to find the minimal Demand Response needed to ensure a load connection. However, due to the nonlinear thermal model of transformers, the optimization problem becomes intractable at long periods. To overcome this problem, a validated piece-wise linearization is applied here. (3) Results: It is possible to increase reserve margins significantly compared to conventional approaches. These high reserve margins could be achieved for relatively small Demand Response volumes. For instance, a reserve margin of 75% (of transformer nominal rating) can be ensured if only 1% of the annual energy is curtailed. Moreover, the maximal amplitude of Demand Response (in kW) should be activated only 2–3 h during a year. (4) Conclusions: Improvements for combining Demand Response with Dynamic Thermal Rating are suggested. Results could be used to develop consumer connection agreements with variable network access.

Development of a methodology for forecasting electricity-price series to improve demand response initiatives

2009 ◽  
Author(s):  
A. Guillamon ◽  
M.C. Ruiz ◽  
A. Gabaldon ◽  
S. Valero ◽  
C. Alvarez ◽  
...  
Keyword(s):  
Demand Response ◽  
Electricity Price ◽  
Price Series

Flexible IT platform for synchronizing energy demands with volatile markets

2018 ◽  
Vol 60 (3) ◽  
pp. 155-164 ◽  
Author(s):  
Paul Schott ◽  
Raphael Ahrens ◽  
Dennis Bauer ◽  
Fabian Hering ◽  
Robert Keller ◽  
...  
Keyword(s):  
Demand Response ◽  
Business Case ◽  
Electricity Production ◽  
Demand And Supply ◽  
Know How ◽  
Electricity System ◽  
Energy Demands ◽  
Production Processes ◽  
Long Run ◽  
Additional Level

Abstract Abandoning fossil and nuclear energy sources in the long run and increasing amount of renewable energies in electricity production causes a more volatile power supply. Depending on external realities, renewable energy production emphasizes the need for measures to guarantee the necessary balance of demand and supply in the electricity system at all times. Energy intensive industry processes theoretically include high Demand Response potentials suitable to tackle this increasing supply volatility. Nevertheless, most companies do not operate their production in a flexible manner due to multiple reasons: among others, the companies lack know-how, technologies and a clear business case to introduce an additional level of flexibility into their production processes, they are concerned about possible impacts on their processes by varying the electricity demand and need assistance in exploiting their flexibility. Aside from fostering knowledge in industry companies, an IT-solution that supports companies to use their processes’ Demand Response potential has become necessary. Its concept must support companies in managing companies’ energy-flexible production processes and monetarize those potentials at flexibility markets. This paper presents a concept, which integrates both companies and energy markets. It enables automated trading of companies’ Demand Response potential on different flexibility markets.

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