Demand response program using incentive and dis-incentive based scheme

The dimensions of the costs and incentives necessary for integrating demand response into the wholesale electricity market are subject to energy policies and bulk system operation. The electricity industry must gain operational flexibility to support the energy transition caused by renewable energy and decarbonization. Complementary services and technologies of demand response programs can be optimized by exploiting the variety of uses of this resource. The main objective of this work is to apply the concept of elasticity of substitution in a strategic demand shift program to promote the integration of renewable energies and the reduction of non-served power, considering an economical and safe generation dispatch. The methodology is analyzed through a case study applied in the Dominican Republic's electricity market, in which the elasticity of substitution coefficients is used to adjust variations below 10.49% of the base demand in the peak period. These variations reduce the generation operating cost by 8.4%, marginal cost by 30.19%, and non-served power by 19.1% when renewable energy increases by 5%. The inclusion of the cost of CO 2 emissions in the simulation of the operating cost function makes the objective function higher than the baseline function. For relative variations in operating cost ranging from 7.27% to 16.03%, the reduction in tons of CO 2 equivalent varies from 2.77 to 28.02. This study contextualizes the economic effect of the CO 2 emissions control, giving new possibilities to optimize system operation and the wholesale electricity market based on demand response programs that encourage flexible consumption, with favorable economic and environmental results.INDEX TERMS CO 2 emissions, demand response, the elasticity of substitution, renewable energy, wholesale electricity market.

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“…According to the statistics published by [38] in its 2019 annual report, the generation mix composition has the distribution shown Fig. 16.…”

Section: Generation Specificationsmentioning

confidence: 99%

Demand-Shifting Strategies to Optimize the Performance of the Wholesale Electricity Market: A Dominican Republic Study Case

et al. 2022

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“…The modeling of the IBDR program for the residential customers, including the loads of the customer to reduce the power consumption, are carried out in the intelligent environment, thereby reducing the customer bill. The IBDR models for handling DR problems, with optimization techniques such as the Stackelberg game, GAMS, CPLEX, and others, are used in SG to obtain a better result of demand reduction and cost minimization [7][8][9][10]. In recent years, game-theory-based algorithms have been implemented to solve the IBDR strategy bidding model from the SP and GO ends [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Multi-Stage Incentive-Based Demand Response Using a Novel Stackelberg–Particle Swarm Optimization

et al. 2022

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Demand response programs can effectively handle the smart grid’s increasing energy demand and power imbalances. In this regard, price-based DR (PBDR) and incentive-based DR (IBDR) are two broad categories of demand response in which incentives for consumers are provided in IBDR to reduce their demand. This work aims to implement the IBDR strategy from the perspective of the service provider and consumers. The relationship between the different entities concerned is modelled. The incentives offered by the service provider (SP) to its consumers and the consumers’ reduced demand are optimized using Stackelberg–particle swarm optimization (SPSO) as a bi-level problem. Furthermore, the system with a grid operator, the industrial consumers of the grid operator, the service provider and its consumers are analyzed from the service provider’s viewpoint as a tri-level problem. The benefits offered by the service provider to its customers, the incentives provided by the grid operator to its industrial customers, the reduction of customer demand, and the average cost procured by the grid operator are optimized using SPSO and compared with the Stackelberg-distributed algorithm. The problem was analyzed for an hour and 24 h in the MATLAB environment. Besides this, sensitivity analysis and payment analysis were carried out in order to delve into the impact of the demand response program concerning the change in customer parameters.

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“…Therefore, the balance of interests between the two parties when participating in the DR program should be ensured. On that basis, the social welfare maximization (SWM) framework that is often used for electricity market models, is introduced in references [18][19][20][21][22][23]. With the SWM framework, an optimal function is established consisting of sub-functions describing the benefits of the supplier and the consumer.…”

Section: Introductionmentioning

confidence: 99%

Impact of renewable energy integration on a novel method for pricing incentive payments of incentive‐based demand response program

Duc

Thanh

Van

et al. 2022

IET Generation Trans & Dist

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With the desire to improve the efficiency and the reliability of the power system as well as the advancement of smart meter and communication networks, the demand response (DR) program has been facilitated to become a key component in the smart grid. Many current researches focus on incentives‐based DR research orientation. In addition, accurately quantifying the incentive payment is also a significant challenge because of the fact that the incentive payment is currently determined depending on knowledge, experience, and experimental results. This paper presents a method of pricing incentive payments for the incentive‐based DR program through social welfare maximization framework which ensures the benefits of all participants involved. Besides, this study also proposed the quantification of incentive payments by a theoretical approach based on the satisfaction level of electricity consumers which is approximated through a fuzzy logic model. Moreover, the impact of renewable energy sources on the pricing mechanism and benefits of all parties participating in the DR program is also discussed through the calculation cost for renewable energy integration and emission cost function. The results show the validity and feasibility of the method.

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Demand response program using incentive and dis-incentive based scheme

Cited by 9 publications

References 30 publications

Demand-Shifting Strategies to Optimize the Performance of the Wholesale Electricity Market: A Dominican Republic Study Case

Demand-Shifting Strategies to Optimize the Performance of the Wholesale Electricity Market: A Dominican Republic Study Case

Multi-Stage Incentive-Based Demand Response Using a Novel Stackelberg–Particle Swarm Optimization

Impact of renewable energy integration on a novel method for pricing incentive payments of incentive‐based demand response program

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