Critical peak rebate strategy and application to demand response Article Swipe

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Hejun Yang , Xinyu Zhang , Yinghao Ma , Dabo Zhang ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.1186/s41601-021-00206-x

Time-of-use (TOU) pricing strategy is an important component of demand-side management (DSM), but the cost of supplying power during critical peak periods remains high under TOU prices. This affects power system reliability. In addition, TOU prices are usually applicable to medium- and long-term load control but cannot effectively regulate short-term loads. Therefore, this paper proposes an optimization method for TOU pricing and changes the electricity consumption patterns during the critical peak periods through a critical peak rebate (CPR). This reduces generation costs and improves power system reliability. An optimization model for peak-flat-valley (PFV) period partition is established based on fuzzy clustering and an enumeration iterative technique. A TOU pricing optimization model including grid-side and customer-side benefits is then proposed, and a simulated annealing particle swarm optimization (SAPSO) algorithm is used to solve the problem. Finally, a CPR decision model is developed to further reduce critical peak loads. The effectiveness of the proposed model and algorithm is illustrated through different case studies of the Roy Billinton Test System (RBTS).

Related Topics

Particle Swarm Optimization

Electrical Engineering

Artificial Intelligence

Combinatorics

Machine Learning

Quantum Mechanics

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Particle swarm optimization Mathematical optimization Computer science Simulated annealing Partition (number theory) Electricity pricing Electric power system Reliability (semiconductor) Grid Power grid Electricity Fuzzy logic Cluster analysis Power consumption Reliability engineering Operations research Power (physics) Electricity market Engineering Mathematics Physics Geometry Electrical engineering Artificial intelligence Combinatorics Machine learning Quantum mechanics

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Type: article
Language: en
Landing Page: https://doi.org/10.1186/s41601-021-00206-x
PDF: https://pcmp.springeropen.com/counter/pdf/10.1186/s41601-021-00206-x
OA Status: hybrid
Cited By: 22
References: 34
Related Works: 10
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DOI: https://doi.org/10.1186/s41601-021-00206-x

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Title: Critical peak rebate strategy and application to demand response

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Language: en

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Publication year: 2021

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Publication date: 2021-09-01

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Authors: Hejun Yang, Xinyu Zhang, Yinghao Ma, Dabo Zhang

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Landing page: https://doi.org/10.1186/s41601-021-00206-x

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Concepts: Particle swarm optimization, Mathematical optimization, Computer science, Simulated annealing, Partition (number theory), Electricity pricing, Electric power system, Reliability (semiconductor), Grid, Power grid, Electricity, Fuzzy logic, Cluster analysis, Power consumption, Reliability engineering, Operations research, Power (physics), Electricity market, Engineering, Mathematics, Physics, Geometry, Electrical engineering, Artificial intelligence, Combinatorics, Machine learning, Quantum mechanics

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Cited by: 22

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