<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The power industry has a long history of unreasonable structure of electricity consumption, high energy-consuming enterprises, low efficiency of electricity, electric energy in the current is still a bottleneck that restricts economic development. First, a fuzzy mathematical model is established and optimized using adaptive fuzzy control, which can transform the fuzzy information of people’s input language into operation instructions and perform real-time regulation. Then the structure of the power customer side energy management system is designed to control the flexible load of the power customer. Describe the control principles of different devices, and analyze the strategies for start/stop control of power generation devices and charge/discharge control of energy storage devices. This paper combined with the actual situation of the current smart grid construction, researches and elaborates on the methods of power companies to carry out demand management i//n this situation, aiming to provide effective reference for power companies to carry out demand management, so that electricity can better serve the economic development. The research results show that the cost of electricity consumption of the proposed method is only $2.9426, which can effectively improve the economic efficiency of the system and improve the supply and demand balance.</p>
</abstract>

The power industry has a long history of unreasonable structure of electricity consumption, high energy-consuming enterprises, low efficiency of electricity, electric energy in the current is still a bottleneck that restricts economic development. First, a fuzzy mathematical model is established and optimized using adaptive fuzzy control, which can transform the fuzzy information of people’s input language into operation instructions and perform real-time regulation. Then the structure of the power customer side energy management system is designed to control the flexible load of the power customer. Describe the control principles of different devices, and analyze the strategies for start/stop control of power generation devices and charge/discharge control of energy storage devices. This paper combined with the actual situation of the current smart grid construction, researches and elaborates on the methods of power companies to carry out demand management i//n this situation, aiming to provide effective reference for power companies to carry out demand management, so that electricity can better serve the economic development. The research results show that the cost of electricity consumption of the proposed method is only $2.9426, which can effectively improve the economic efficiency of the system and improve the supply and demand balance.

A fuzzy mathematical model-based approach to customer-side energy management for power companies

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The power industry has a long history of unreasonable structure of electricity consumption, high energy-consuming enterprises, low efficiency of electricity,...

A fuzzy mathematical model-based approach to customer-side energy management for power companies

Published Online: Jun 02, 2023

Page range: -

Received: Jun 07, 2022

Accepted: Oct 05, 2022

DOI: https://doi.org/10.2478/amns.2023.1.00127

Keywords
Fuzzy mathematical model, Adaptive fuzzy control, Real-time regulation, user-side energy, Flexible load

© 2023 Yinghui Lu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A fuzzy mathematical model-based approach to customer-side energy management for power companies

Published Online: Jun 02, 2023

Page range: -

Received: Jun 07, 2022

Accepted: Oct 05, 2022

DOI: https://doi.org/10.2478/amns.2023.1.00127

KeywordsFuzzy mathematical model, Adaptive fuzzy control, Real-time regulation, user-side energy, Flexible load

© 2023 Yinghui Lu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Fuzzy mathematical model, Adaptive fuzzy control, Real-time regulation, user-side energy, Flexible load