Unit Commitment in Microgrid Considering Customer Satisfaction in Incentives-Based Demand Response Program: A Fuzzy Logic Model

The increasing integration of Renewable Energy Sources (RES) poses significant challenges for power system operators due to their inherent variability and intermittency. This paper presents a Mixed-Integer Quadratic Programming (MIQP) approach to solve the Unit Commitment (UC) problem in microgrids,...

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Bibliographic Details
Published in:Smart grids and sustainable energy 2025-01, Vol.10 (1), p.10, Article 10
Main Authors: Xuan, Hung Ta, Duc, Tuyen Nguyen
Format: Article
Language:English
Subjects:
Customer satisfaction
Distributed generation
Economics and Management
Electric power demand
Electric power systems
Electrical loads
Electrical Machines and Networks
Electricity
Electricity pricing
Energy
Energy costs
Energy management
Energy Policy
Energy storage
Energy Systems
Fuzzy logic
Incentives
Mixed integer
Operating costs
Operators
Optimization
Power Electronics
Quadratic programming
Renewable energy sources
Systems stability
Unit commitment
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Summary:The increasing integration of Renewable Energy Sources (RES) poses significant challenges for power system operators due to their inherent variability and intermittency. This paper presents a Mixed-Integer Quadratic Programming (MIQP) approach to solve the Unit Commitment (UC) problem in microgrids, focusing on the combined use of RES, Battery Energy Storage Systems (BESS), and Incentive-Based Demand Response (IBDR) programs. The proposed model optimizes power generation scheduling for both grid-connected and isolated microgrid modes. To assess customer satisfaction in IBDR programs, a Fuzzy Logic Model evaluates key factors like load demand, freedom of time, electricity prices, and incentives. This model aims to minimize operating costs when IBDR is not applied or maximize social welfare when IBDR is implemented. Results, obtained using Matlab/Simulink for customer satisfaction modeling and the CPLEX solver in Python for UC optimization, demonstrate that integrating BESS and IBDR enhances system flexibility and resilience to RES fluctuations. In optimal grid-connected operation, the model achieves a 22.27% reduction in operating costs and a 28.95% increase in social welfare compared to isolated operations. Although customer electricity bills rise by 15.35%, increased satisfaction, and system stability underscore the overall benefits of integrating BESS and IBDR for both operators and consumers. These findings demonstrate the potential of this approach to significantly enhance microgrid performance and ensure greater reliability in practical implementations.
ISSN:2731-8087
2731-8087
2199-4706
DOI:10.1007/s40866-024-00233-1