A non-cooperative game based energy management considering distributed energy resources in price-based and incentive-based demand response program
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Monika Gaba
und
Saurabh Chanana
Abstract
Demand response (DR), an integral part of the smart grid, has great potential in handling the challenges of the existing power grid. The potential of different DR programs in the energy management of residential consumers (RCs) and the integration of distributed energy resources (DERs) is an important research topic. A novel distributed approach for energy management of RCs considering the competitive interactions among them is presented in this paper. The impact of participation of RC’s in price-based (PB) and incentive-based (IB) DR programs is investigated using game theory. For this, an energy management optimization problem (EMOP) is formulated to minimize electricity cost. The utility company employs electricity price as a linear function of aggregated load in the PB DR program and an incentive rate in the IBDR program. RCs are categorized into active and passive users. Active users are further distinguished based on the ownership of energy storage devices (SD) and dispatchable generation units (DGU). EMOP is modeled using a non-cooperative game, and the distributed proximal decomposition method is used to obtain the Nash equilibrium of the game. The results of the proposed approach are analyzed using different case studies. The performance of the proposed approach is evaluated in terms of aggregated cost and system load profile. It has been observed that participation in PB and IBDR program benefits both the utility and the consumers.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/ijeeps-2021-0021).
© 2021 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Efficient power scheduling in smart homes using a novel artificial ecosystem optimization technique considering two pricing schemes
- MPPT control based on improved mayfly optimization algorithm under complex shading conditions
- A cogeneration scheme with biogas and improvement of frequency stability using inertia based control in AC microgrid
- Profit evaluation inclusive of reserve pricing for renewable-integrated GENCOs
- An ideal solution for the deployment of photovoltaic generators using agent-based Nash Differential Evolution (NashDE) algorithm
- Design and operation of smart hybrid microgrid
- Three-state switching cell boost converter using H-inf controller
- Bayesian optimization based machine learning approaches for prediction of plug-in electric vehicle state-of-charge
- Probabilistic and deterministic analysis of single diode model of a solar cell: a case study
- A novel approach to increase the share of renewable purchase obligation for planning of distribution network including grid scale energy storage
- A non-cooperative game based energy management considering distributed energy resources in price-based and incentive-based demand response program
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Efficient power scheduling in smart homes using a novel artificial ecosystem optimization technique considering two pricing schemes
- MPPT control based on improved mayfly optimization algorithm under complex shading conditions
- A cogeneration scheme with biogas and improvement of frequency stability using inertia based control in AC microgrid
- Profit evaluation inclusive of reserve pricing for renewable-integrated GENCOs
- An ideal solution for the deployment of photovoltaic generators using agent-based Nash Differential Evolution (NashDE) algorithm
- Design and operation of smart hybrid microgrid
- Three-state switching cell boost converter using H-inf controller
- Bayesian optimization based machine learning approaches for prediction of plug-in electric vehicle state-of-charge
- Probabilistic and deterministic analysis of single diode model of a solar cell: a case study
- A novel approach to increase the share of renewable purchase obligation for planning of distribution network including grid scale energy storage
- A non-cooperative game based energy management considering distributed energy resources in price-based and incentive-based demand response program
