Profit evaluation inclusive of reserve pricing for renewable-integrated GENCOs
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Saurabh Kumar
,
Bharti Dwivedi
und
Nitin Anand Shrivastava
Abstract
Under the deregulated market scenario, the electric power industry is rapidly getting transformed due to integration of increasing renewable generation. Profit maximization has always been of highest priority for all the stakeholders. The generation planning problem is an important problem in the operation and planning of power systems which is required to be solved to accomplish the maximum profit. The individual GENeration COmpanies (GENCOs) are envisioning their most profitable Unit Commitment (UC) in the light of the available forecasts of availability of solar and wind power, energy prices and reserve prices during a given scheduling period. This paper presents a UC strategy for GENCOs’ profit with a generation portfolio comprising thermal generation, wind generation, and solar PV generation in different combinations. Priority List Method (PLM) and Modified Particle Swarm Optimization (PSO) with Time-Varying Acceleration Coefficients (PSO-TVAC) solution technique is deployed on the MATLAB platform. The aim is to maximize the profit while satisfying the load demand together with maintaining sufficient reserve at each hour. Sensitivity analysis of profit has also been carried out to showcase the impact of different pricing techniques, different parameters chosen and the different bidding prices for the power dispatched as well as for the reserve power maintained. The observations that emerged through the presented solution model may help develop an insight to the GENCOs to gain maximum profits.
Funding source: Dr. APJ Abdul Kalam Technical University, Lucknow
Funding source: Institute of Engineering and Technology, Lucknow
Acknowledgment
The authors would like to acknowledge Homi Bhabha Teaching Assistant Fellowship of Dr. APJ Abdul Kalam Technical University, Lucknow and Institute of Engineering and Technology, Lucknow for supporting this research.
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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: The study was supported by the Homi Bhabha Teaching Assistant Fellowship of Dr. APJ Abdul Kalam Technical University, Lucknow and Institute of Engineering and Technology, Lucknow.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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© 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
