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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.18484 |
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| _version_ | 1866929438097145856 |
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| author | Dassios, Ioannis |
| author_facet | Dassios, Ioannis |
| contents | This working paper presents a comprehensive study on the development and analysis of various electricity market models, focusing on continuous, discrete, and fractional-order approaches. The continuous model captures the ongoing interactions between power producers and consumers using differential equations, providing insights into long-term trends and steady-state behaviors. The discrete model, suitable for analyzing scenarios where market events occur at specific time intervals, incorporates memory effects to account for historical behaviors and decisions, offering a realistic representation of short-term market dynamics. The fractional-order model introduces fractional calculus to capture memory effects and hereditary properties, enhancing the model's realism and predictive capability by reflecting the influence of past states on current market behavior. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_18484 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Constructing Electricity Market Models Dassios, Ioannis Optimization and Control This working paper presents a comprehensive study on the development and analysis of various electricity market models, focusing on continuous, discrete, and fractional-order approaches. The continuous model captures the ongoing interactions between power producers and consumers using differential equations, providing insights into long-term trends and steady-state behaviors. The discrete model, suitable for analyzing scenarios where market events occur at specific time intervals, incorporates memory effects to account for historical behaviors and decisions, offering a realistic representation of short-term market dynamics. The fractional-order model introduces fractional calculus to capture memory effects and hereditary properties, enhancing the model's realism and predictive capability by reflecting the influence of past states on current market behavior. |
| title | Constructing Electricity Market Models |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2407.18484 |