An Improved Deep Reinforcement Learning Method for Dispatch Optimization Strategy of Modern Power Systems

Zhai, Suwei; Li, Wenyun; Qiu, Zhenyu; Zhang, Xinyi; Hou, Shixi

doi:10.3390/e25030546

Cited by 4 publications

(3 citation statements)

References 31 publications

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“…The findings provide new methods for wind parameter modeling and wind energy development in other regions. Due to the power of intelligent algorithms, numerous scholars have conducted in-depth studies on wind power prediction using various artificial intelligence algorithms, making it an effective and cutting-edge alternative [ 49 , 50 ]. Furthermore, to more accurately represent wind energy, consideration of multi-variable joint probability density modeling, including wind speed, wind direction, wind shear, and air density, is necessary.…”

Section: Discussionmentioning

confidence: 99%

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy Assessment

Liu,

Yan

2024

Entropy

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The joint probability density function of wind speed and wind direction serves as the mathematical basis for directional wind energy assessment. In this study, a nonparametric joint probability estimation system for wind velocity and direction based on copulas is proposed and empirically investigated in Inner Mongolia, China. Optimal bandwidth algorithms and transformation techniques are used to determine the nonparametric copula method. Various parameter copula models and models without considering dependency relationships are introduced and compared with this approach. The results indicate a significant advantage of employing the nonparametric copula model for fitting joint probability distributions of both wind speed and wind direction, as well as conducting correlation analyses. By utilizing the proposed KDE-COP-CV model, it becomes possible to accurately and reliably analyze how wind power density fluctuates in relation to wind direction. This study reveals the researched region possesses abundant wind resources, with the highest wind power density being highly dependent on wind direction at maximum speeds. Wind resources in selected regions of Inner Mongolia are predominantly concentrated in the northwest and west directions. These findings can contribute to improving the accuracy of micro-siting for wind farms, as well as optimizing the design and capacity of wind turbine generators.

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Section: Discussionmentioning

confidence: 99%

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy Assessment

Liu,

Yan

2024

Entropy

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“…The research details the rise of greenhouse gases and the effect of global warming and makes solar water heater systems and helps optimize them [45]. The solar water heater is produced by Evacuated Tube Collectors (ETC) that convert the solar energy to heat energy and help to distribute the energy throughout the building or office and is applied for water heating and also energy consumption in houses [46]. These generalized the use of solar water heaters and performed many calculations and steps to collect the data from the tube collectors and transform the energy from solar energy to heat energy of the water [47].…”

Section: Solar Ground Heat Pump System For Cooling and Heating Househ...mentioning

confidence: 99%

Sizing and Optimization of Solar Water Heater Systems for Different Demands

Anand Kishorbhai Patel

2023

tjjpt

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In the Introduction Chapter discussed how significant attention has been paid to the use of solar energy for heating water as a sustainable substitute for traditional fossil fuel-based systems. It has also made a crucial need to improve the functionality and sustainability of solar water heater systems in a variety of operating scenarios serves as the foundation for this research. The Third Chapter Methodology explains the philosophy of this study is interconnected, which acknowledges the subjectivity of human experiences as well as opinions about solar water heaters. It has also done method enabled the systematic testing and improvement of already-known information. The Fourth Chapter's Results discussed Dynamic Demand Characterization and Classification along with Innovative Solar Water Heater Sizing Methodologies. It has also done Optimization Techniques for Enhanced System Performance as well as Integration of Climate Variables in System Design. The Fifth Chapter's Conclusion explains study has clarified the crucial value of dynamic demand characterization, cutting-edge sizing techniques, and the inclusion of climate variables in solar water heater system optimization.

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“…Integrated demand response (IDR) can effectively promote the adjustment of energy consumption behaviors of users, which is an important way to realize flexible interaction between the energy demand side and supply side [15]. Most of the existing research is about a single type of demand response behavior [16,17], or multi-type demand response behavior in a single IES [18,19].…”

Section: Introductionmentioning

confidence: 99%

Master–Slave Game Optimal Scheduling for Multi-Agent Integrated Energy System Based on Uncertainty and Demand Response

Zhu,

Wang

2024

Sustainability

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With the transformation of the energy market from the traditional vertical integrated structure to the interactive competitive structure, the traditional centralized optimization method makes it difficult to reveal the interactive behavior of multi-agent integrated energy systems (MAIES). In this paper, a master–slave game optimal scheduling strategy of MAIES is proposed based on the integrated demand response. Firstly, a master–slave game framework of MAIES is established with an energy management agent as leader, an energy operation agent, an energy storage agent, and a user aggregation agent as followers. Secondly, in view of the wind and solar uncertainty, the Monte Carlo method is used to generate random scenarios, and the k-means clustering method and pre-generation elimination technology are used for scenario reduction. Then, according to different flexible characteristics of loads, a multi-load and multi-type integrated demand response model including electric, thermal, and cold energy is built to fully utilize the regulation role of flexible resources. On this basis, the transaction decision-making models of each agent are constructed, and the existence and uniqueness of the Stackelberg equilibrium solution are proved. Finally, the case simulations demonstrate the effectiveness of the proposed optimal scheduling strategy of MAIES. Compared to the scenario without considering the wind and solar uncertainty and the integrated demand response, the rate of renewable energy curtailment was reduced by 6.03% and the carbon emissions of the system were reduced by 1335.22 kg in the scenario considering the proposed method in this paper.

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An Improved Deep Reinforcement Learning Method for Dispatch Optimization Strategy of Modern Power Systems

Cited by 4 publications

References 31 publications

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy Assessment

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy Assessment

Sizing and Optimization of Solar Water Heater Systems for Different Demands

Master–Slave Game Optimal Scheduling for Multi-Agent Integrated Energy System Based on Uncertainty and Demand Response

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