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Research on Power Grid Investment Portfolio Optimization Method Based on Deep Deterministic Policy Gradient Algorithm

Published: 19 April 2023 Publication History

Abstract

In recent years, deep learning and reinforcement learning algorithms have been widely used in various fields. In the field of electric power investment, deep learning and reinforcement learning algorithms are also widely paid attention to. This paper takes the power grid project portfolio model as the research object and analyzes the complex and different power grid project portfolios. Firstly, the power grid investment scale pre-allocation model and modified allocation model are proposed. Then, considering the advantages of deep learning and reinforcement learning algorithms, a deep Deterministic policy gradient (DDPG) algorithm is proposed to select the power grid investment scheme and optimize the scheme. Finally, an empirical analysis is made through a typical provincial power grid. The results show that the model is effective and feasible.

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RICAI '22: Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence
December 2022
1396 pages
ISBN:9781450398343
DOI:10.1145/3584376
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 19 April 2023

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