Shunfu Lin

Collaborative energy optimization training strategy for multiple intelligent buildings based on federated reinforcement learning

Ronghui Liu, Gaiping Sun, Shunfu Lin, Xu Wang

cn (code pays fourni par la source)

Smart Generation Control for Interconnected Power System Based on Self-Learning Reward Function

Fan Yang, Yuexing Shi, Jiangjiao Xu, Dongdong Li et autres

Smart generation control (SGC) offers solutions to stabilize frequency fluctuations in power systems characterized by uncertainty. However, most existing SGC methods often rely on subjectively designed reward functions created by humans, which hinders the effective training of agents and is also a …

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Optimal Planning of Integrated Energy Systems Considering Multi-Day Low-Output Events and Efficiency Degradation of Electrolyzer

Shunfu Lin, Jin Tan, Zhuoxiang Wu, Qiuwei Wu

Hydrogen storage plays a key role in mitigating the long-term fluctuations in integrated energy systems (IESs), such as the multi-day low-output events (MLEs) that last for several days. However, most studies do not consider the impacts of the MLEs on the IES …

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Analysis of Coordination Strategies between Large-Scale Power Users' Direct Participation in Inter-Provincial Spot Markets and Grid-Agent Electricity Procurement

Bo Zhou, Shunfu Lin, Zhiqiang Luo, Shuyan Zhang et autres

This study focuses on analyzing coordination strategies between Large-Scale power users' direct participation in inter-provincial spot markets and Grid-Agent electricity procurement. It aims to provide theoretical support and practical guidance for the stable operation of the electricity market during the reform transition …

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Ultra-Short-Term Solar Power Prediction Using Sky Image Sequences by a Residual Vision Reformer

Razieh Rastgoo, Nima Amjady, Shunfu Lin, S. M. Muyeen

The unpredictable nature of solar power generation, largely influenced by fluctuating cloud cover, poses a challenge to the stability of renewable energy systems. Considering this, accurate forecasting of solar power can lead to better grid management and operation. With the advent of …

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Multi-objective optimal scheduling strategy of energy storage system based on improved multi-agent deep deterministic policy gradient

Randy J. Gu, Yishun Wang, Hua Xue, Yiyan Sang et autres

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Coordinated Optimal Dispatching of Source and Load in Energy-Intensive Industrial Park

Liang Qian, Shunfu Lin, Dongdong Li, Wei Wang

In recent years, the randomness and intermittency of wind and solar power output have continuously increased the regulation pressure of conventional power sources. The conventional electric power dispatching cannot effectively solve the uncertainty of renewable energy output. The problem of obstructing the …

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Optimal Pricing and Energy‐Sharing Strategies for a Commercial Building‐Based Virtual Power Plant

Shunfu Lin, H.-C. Wang, Yunwei Shen, Hao Yu et autres

Abstract As distributed resources within buildings continue to grow, buildings have had a significant impact on the stability of the distribution network. It's urgent to effectively achieve regional power balancing and consumption within building clusters. Virtual power plants (VPP) are believed to …

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Multi-scenario stochastic assessment of operational risk of integrated energy system based on R-vine Copula

Zhong Wu, Shunfu Lin, Jin Tan, Dongdong Li

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Nonintrusive Load Disaggregation Based on Attention Neural Networks

Shunfu Lin, Yi Li, Yunwei Shen, Fangxing Li et autres

Nonintrusive load monitoring (NILM), also known as energy disaggregation, infers the energy consumption of individual appliances from household metered electricity data. Recently, NILM has garnered significant attention as it can assist households in reducing energy usage and improving their electricity behaviors. In …

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A hybrid model based on the photovoltaic conversion model and artificial neural network model for short-term photovoltaic power forecasting

Ran Chen, Shaowei Gao, Yao Zhao, Dongdong Li et autres

Photovoltaic (PV) power is greatly uncertain due to the random meteorological parameters. Therefore, accurate PV power forecasting results are significant for the dispatching of power and improving of system stability. This paper proposes a hybrid forecasting model for one-day-ahead PV power forecasting …

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Bidding strategy for the virtual power plant based on cooperative game participating in the Electricity-Carbon joint market

Ronghui Liu, Keyu Chen, Gaiping Sun, Shunfu Lin et autres

• VPP with CCER mechanism promotes the consumption of new energy, increases the total profit and reduces the carbon emissions in the joint market. • An improved PBDR combined with elastic coefficient is proposed, which enhances the impact of electricity price on …

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