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  • Open Access

    ARTICLE

    Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

    Li Wang1,*, Xiaoyong Wang2

    Energy Engineering, Vol.121, No.12, pp. 3953-3979, 2024, DOI:10.32604/ee.2024.056705 - 22 November 2024

    Abstract Plug-in Hybrid Electric Vehicles (PHEVs) represent an innovative breed of transportation, harnessing diverse power sources for enhanced performance. Energy management strategies (EMSs) that coordinate and control different energy sources is a critical component of PHEV control technology, directly impacting overall vehicle performance. This study proposes an improved deep reinforcement learning (DRL)-based EMS that optimizes real-time energy allocation and coordinates the operation of multiple power sources. Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces. They often fail to strike an optimal balance between exploration and exploitation, and… More >

  • Open Access

    ARTICLE

    A Predictive Energy Management Strategies for Mining Dump Trucks

    Yixuan Yu, Yulin Wang*, Qingcheng Li, Bowen Jiao

    Energy Engineering, Vol.121, No.3, pp. 769-788, 2024, DOI:10.32604/ee.2023.044042 - 27 February 2024

    Abstract The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the More >

  • Open Access

    ARTICLE

    Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

    Zhenzhen Zhang1,*, Qingquan Lv1, Long Zhao1, Qiang Zhou1, Pengfei Gao1, Yanqi Zhang1, Yimin Li2

    Energy Engineering, Vol.120, No.7, pp. 1637-1654, 2023, DOI:10.32604/ee.2023.026942 - 04 May 2023

    Abstract Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids. In this paper, an improved energy management strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids, and the optimal allocation of energy storage capacity is carried out by using this strategy. Firstly, the structure and model of microgrid are analyzed, and the output model of wind power, photovoltaic and energy storage is established. Then, considering the interactive power cost between the microgrid… More >

  • Open Access

    ARTICLE

    Artificial Neural Network-Based Development of an Efficient Energy Management Strategy for Office Building

    Payal Soni, J. Subhashini*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1225-1242, 2023, DOI:10.32604/iasc.2023.038155 - 29 April 2023

    Abstract In the current context, a smart grid has replaced the conventional grid through intelligent energy management, integration of renewable energy sources (RES) and two-way communication infrastructures from power generation to distribution. Energy management from the distribution side is a critical problem for balancing load demand. A unique energy management strategy (EMS) is being developed for office building equipment. That includes renewable energy integration, automation, and control based on the Artificial Neural Network (ANN) system using Matlab Simulink. This strategy reduces electric power consumption and balances the load demand of the traditional grid. This strategy is More >

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