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Optimal Scheduling of Off-Site Industrial Production in the Context of Distributed Photovoltaics

Author

Listed:
  • Sizhe Xie

    (Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Yao Li

    (Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Peng Wang

    (Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

A reasonable allocation of production schedules and savings in overall electricity costs are crucial for large manufacturing conglomerates. In this study, we develop an optimization model of off-site industrial production scheduling to address the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China’s power supply, and the difficulty in promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and variations in electricity prices in different places to optimize the scheduling of industrial production in various locations. The model is embedded with two sub-models, i.e., an electricity price prediction model and a distributed photovoltaic power cost model to complete the model parameters, in which the electricity price prediction model utilizes a Long Short-Term Memory (LSTM) neural network. Then, the particle swarm optimization algorithm is used to solve the optimization model. Finally, the production data of two off-site pharmaceutical factories belonging to the same large group of enterprises are substituted into the model for example analysis, and it is concluded that the optimization model can significantly reduce the electricity consumption costs of the enterprises by about 7.9%. This verifies the effectiveness of the optimization model established in this paper in reducing the cost of electricity consumption on the demand side.

Suggested Citation

  • Sizhe Xie & Yao Li & Peng Wang, 2024. "Optimal Scheduling of Off-Site Industrial Production in the Context of Distributed Photovoltaics," Energies, MDPI, vol. 17(9), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2156-:d:1387157
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    References listed on IDEAS

    as
    1. Xue, Liya & Liu, Junling & Lin, Xiaojing & Li, Mengyue & Kobashi, Takuro, 2024. "Assessing urban rooftop PV economics for regional deployment by integrating local socioeconomic, technological, and policy conditions," Applied Energy, Elsevier, vol. 353(PA).
    2. Schwidtal, Jan Marc & Agostini, Marco & Coppo, Massimiliano & Bignucolo, Fabio & Lorenzoni, Arturo, 2023. "Optimized operation of distributed energy resources: The opportunities of value stacking for Power-to-Gas aggregated with PV," Applied Energy, Elsevier, vol. 334(C).
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