Ning Pang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Ning Pang has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Chen Shao
Hebei Provincial Key Laboratory of Distributed Energy Storage and Microgrid, North China Electric Power University, Baoding 071000, China
1 shared publication - Chunyan Rong
The State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050081, China
1 shared publication - Guangyi Li
The State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050081, China
1 shared publication - Mingyu Li
College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
1 shared publication - Shiyao Hu
The State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050081, China
1 shared publication - Yan Zhang
The State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050081, China
1 shared publication
Latest Publications
- Open Access
Optimal Integrated Energy Dispatch Method for Agricultural Parks Considering the Results of Short-Term Load Forecasting
As distributed power sources, agricultural electrical equipment, and user-side energy storage are scaled up in rural distribution networks, agricultural integrated energy systems play a key role in promoting distributed energy accommodation and economic operation. However, the uncertainty of electricity load and the diversity of connected equipment pose challenges to system optimization and scheduling. To address this, this paper proposes an optimal integrated energy scheduling method for agricultural parks that takes short-term load forecasting results into account. Firstly, a prediction model based on improved Bayesian optimization and ensemble learning is established. Compared to individual base learners, this model can effectively enhance reliability and accuracy, thus achieving a robust description of the scheduling scheme. Then, Interruptible Load (IL) resources and a reward mechanism are introduced to shift peak loads and improve the economic operation of agricultural parks. Finally, simulation analysis is carried out based on an actual microgrid in an agricultural park in North China. Results indicate that the proposed method reduces electricity costs by 1.02%, validating its effectiveness and advancement.
Open AccessOptimal Integrated Energy Dispatch Method for Agricultural Parks Considering the Results of Short-Term Load Forecasting
As distributed power sources, agricultural electrical equipment, and user-side energy storage are scaled up in rural distribution networks, agricultural integrated energy systems play a key role in promoting distributed energy accommodation and economic operation. However, the uncertainty of electricity load and the diversity of connected equipment pose challenges to system optimization and scheduling. To address this, this paper proposes an optimal integrated energy scheduling method for agricultural parks that takes short-term load forecasting results into account. Firstly, a prediction model based on improved Bayesian optimization and ensemble learning is established. Compared to individual base learners, this model can effectively enhance reliability and accuracy, thus achieving a robust description of the scheduling scheme. Then, Interruptible Load (IL) resources and a reward mechanism are introduced to shift peak loads and improve the economic operation of agricultural parks. Finally, simulation analysis is carried out based on an actual microgrid in an agricultural park in North China. Results indicate that the proposed method reduces electricity costs by 1.02%, validating its effectiveness and advancement.