Microgrid energy management

In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings in Chonnam National University were used.

13p nhanchienthien 25-07-2023 8 4   Download

Power load forecasting is an important issue in microgrid energy management. Accurate load forecasting is urgently required for effective power management for microgrid. This paper considers the evaluation of the effectiveness of applying different optimization algorithms to the proposed Deep Learning Neural Network, which is Wavenet.

9p viwolverine 07-07-2023 5 2   Download

This paper first describes the microgrid structure and topology in Section 0, while Section 0 presents the proposed fuzzy logic control-based energy management strategy. Simulation results are shown in Section 0, and the conclusions of this article are placed in Section 0.

5p vifalcon 16-05-2023 14 4   Download

This paper presents a development of stochastic tool to assess impacts of RES integration. Intelligent strategies to control voltage and frequency in a microgrid are also proposed. Energy management strategies for a gridconnected or isolated microgrid are developed by using dynamic programming or multiagent system.

21p vioregon2711 22-02-2021 8 3   Download