Deep Reinforcement Learning Based Optimal Energy Management of Multi-energy Microgrids with Uncertainties

no code implementations • 30 Nov 2023 • Yang Cui, Yang Xu, Yang Li, Yijian Wang, Xinpeng Zou

To help EMS formulate optimal dispatching schemes, a deep reinforcement learning (DRL)-based MEMG energy management scheme with renewable energy source (RES) uncertainty is proposed in this paper.

energy management Management +1

Short-term power load forecasting method based on CNN-SAEDN-Res

no code implementations • 2 Sep 2023 • Yang Cui, Han Zhu, Yijian Wang, Lu Zhang, Yang Li

In this method, feature extraction module is composed of a two-dimensional convolutional neural network, which is used to mine the local correlation between data and obtain high-dimensional data features.

Load Forecasting Time Series

Collaborative Optimization of Multi-microgrids System with Shared Energy Storage Based on Multi-agent Stochastic Game and Reinforcement Learning

no code implementations • 19 Jun 2023 • Yijian Wang, Yang Cui, Yang Li, Yang Xu

The proposed MMG system framework can reduce energy fluctuations in the main grid by 1746. 5kW in 24 hours and achieve a cost reduction of 16. 21% in the test.

ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech

1 code implementation • 30 Dec 2022 • Zehua Chen, Yihan Wu, Yichong Leng, Jiawei Chen, Haohe Liu, Xu Tan, Yang Cui, Ke Wang, Lei He, Sheng Zhao, Jiang Bian, Danilo Mandic

Denoising Diffusion Probabilistic Models (DDPMs) are emerging in text-to-speech (TTS) synthesis because of their strong capability of generating high-fidelity samples.

Denoising