印度西部地区短期太阳能和风能发电预测

Dhwani Panjwani, Sanket Barhate, Rahul Rane, A. Pandey, Faruk Kazi
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引用次数: 2

摘要

随着化石燃料排放的温室气体不断增加,对环境造成危害,可再生能源成为当今世界关注的焦点。可再生能源在发电中的集成引入了可变性和斜坡事件,因为它们的间歇性会影响系统平衡、储备管理或生产机组的调度和承诺。因此,预测发电量有助于减少不确定性,这对简化发电和使用至关重要。本研究旨在利用印度西部地区负荷调度中心(WRLDC)长短期记忆(LSTM)网络收集的最新数据,预测印度西部地区几个电站的风能和太阳能发电量。在模型中引入了风电密度(WPD)和目标编码的概念。此外,本研究对最新数据提供了有希望的结果,旨在为电力系统领域的潜在研究人员提供正确的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-Term Solar and Wind Generation Forecasting for the Western Region of India
With the increased emission of greenhouse gases from fossil fuels, which endanger the environment, Renewable Energy (RE) sources have been attracting much attention in today's world. Integration of RE in power generation introduces variability and ramp events in power outputs due to their intermittent nature which affects system balancing, reserve management or scheduling and commitment of producing units. As a result, forecasting generation aids in the reduction of uncertainty, which is crucial for streamlined power generation and use. This work aims to forecast wind and solar power generation of several stations for the Western region of India using the recent data collected from the Western Region Load Dispatch Center (WRLDC) using the Long Short-Term Memory (LSTM) network. The concept of Wind Power Density (WPD) and target encoding was introduced as features in the model. Furthermore, this research offers promising results on the recent data and aims to send potential researchers in the power systems field, the right way.
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