预测电力市场中不同维度的流动性:综述

IF 1.8 Q4 ENERGY & FUELS AIMS Energy Pub Date : 2023-01-01 DOI:10.3934/energy.2023044
Sameer Thakare, Neeraj Dhanraj Bokde, Andrés E. Feijóo-Lorenzo
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引用次数: 0

摘要

<abstract><p>全球能源消耗日益增加。电是人类所发现的传输能量的最佳手段。不管它的起源如何,都可以这么说。能源传输对于确保从发电源向最终用户有效可靠地分配电力至关重要。它构成了现代社会的支柱,支撑着住宅、商业和工业活动等各个部门。能源传输是电力市场运行良好和竞争激烈的根本因素,支持可靠的供应、市场整合、价格稳定和可再生能源的整合。来自世界各地的电能每天在这些电力市场进行常规交易。本文提出了一个回顾的预测技术,日内电力市场的价格,容量和价格波动。电力市场以连续的方式运行,包括不同的组成部分,如前一天,日内和平衡市场。盘中市场与电力及时交付密切相关,便于当日电力供需交易和调整,确保电网平衡可靠。准确的预测对于交易者在日内市场中实现利润最大化至关重要,这使得预测成为电力市场管理中的一个关键问题。在这篇综述中,介绍了涉及各种机器学习和集成/混合技术的统计和计量经济学方法。总的来说,文献强调了机器学习和集成/混合模型相对于统计模型的优越性。</p></abstract>
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Forecasting different dimensions of liquidity in the intraday electricity markets: A review

Energy consumption increases daily across the world. Electricity is the best means that humankind has found for transmitting energy. This can be said regardless of its origin. Energy transmission is crucial for ensuring the efficient and reliable distribution of electricity from power generation sources to end-users. It forms the backbone of modern societies, supporting various sectors such as residential, commercial, and industrial activities. Energy transmission is a fundamental enabler of well-functioning and competitive electricity markets, supporting reliable supply, market integration, price stability, and the integration of renewable energy sources. Electric energy sourced from various regions worldwide is routinely traded within these electricity markets on a daily basis. This paper presents a review of forecasting techniques for intraday electricity markets prices, volumes, and price volatility. Electricity markets operate in a sequential manner, encompassing distinct components such as the day-ahead, intraday, and balancing markets. The intraday market is closely linked to the timely delivery of electricity, as it facilitates the trading and adjustment of electricity supply and demand on the same day of delivery to ensure a balanced and reliable power grid. Accurate forecasts are essential for traders to maximize profits within intraday markets, making forecasting a critical concern in electricity market management. In this review, statistical and econometric approaches, involving various machine learning and ensemble/hybrid techniques, are presented. Overall, the literature highlights the superiority of machine learning and ensemble/hybrid models over statistical models.

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来源期刊
AIMS Energy
AIMS Energy ENERGY & FUELS-
CiteScore
3.80
自引率
11.10%
发文量
34
审稿时长
12 weeks
期刊介绍: AIMS Energy is an international Open Access journal devoted to publishing peer-reviewed, high quality, original papers in the field of Energy technology and science. We publish the following article types: original research articles, reviews, editorials, letters, and conference reports. AIMS Energy welcomes, but not limited to, the papers from the following topics: · Alternative energy · Bioenergy · Biofuel · Energy conversion · Energy conservation · Energy transformation · Future energy development · Green energy · Power harvesting · Renewable energy
期刊最新文献
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