A novel structural adaptive discrete grey prediction model and its application in forecasting renewable energy generation

计算机科学 粒子群优化 可再生能源 数学优化 网格 非线性系统 电力系统 机器学习 功率(物理) 数学 工程类 物理 几何学 量子力学 电气工程
作者
Wuyong Qian,Aodi Sui
出处
期刊:Expert Systems With Applications [Elsevier BV]
卷期号:186: 115761-115761 被引量:46
标识
DOI:10.1016/j.eswa.2021.115761
摘要

The rapidly growing renewable energy generation instigates stochastic volatility of electricity supply that may compromise the power grid's stability and increase the grid imbalance cost. Therefore, accurate mid-to-long term renewable energy generation forecasting is of great significance for integrating renewable energy systems with smart grid and energy strategic planning. For this purpose, a new structural adaptive discrete grey prediction model is proposed. Overall, the proposed model possesses three main contributions. Firstly, the introduction of nonlinear term and periodic term strengthens the ability of the traditional DGM (1,1) model to capture the nonlinear and linear development trend of time series and improves the adaptability of the grey prediction model to arbitrary periodic time series. Secondly, the emerging coefficients are determined by the particle swarm optimization algorithm and hold-out cross-validation method, and the adaptive selection of the model structure is realized. From the perspective of expert system, it reduces the need for modeling knowledge. Thirdly, the consistency of stretching, unbiasedness, and compatibility with other grey models are discussed, which further verified the feasibility and practicability of the proposed model. Besides, the performance of the proposed model is compared with those of a series of grey prediction models and non-grey prediction methods to verify the feasibility and superiority of this new approach by three real cases. The results indicate that the proposed model benefits from its adaptive structure and produces reliable predictions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2023204306324完成签到,获得积分20
刚刚
依灵完成签到,获得积分10
2秒前
香蕉觅云应助7733采纳,获得10
2秒前
5秒前
小猪完成签到,获得积分10
5秒前
7秒前
萌面大侠完成签到,获得积分10
7秒前
7秒前
金枪鱼完成签到,获得积分10
8秒前
sssssssssss完成签到,获得积分10
8秒前
mary发布了新的文献求助10
10秒前
研友_VZG7GZ应助hahaha123213123采纳,获得10
10秒前
枕星发布了新的文献求助10
12秒前
12秒前
13秒前
13秒前
求求大家了完成签到,获得积分10
13秒前
阳光完成签到,获得积分10
13秒前
Crystal完成签到 ,获得积分10
15秒前
16秒前
16秒前
17秒前
17秒前
17秒前
乐乐应助赖道之采纳,获得10
18秒前
18秒前
Sun_Chen完成签到,获得积分10
18秒前
体贴凌柏发布了新的文献求助10
19秒前
成就的笑南完成签到 ,获得积分10
19秒前
20秒前
20秒前
wyw123完成签到,获得积分10
20秒前
求大佬帮助完成签到,获得积分10
20秒前
李健的小迷弟应助zyq采纳,获得10
21秒前
陈隆完成签到,获得积分10
21秒前
哎呀完成签到 ,获得积分10
21秒前
量子星尘发布了新的文献求助10
22秒前
mary完成签到,获得积分10
22秒前
22秒前
朱成豪发布了新的文献求助10
24秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038368
求助须知:如何正确求助?哪些是违规求助? 3576068
关于积分的说明 11374313
捐赠科研通 3305780
什么是DOI,文献DOI怎么找? 1819322
邀请新用户注册赠送积分活动 892672
科研通“疑难数据库(出版商)”最低求助积分说明 815029