Bi-level scheduling model for a novel virtual power plant incorporating waste incineration power plant and electric waste truck considering waste transportation strategy

焚化 卡车 可再生能源 虚拟发电厂 废物管理 发电站 工程类 电力 废物收集 废物转化为能源 汽车工程 城市固体废物 功率(物理) 分布式发电 电气工程 物理 量子力学
作者
Dongqing Jia,Zhong Shen,Xingmei Li,Xiaoyan Lv
出处
期刊:Energy Conversion and Management [Elsevier BV]
卷期号:298: 117773-117773 被引量:10
标识
DOI:10.1016/j.enconman.2023.117773
摘要

Aggregating waste incineration plants, electric waste trucks, and renewable energy sources into virtual power plants is important to promote renewable energy utilization and sustainable waste disposal. However, electric waste trucks must perform daily waste transportation tasks while participating in virtual power plant scheduling. Therefore, coordinating the relationship between the two has become a key to the stable operation of the virtual power plant systems. This study constructed a novel virtual power plant system incorporating waste incineration plants and electric waste trucks. The transportation strategy of the electric waste truck and the scheduling strategy of the virtual power plant were simultaneously considered through a bi-level programming model. The simulation results show that: (1) the proposed virtual power plant's revenue increased by 19.59%, and electric waste truck operating costs decreased by 45.91% compared to independent operations; (2) the of revenue plant increased by only 5.81% when electric waste trucks fully adhered to the virtual power plant schedule before performing waste transportation tasks, but electric waste truck costs increased by 27.14% compared to the proposed bi-level programming model. In conclusion, this bi-level programming model effectively balances the interests of various stakeholders, promotes efficient waste resource utilization, and enhances municipal solid waste removal efficiency. The proposed virtual power plant planning scheme fully utilizes renewable energy and waste resources, improves waste utilization efficiency, and provides innovative ideas for renewable energy consumption.
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
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
haix应助liu采纳,获得30
刚刚
朱佳慧完成签到,获得积分10
刚刚
今后应助负责的梦蕊采纳,获得10
1秒前
2秒前
2秒前
2秒前
852应助胖虎啊采纳,获得10
2秒前
2秒前
细腻的谷秋完成签到 ,获得积分10
3秒前
lulu完成签到,获得积分20
3秒前
raolixiang发布了新的文献求助10
3秒前
lllll发布了新的文献求助10
4秒前
4秒前
Wei发布了新的文献求助10
5秒前
Orange应助AIMS采纳,获得10
5秒前
yy发布了新的文献求助10
6秒前
科研通AI5应助YuF采纳,获得30
6秒前
6秒前
6秒前
REBACK发布了新的文献求助10
6秒前
科研通AI5应助ni采纳,获得10
6秒前
7秒前
rora完成签到 ,获得积分10
7秒前
lllll完成签到,获得积分10
8秒前
8秒前
充电宝应助金雪采纳,获得10
9秒前
上官若男应助小酒窝采纳,获得10
9秒前
9秒前
吃猫的鱼发布了新的文献求助10
10秒前
10秒前
1111完成签到,获得积分10
10秒前
Little发布了新的文献求助10
11秒前
11秒前
李健应助儒雅新波采纳,获得10
11秒前
迷路诗蕊发布了新的文献求助10
11秒前
tomato039完成签到,获得积分10
12秒前
徐先生1106完成签到,获得积分10
12秒前
科研通AI5应助DK采纳,获得10
13秒前
13秒前
洪对对发布了新的文献求助10
13秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
English language teaching materials : theory and practice 200
Parallel Optimization 200
Deciphering Earth's History: the Practice of Stratigraphy 200
New Syntheses with Carbon Monoxide 200
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3835595
求助须知:如何正确求助?哪些是违规求助? 3377959
关于积分的说明 10501323
捐赠科研通 3097529
什么是DOI,文献DOI怎么找? 1705876
邀请新用户注册赠送积分活动 820756
科研通“疑难数据库(出版商)”最低求助积分说明 772226