Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties

解算器 数学优化 元启发式 分类 计算机科学 可再生能源 软件 遗传算法 多目标优化
作者
Zahra Ghaemi,Thomas T.D. Tran,Amanda D. Smith
出处
期刊:Applied Energy [Elsevier BV]
卷期号:321: 119400-119400
标识
DOI:10.1016/j.apenergy.2022.119400
摘要

District energy systems (DES) can reduce CO 2 emissions associated with buildings while meeting the energy needs of a group of buildings with fossil fuel or renewable energy resources that are located on-site. One of the present challenges of DES is optimizing the operation of energy components, as different optimization methods are available. These optimization methods can have various requirements for implementation, distinct needs for engineering labor, and may rely on freely accessible software or proprietary software. Most importantly, different methods may result in dissimilar operation planning for a given DES, which makes the selection of optimization method a key consideration for decision-makers. In this study, two optimization methods, a mixed-integer linear programming (MILP) solver as a classical method and a non-dominated sorting genetic algorithm II (NSGA-II) as a metaheuristic method, are used to optimize the early-stage operation planning of a hypothetical DES for a university campus in a cool and dry climate. The objective is to minimize the operating cost and CO 2 emissions when considering uncertainties in energy demands, solar irradiance, wind speed, and annualized electricity-related emissions. Both methods present similar operation of energy components, operating cost, and operating CO 2 emissions. The MILP solver and NSGA-II algorithm vary in computation time to perform the optimization, initial knowledge to run the simulation, accessibility (free/open-source status), and satisfaction of constraints. This work compares the characteristics of a MILP solver and NSGA-II algorithm to help future researchers select the suitable optimization method related to their case study. The software underlying this work is open-source and publicly available to be reused and customized for early-stage operation planning of their specific DES. This work is novel by optimizing the operation planning of a mixed-used DES to minimize the cost and CO 2 emissions while considering uncertainties in weather parameters, energy demands, and annualized electricity-related emissions. • Multi-objective optimization of district energy system performed by MILP and NSGA-II. • Uncertainties in energy demands, meteorology, and emissions are considered. • Results of operation planning are similar between MILP and NSGA-II. • Highly variable renewable sources do not cause high variability in cost or emissions. • An open source framework is presented to help optimize district energy systems.
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
布鲁克完成签到,获得积分10
1秒前
1秒前
量子星尘发布了新的文献求助10
2秒前
今后应助朴实的绣连采纳,获得30
2秒前
<小天才>发布了新的文献求助10
4秒前
4秒前
5秒前
Smy完成签到 ,获得积分10
5秒前
在水一方应助梁晓雯采纳,获得10
6秒前
Yy123发布了新的文献求助10
6秒前
tao发布了新的文献求助10
6秒前
3237924531完成签到,获得积分10
6秒前
健忘小霜完成签到,获得积分10
7秒前
8秒前
scholar完成签到,获得积分10
9秒前
wei发布了新的文献求助10
9秒前
鳗鱼灵阳完成签到,获得积分20
10秒前
10秒前
11秒前
无情的聋五完成签到 ,获得积分10
11秒前
Owen应助QQiang6采纳,获得10
12秒前
12秒前
SciGPT应助wudizhuzhu233采纳,获得10
12秒前
夏天应助wudizhuzhu233采纳,获得150
12秒前
不宁不令发布了新的文献求助20
12秒前
戴佳伟彩笔完成签到,获得积分10
13秒前
13秒前
英俊的绮波完成签到,获得积分10
13秒前
13秒前
13秒前
Ava应助Yy123采纳,获得10
13秒前
15秒前
科目三应助科研小贩采纳,获得10
15秒前
lll发布了新的文献求助10
17秒前
mingming发布了新的文献求助10
18秒前
核桃应助火星上念梦采纳,获得10
18秒前
顾矜应助常芹采纳,获得10
18秒前
18秒前
sunny发布了新的文献求助10
18秒前
杨立方发布了新的文献求助10
18秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
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 3988838
求助须知:如何正确求助?哪些是违规求助? 3531250
关于积分的说明 11252914
捐赠科研通 3269838
什么是DOI,文献DOI怎么找? 1804820
邀请新用户注册赠送积分活动 881943
科研通“疑难数据库(出版商)”最低求助积分说明 809028