遵循“负荷预测-机理仿真-软件模拟-协同优化”的技术路线,在运用DeST软件预测上海某酒店全年逐时冷、热负荷、PVsyst软件计算光伏发电量和构建燃气轮机仿真模型计算能源输出的基础上,将上述计算结果输入预先构建的太阳能“冷-热-电”联供系统运行优化模型中,得到合理、可行的系统供能方案。相较于传统优化模型,运用集成方法得到的调度方案更有利于实现能源供需平衡,可为其他类似系统的运行和管理提供很好的示范。
Abstract
Accurate architecture-load prediction and equipment-output calculation are the key to realize the operation optimization of integrated energy system. In this paper, the procedure of “load prediction-device simulation-software simulation-collaborative optimization” was firstly designed. Secondly, DeST software was used to predict the cooling and heating load and PVsyst software was exploited to calculate the photovoltaic power. Next, the power output of gas turbine was estimated by aid of simulation model. Finally, the obtained results based on above three processes were incorporated into pre-established operation optimization model in order to generate reasonable and efficient energy-provision scheme. Compared with traditional optimization model, the schedule pattern based on integrated method was beneficial to achieve balance between energy supply and demand, also was capable of providing a good demonstration for the operation and management of other similar systems.
关键词
太阳能 /
燃气轮机 /
负荷预测 /
CCHP /
设备仿真 /
集成建模
Key words
solar energy /
gas turbine /
load forecasting /
CCHP /
device simulation /
integrated modelling
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] BUENO B, NORFORD L, PIGEON G, et al.A resistance-capacitance network model for the analysis of the interactions between the energy performance of buildings and the urban climate[J]. Building and environment, 2012, 54: 116-125.
[2] 于水, 常忠浩, 杨江辉. 基于TRNSYS的太阳能-天然气冷热电三联供最优配比研究[J]. 沈阳建筑大学学报(自然科学版), 2021, 37(2): 324-329.
YU S, CHANG Z H, YANG J H.Optimal ratio of solar-gas cooling,heating and power triple supply based on TRNSYs[J]. Journal of Shenyang Jianzhu University(Natural Science), 2021, 37(2): 324-329.
[3] ASSAF S, NOUR M.Potential of energy and water efficiency improvement in Abu Dhabi’s building sector- analysis of Estidama pearl rating system[J]. Renewable energy, 2015, 82: 100-107.
[4] HUANG H, NAZI W I B W, YU Y, et al. Energy performance of a high-rise residential building retrofitted to passive building standard-A case study[J]. Applied thermal engineering, 2020, 181: 115902.
[5] 付嘉衡, 宋梦宇, 田晓亮. 青岛某办公建筑供热改造工程技术经济分析[J]. 热科学与技术, 2021, 20(2): 200-208.
FU J H, SONG M Y, TIAN X L.Technical and economic analysis of heating renovation project of an office building in Qingdao[J]. Journal of thermal science and technology, 2021, 20(2): 200-208.
[6] 冯国会, 崔航, 黄凯良, 等. 严寒地区超低能耗建筑负荷特性研究[J]. 沈阳建筑大学学报(自然科学版), 2021, 37(4): 724-729.
FENG G H, CUI H, HUANG K L, et al.Load characteristics of ultra low energy consumption building in severe cold area[J]. Journal of Shenyang Jianzhu University(Natural Science), 2021, 37(4): 724-729.
[7] GOU X, ZHANG H, LI G Y, et al.Dynamic simulation of a gas turbine for heat recovery at varying load and environment conditions[J]. Applied thermal engineering, 2021, 195: 117014.
[8] MOHAMMADIAN P K, SAIDI M H.Simulation of startup operation of an industrial twin-shaft gas turbine based on geometry and control logic[J]. Energy, 2019, 183: 1295-1313.
[9] 赵星竹. 屋顶并网光伏发电系统优化设计与验证[D]. 沈阳: 沈阳工程学院, 2019.
ZHAO X Z. optimization design and verification of rooftop grid-connected photovoltaic power generation system[D]. Shenyang: Shenyang Institute of Engineering, 2019.
[10] 蒋欢. 基于数值模拟的光伏茶园光环境分析[D]. 杭州:浙江大学, 2018.
JIANG H.Analysis of lighting environment of photovoltaic tea garden based on numerical simulation[D]. Hangzhou: Zhejiang University, 2018.
[11] CAO Y, DHAHAD H A, TOGUN H, et al.Exergetic and economic assessments and multi-objective optimization of a modified solar-powered CCHP system with thermal energy storage[J]. Journal of building engineering, 2021, 43: 102702.
[12] YANG G, ZHAI X Q.Optimization and performance analysis of solar hybrid CCHP systems under different operation strategies[J]. Applied thermal engineering, 2018, 133: 327-340.
[13] 吴鸣, 骆钊, 季宇, 等. 基于模型预测控制的冷热电联供型微网动态优化调度[J]. 中国电机工程学报, 2017, 37(24): 7174-7184.
WU M, LUO Z, JI Y, et al.Optimal dynamic dispatch for combined cooling heating and power microgrid based on model predictive control[J]. Proceedings of the CSEE, 2017, 37(24): 7174-7184.
[14] 段成俊. 区域综合能源系统负荷预测和优化调度研究[D]. 镇江: 江苏大学, 2020.
DUAN C J.Research on load forecasting and optimal scheduling of regional integrated energy system[D]. Zhenjiang: Jiangsu University, 2020.
基金
国家重点研发计划（2018YFE0208400）; 国家电网有限公司总部科技项目《面向跨境互联的多能互补新型能源系统关键技术研究》
PDF(1884 KB)
