Building-to-grid optimal control of integrated MicroCSP and building HVAC system for optimal demand response services

被引:2
|
作者
Toub, Mohamed [1 ]
Robinett, Rush D., III [2 ]
Shahbakhti, Mahdi [3 ]
机构
[1] Mohammed V Univ Rabat, Mohammadia Sch Engn, Ave Ibn Sina BP 765, Rabat 10090, Morocco
[2] Michigan Technol Univ, Mech Engn Dept, Houghton, MI 49931 USA
[3] Univ Alberta, Mech Engn Dept, Edmonton, AB, Canada
来源
基金
美国国家科学基金会;
关键词
ancillary services; building predictive control; demand response; MicroCSP; peak load shaving; FREQUENCY REGULATION; LOAD; ENERGY; MANAGEMENT;
D O I
10.1002/oca.2862
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The world is shifting toward cleaner and more sustainable power generation to face the challenges of climate change. Renewable energy sources such as solar, wind, hydraulic are now the go-to technologies for the new power generation system. However, these sources are highly intermittent and introduce uncertainty to the power grid which affects its frequency and voltage and could jeopardize its stable operations. The integration of micro-scale concentrated solar power (MicroCSP) and thermal energy storage with the heating, ventilation, and air conditioning (HVAC) system gives the building greater leeway to control its loads which can allow it to support the power grid by providing demand response (DR) services. Indeed, the optimal control of the power flowing between the MicroCSP, the HVAC system, and the thermal zones can bring additional degrees of freedom to the building which can be relegated to the power grid based on the objective function and the incentives provided by the latter. This article presents an in-depth investigation of the MicroCSP potential to provide ancillary services to the power grid. It focuses on evaluating the effect of incentives provided by the power grid on the building participation to the load following programs. It also demonstrates how the MicroCSP can help the building deal with constraints related to load peak shaving and ramp-rate reduction set by the power grid as part of long-term DR contracts. A sensitivity analysis is carried out to confront the results to prediction uncertainties of the energy prices and the weather conditions.
引用
收藏
页码:866 / 884
页数:19
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