Model Predictive Control of Micro-CSP Integrated Into a Building HVAC System for Load Following Demand Response Programs

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS

Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9106

Mohamed Toub, M. Shahbakhti, R. Robinett, G. Aniba

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引用次数: 3

Abstract

Building heat, ventilation and air conditioning (HVAC) systems are good candidates for demand response (DR) programs as they can flexibly alter their consumption to provide ancillary services to the grid and contribute to frequency and voltage regulation. One of the major ancillary services is the load following demand response (DR) program where the demand side tries to track a DR load profile required by the grid. This paper presents a real-time Model Predictive Control (MPC) framework for optimal operations of a micro-scale concentrated solar power (MicroCSP) system integrated into an office building HVAC system providing ancillary services to the grid. To decrease the energy cost of the building, the designed MPC exploits, along with the flexibility of the building’s HVAC system, the dispatching capabilities of the MicroCSP with thermal energy storage (TES) in order to control the power flow in the building and respond to the DR incentives sent by the grid. The results show the effect of incentives in the building participation to the load following DR program in the presence of a MicroCSP system and to what extent this participation is affected by seasonal weather variations and dynamic pricing.

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负荷跟随需求响应方案中微型csp集成到建筑HVAC系统的模型预测控制

建筑供暖、通风和空调(HVAC)系统是需求响应(DR)计划的理想选择，因为它们可以灵活地改变其消耗，为电网提供辅助服务，并有助于频率和电压调节。主要的辅助服务之一是负载跟随需求响应(DR)计划，其中需求方试图跟踪电网所需的DR负载概况。本文提出了一个实时模型预测控制(MPC)框架，用于将微尺度聚光太阳能(MicroCSP)系统集成到为电网提供辅助服务的办公楼暖通空调系统中进行优化运行。为了降低建筑的能源成本，设计的MPC利用了建筑HVAC系统的灵活性，以及MicroCSP的热储能(TES)调度能力，以控制建筑中的功率流，并响应电网发送的DR激励。结果显示了在MicroCSP系统存在的情况下，建筑物参与的激励措施对DR计划后负荷的影响，以及这种参与受到季节性天气变化和动态定价的影响程度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.40

自引率

66.70%

发文量

期刊介绍： This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.