INTRODUCTION
Recent power blackouts, constraints on the transmission and distribution (T&D) infrastructure and the inability of power merchants to raise capital for new construction are creating new challenges and opportunities. Widespread use of distributed generation (DG) and combined cooling, heating, and power (CHP) technologies for buildings could provide much needed relief. Although recent technology advancements have made CHP a viable option, there are several challenges that need to be overcome before CHP technologies are universally adopted in the commercial buildings sector.
Because they rely on interactions among systems, CHP technologies are more complex than any existing building systems. Unless the various components of these systems work as an integrated unit, delivering the promised performance, their full market penetration potential will not be realized and could be damaged if early installations encounter operation problems. Integration of these technologies with existing building systems brings additional challenges that need to be addressed as well. Finally, many commercial buildings lack adequate control infrastructure, properly trained building operators, and proven operations and maintenance practices for reliable and optimal operation of these systems.
The U.S. Department of Energy (DOE) and others (
Kramer 2004, Patnaik 2004, and Rosfjord 2004) are working on overcoming many of the challenges facing CHP technologies; however, issues associated with system integration, supervisory controls, and integration of CHP and building systems have not yet been adequately addressed.
This article highlights challenges associated with integration of CHP systems with existing buildings and maintaining their performance over time. The article also identifies key research and development needs to address the challenges, so that CHP technologies can deliver the promised performance and reach their full potential market penetration.
WHY CHP?
Overall efficiency of power generation in the US has remained stagnant at about 32 percent since 1960 (http://uschpa.admgt.com/vision2020.pdf). Because CHP systems utilize waste heat from power generation for heating or cooling, the overall efficiency can be significantly greater than 32 percent (>50 percent for many systems). In addition, electric transmission and distribution losses are almost non-existent because the power is typically used locally where it is generated.
A typical CHP system consists of a generator, a heat exchanger to recover heat from the generator exhaust and an absorption chiller system to generate chilled water. If there is a need for dehumidification, the waste heat from the absorption chiller can be used to regenerate a desiccant. A typical CHP installation is shown in Figure 1. Although fossil-fuel-powered DG technologies are still in their infancy serving niche markets (e.g., emergency, remote, backup and other special power needs), they have a great potential in a deregulated electric-utility environment and where demand cost is a significant fraction of the total electricity cost.
Other societal benefits from widespread use of distributed generation technologies, and CHP in particular, can help mitigate the impacts of electricity price volatility. Widespread use of DG for electric power would also enhance the reliability of the grid and alleviate T&D bottlenecks by moving more of the required generation near the point of end use, putting less burden on the T&D system.
Figure 1: Microturbine Generator and Heat Recovery Heat Exchanger Installed at a Supermarket in Hauppage, N.Y.
CHP CHALLENGES
Major challenges for widespread adoption of CHP include: 1) higher performance technology at lower first cost, 2) grid interconnection technologies and standards, 3) regulatory and policy issues, 4) system integration issues and 5) issues related to integration with existing buildings.
Given the current state of operations in many commercial buildings, integrating DG technologies with existing building systems presents a major challenge.
CURRENT STATE OF BUILDING OPERATIONS
Although no reliable nationwide estimates are available, many case studies in limited geographic regions over the past decade have shown that a significant fraction (as much as 30 percent) of the energy consumed in commercial buildings is unnecessarily wasted (
Ardehali et al. 2003; Ardehali and Smith 2002; Claridge et al. 2000, 1996, and 1994). Much of the waste can be related to the inability to control, maintain, detect, diagnose and correct operation problems with buildings and their systems.
Available evidence shows extensive equipment performance problems in commercial buildings and that an energy-efficient building stock will not result from solely designing efficient buildings and installing efficient equipment; good operation and maintenance of the building and associated equipment are needed. Operational problems lead to inefficiencies (increasing energy use and cost), a loss in cooling/heating capacity (leading to inability to maintain occupant comfort), inability to maintain occupant comfort (causing loss of occupant productivity and loss of tenants), and increased equipment down time (decreased reliability). These performance problems are not inherent in high-efficiency equipment, but instead result from errors in installation and operation of complex building heating/cooling systems, and particularly, their controls.
WHY SUPERVISORY CONTROLS AND DIAGNOSTICS ARE RELEVANT
To realize the potential energy savings and societal benefits that DOE foresees from CHP requires its rapid acceptance and penetration into the buildings sector. To accomplish this, suppliers must produce flexible, integrated systems quickly, inexpensively, and reliably, while honoring the OEMs' suggested ranges and absolute limits for equipment operating conditions. So, there is as great a need for plug-and-play controls as there is for physical compatibility among the equipment.
Ensuring the high level of performance that will guarantee continued consumer acceptance requires continuous, on-board performance diagnostics for both component-level performance degradation and failures to overall system performance. Equipment level diagnostics from different OEMs will need to be integrated with each other to achieve integrated system-level diagnostics. Maintaining component and system performance over time is a major challenge to efficient operation of building systems.
Many of the operational and integration issues can be addressed by yet-to-be-developed supervisory control and automated diagnostic algorithms. These algorithms can then be used as the basis for automated tools that help the building manager or energy service provider better manage complex CHP systems and their interactions with existing building systems. Three major functional requirements for such supervisory controls and diagnostics are listed and described below:
1. Provide continuous feedback to operators on system performance using easily understood performance metrics;
2. Automatically detect, diagnose, and project system and equipment degradation and faults using algorithms for automated fault detection, diagnostics and prognostics for components and systems;
3. Provide support for optimization and load balancing using adaptive predictive controls and automated decision support tools.
CONTINUOUS PERFORMANCE FEEDBACK
Although providing performance feedback to operators or energy service providers managing CHP systems will not guarantee optimal operations, together with automatic control under normal circumstances, it will provide the performance information that will enable operators to recognize anomalous situations requiring action.
Performance feedback can be in the form of:
1. Initial commissioning score: An automated commissioning tool that would score the initial performance (as soon as a system is installed) by:
a. Comparing actual performance (energy use and efficiency) to expected performance;
b. Estimating expected performance using manufacturers' specified performance data;
c. Providing comparisons of the performance of individual components and the system as a whole.
2. Dynamic and static performance feedback: An automated tool that would monitor the performance and provide continuous real-time feedback to operators by reporting:
a. Operating conditions;
b. Performance of individual components and the system as a whole;
c. Performance information at different resolutions (hourly, daily, monthly, yearly);
d. Information on costs and how they compare to similar situations experienced historically.
AUTOMATED DIAGNOSTICS AND PROGNOSTICS
Automated fault detection and diagnosis (AFDD) is an automatic process by which faulty operation, degraded performance, and failed components in a physical system are detected, understood and reported.
The AFDD tool may be either passive, analyzing operation of the equipment/system as it operates, without altering any of its set points or control outputs, or active, automatically initiating changes to produce or simulate operating conditions that cover a wider range of conditions than might be experienced for a considerable time under normal operation.
Even if the integrated system is commissioned during installation, this does not ensure continued proper operation. Only continuous monitoring of the status of the equipment and its performance can ensure continued proper operation.
AFDD systems are central to this continuous monitoring and commissioning process by constantly monitoring equipment and identifying failures or degradation in performance. Further, prognostic tools can inform operators and maintenance personnel regarding the time before failure or significant performance degradation, enabling personnel to anticipate and plan for maintenance. The human operator or repair person is still critical to completing the commissioning and maintenance cycles, but without the automated systems monitoring continuously, problems can go undetected for days, weeks, months, or even years and none can be anticipated in advance.
The functional needs for diagnostic algorithms are:
1. Component level diagnostics: Diagnostic algorithms that monitor component performance on a continuous basis to detect and diagnose faults at the component level.
2. System level diagnostics: Even if individual systems are operating properly, the system as a whole may not be operating optimally. Therefore, there is a need for diagnostic algorithms that monitor whole-system performance on a continuous basis and detect and diagnose faulty and degraded operation.
3. Building integration diagnostics: Because the thermal output is integrated with existing chilled and hot water distribution loops, there is a need to ensure that the performance of the integrated system is optimal.
4. Prognostics: These tools are needed to enable operation and maintenance personnel to anticipate and plan for repair and maintenance to maintain performance and minimize down time.
Diagnostic and prognostic tools:
a. compliment manufacturer-provided onboard diagnostics;
b. use simple graphical user interfaces that require minimal configuration and can be interpreted at a glance;
c. clearly highlight anomalous or faulty operation;
d. report problems by automatically alerting (e.g., by paging or emailing) operators and contractors when major problems arise.
ADAPTIVE PREDICTIVE CONTROL
In a deregulated utility environment, adaptive and predictive control algorithms will be needed to help operators and managers make informed decisions. Economic optimization and dispatch control algorithms are required to make use of forecasts (e.g., for load of the building, energy prices, and weather) to make autonomous decisions on whether to generate power locally or to buy power from the grid. In addition, these algorithms can be used to significantly improve plant efficiency by optimizing equipment and resource utilization.
CONCLUSIONS
Distributed generation in general and CHP systems in particular can fundamentally transform the delivery mechanism for electric power by significantly improving the reliability of the power grid and increasing the overall efficiency of energy conversion. However, for CHP technologies and systems to realize their full market potential, significant challenges must be overcome in the next few years, including the development of supervisory controls, automated diagnostics and prognostics, and adaptive predictive controls as described in this article. The successful development and deployment of such advanced system controls and predictive algorithms will ensure that CHP systems installed in commercial buildings will perform reliably and cost effectively.
References
Ardehali, M.M. and T.F. Smith. 2002.
Literature Review to Identify Existing Case Studies of Controls-Related Energy-Inefficiencies in Buildings. Technical Report: ME-TFS-01-007. Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, Iowa.
Ardehali, M.M., T.F. Smith, J.M. House, and C.J. Klaassen. 2003. "Building Energy Use and Control Problems: An Assessment of Case Studies."
ASHRAE Transactions, Vol. 109, Pt. 2, 2003.
Claridge, D.E., C.H. Culp, M. Liu, S. Deng, W.D. Turner, and J.S. Haberl. 2000. "Campus-Wide Continuous Commissioning of University Buildings." In
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Sidebar:
Cooling, Heating, and Power Integration Laboratory
Oak Ridge National Laboratory's (ORNL) Cooling, Heating, and Power (CHP) Integration Laboratory provides a research and development test bed for improving the energy efficiency and utility load characteristics of CHP equipment and the integration of components into packaged systems. The charter of the CHP Integration Laboratory calls for it to help industry expand and encourage the use of distributed energy generation and CHP by developing and testing CHP technologies and educating users on their application and benefits.
The CHP Integration Laboratory tests the performance of individual CHP components and integrated systems within the facility's thermal loop. It provides unique capabilities for testing CHP integration under various operating performance modes and configurations. The facility brings together in one location many closely related experimental research capabilities, including a number of unique tools for research on CHP and thermally activated technologies. The laboratory can configure power-generating units such as microturbines, engines, and fuel cells and operate them with and without waste heat recovery from the exhaust. The system configuration, presently set up with a 30-kW gas-fired microturbine, can be extended to test different types and sizes of generating equipment.
Testing at the ORNL CHP Integration Laboratory will lead to the development of the integrated energy system (IES) Design Optimization Model. Use of this model is underway to quantify the quantity and quality of thermal resource that is potentially available from a given amount of electrical generation from an IES. This method of analysis will be used to characterize the operating characteristics of the various components involved in an integrated CHP system (e.g., prime mover, exhaust heat exchanger, absorption chiller, and desiccant unit) and to determine expected steady-state conditions based upon thermodynamic behavior of the system.
The goal is to develop a method to quickly estimate the amount of thermal energy available and quality of the thermal stream (e.g., temperature) based upon a minimum amount of input regarding the CHP system elements. From this effort, various CHP system configurations can be evaluated for their potential use in a given application. Throughout all the testing at the facility, performance data have been collected on individual components and overall CHP systems. The test results have been used to optimize the design and performance of components and systems, reducing the potential risk to businesses and industries that are manufacturing and operating CHP systems.
Plans for future work at the CHP Integration Laboratory include research and development in the areas of assessment of equipment controls, advanced diagnostics, and thermal energy storage, as well as tests on different types and sizes of generating equipment.
