Nelson Fumo

Cooling, heating, and power energy performance for system feasibility:

Abstract Buildings with heating and cooling energy requirements are usually supplied by separated systems such as furnaces or boilers for heating, and vapour compression systems for cooling. For these types of buildings, the use of cooling, heating, and power (CHP) systems is an alternative for energy savings. Different investigations have claimed that the use of CHP systems reduces the energy consumption related to transmission and distribution of energy. However, most of these analyses are based on the reduction of operating cost without measuring the actual energy use reduction. In this study, the definition of building primary energy ratio (BPER) is introduced as a new parameter to evaluate the CHP energy performance. BPER measures the variation of the building primary energy (BPE) when the building is operated without a CHP system versus the BPE when a CHP system is used. Results show that using the thermal efficiency alone is not the best approach to describe the CHP system energy performance and that using the BPER provides a more comprehensive CHP evaluation. For this investigation, values of BPER greater than 1 indicate that primary energy is being saved for that specific time, which makes this concept a reliable tool for the CHP design and operational control.

Methodology to perform a non-conventional evaluation of cooling, heating, and power systems

Abstract Cooling, heating, and power (CHP) is a distributed generation technology that can provide electricity and heat while improving the overall thermal energy efficiency of a building. The evaluation and comparison of this technology versus conventional technologies cannot be limited to economical considerations only. Therefore, a non-conventional evaluation, based on non-economical aspects, is necessary to show the additional benefits that can be obtained from the CHP technology. A non-conventional evaluation includes aspects such as: environmental quality, energy-efficient buildings, power reliability, power quality, fuel source flexibility, etc. Some benefits of these non-conventional evaluations can be factored into an economic evaluation but others give intangible potential to the technology. The current paper presents a methodology to evaluate CHP systems based on two non-conventional aspects: energy-efficient buildings and emission of pollutants. Using the methodology described in the current paper it can be demonstrated that the use of CHP systems could improve the Energy Star rating of a building in more than 50 points. The improvement on the Energy Star rating is significant on the Leadership in Energy and Environmental Design rating as a building can score up to ten points of the 23 available in the energy and atmosphere category on energy efficiency alone. As much as eight points can be obtained in this category due to the Energy Star rating increment from the use of CHP systems. Also, using the proposed methodology it can be demonstrated that CHP systems have the ability to significantly reduce emission of pollutants. For carbon dioxide a reduction around 50 per cent can be reached, for nitrogen oxides the reduction can be in the order of 75 per cent, while for sulphur dioxide the reduction is higher than 90 per cent.

Analysis of combined cooling, heating, and power systems operating following the electric load and following the thermal load strategies with no electricity export

Technologies such as cogeneration and trigeneration have great potential for energy and emission reduction because these technologies make better use of fuels by recovering waste heat to satisfy thermal loads. Operation of a system that involves several types of equipment operating as one unit, that at the same time interact with the building to meet its energy demand, requires an operational strategy that makes the system operate properly. This means the system must be able to respond to the building energy demand while having the best performance within the constraints imposed by the operational strategy. When a cogeneration system (combined heating and power) or trigeneration system (combined cooling, heating, and power) operates at partial load, the operational strategy has particular effect on the performance of the system. Two common operational strategies to operate these systems are following the electric load and following the thermal load. This article presents a methodology that allows selecting the right operational strategy based on the ratio between the building electric and thermal loads, and the ratio between electricity demand and size of the power generation unit when exporting electricity is not an option. Results show that the following the thermal load strategy seems to be better than the following the electric load strategy for most cases. Therefore, the methodology presented in this article is a decision-making tool for the selection of the right operational strategy.

Hybrid-cooling, combined cooling, heating, and power systems

Abstract Combined cooling, heating, and power (CCHP) systems have the ability to optimize fuel consumption by recovering thermal energy from the prime mover of the power generation unit (PGU). Design of a CCHP system requires consideration, among other variables, of CCHP system components size and type. This study focuses on the analysis of hybrid-cooling, heating, and power (hybrid-cooling CCHP) systems that have an absorption chiller (CH) and a vapour compression system to handle the cooling load. The effect of the size of both cooling mechanisms is analysed in conjunction with the PGU size and efficiency. For better energy performance analysis simulations, results are presented based on the building-CCHP system primary energy consumption (PEC). Hybrid-cooling CCHP systems yield higher primary energy reduction than CCHP systems with an absorption CH alone. To account for the effect of climate conditions, hot and cold climates were considered by performing simulations for Tampa and Chicago weather conditions. The results are presented in tabular form to show the value of the PEC reduction as a function of the PGU size and efficiency, and the size of the absorption CH.

Impact of CHP System Component Efficiencies on the Economic Benefit of CHP Systems Using Spark Spread Analysis

A combined heating and power system (CHP) can take the place of a conventional system with separate heating and power (SHP) where electricity is purchased from the grid. The CHP system provides electrical energy through a prime mover located near the building it serves, and waste heat from this generation is captured and delivered to the building to provide thermal energy. For a CHP system to show an economic advantage over a conventional system, its operating costs must be lower when providing the same amount of thermal energy and electricity that would have come from the SHP system. The spark spread (SS), or price difference between purchased electricity and fuel, is used as a simple indicator as to whether the CHP system is economically viable. Rather than using a single value of SS as a cutoff for viability of the CHP system, a more detailed spark spread expressed in terms of the efficiencies of the CHP system and SHP system components can be used to determine if a CHP system is economically viable. In an initial feasibility study, the calculation of the SS is based on estimates of a number of variables. It is important to assess the likely impact of changes in certain of some of these variables, as such changes can affect the SS calculations. This paper presents a sensitivity analysis to determine the effects of different parameters on the cost ratio which is used to calculate SS, including: reference heating system efficiency, power generation unit (PGU) efficiency and CHP overall system efficiency. Because CHP system efficiency itself is a function of the PGU efficiency as well as the thermal efficiency, these two parts of the total system efficiency are also investigated separately. Since the cost of purchased electricity and fuel varies by geographic region, the required spark spread for a given system may indicate favorable economics for a CHP system in one location while the CHP system shows no potential for savings in another location. Therefore, the sensitivity analysis is considered for three different U.S. locations.Copyright

Solar thermal driven cooling system for a data center in albuquerque New Mexico

Data centers are facilities that primarily contain electronic equipment used for data processing, data storage, and communications networking. Regardless of their use and configuration, most data centers are more energy intensive than other buildings. The continuous operation of information technology equipment and power delivery systems generates a significant amount of heat that must be removed from the data center for the electronic equipment to operate properly. Since data centers spend up to half their energy on cooling, cooling systems becomes a key factor for energy consumption reduction strategies and alternatives in the data centers. This paper presents a theoretical analysis of an absorption chiller driven by solar thermal energy as cooling plant alternative for data centers. Source primary energy consumption is used to compare the performance of different solar cooling plants with a standard cooling plant. The solar cooling plants correspond to different combinations of solar collector arrays and thermal storage tank, with a boiler as source of energy to ensure continuous operation of the absorption chiller. The standard cooling plant uses an electric chiller. Results suggest that the solar cooling plant with flat-plate solar collectors is a better option over the solar cooling plant with evacuated-tube solar collectors. However, although solar cooling plants can decrease the primary energy consumption when compared with the standard cooling plant, the net present value of the cost to install and operate the solar cooling plants are higher than the one for the standard cooling plant.

Uncertainty Analysis for Dimensioning Solar Photovoltaic Arrays

As the world population increases, so does their demand for energy. The demand of energy is mainly in the form of electricity with an origin primarily from fossil fuels. Since solar photovoltaic technology has the ability to convert solar energy directly into electricity, this technology has become one of the most popular alternatives at all scales for substitution of technology that uses fossil fuels. However, a limiting factor for the massive use solar photovoltaic technology is economics. A key component in the overall strategy to overcome the economic limitation of solar photovoltaic technology is the system size optimization at the design stage. At the design stage, data related to the solar energy availability, energy demand, and equipment performance is used to determine the size of the equipment while being able to satisfy the targeted peak energy demand. In general, a common engineering safety factor is used to ensure the system to meet the energy demand during its life cycle operation. The sizing procedure of solar photovoltaic systems can be further improved to be more reliable and economical when the uncertainty in the design process is considered. This paper presents a framework to perform an uncertainty analysis that can lead to improve sizing process for solar photovoltaic arrays. Through results from the application of the proposed approach, a reliable interval for the size of the photovoltaic array is found that can lead to more accurate and economic design compared to the use of common engineering safety factors.Copyright

Potential of Solar Thermal Energy for CCHP Systems

Integrated energy systems combine distributed power generation with thermally activated components to use waste heat, improving the overall energy efficiency, and making better use of fuels. Use of solar thermal energy is attractive to improve combined cooling, heating, and power (CCHP) systems performance, particularly during summer time since the cooling load coincides very well with solar energy availability. Limitation of the use of solar systems is mainly related to high first cost and large surface area for solar energy harvesting. Therefore, solar thermal CCHP systems seem to be an alternative to increase the use of solar thermal energy as a means to increase energy systems overall efficiency and reduce greenhouse gases (GHGs) emissions. This study focuses on the use of solar collectors in CCHP systems in order to reduce PEC and emission of CO2 in office buildings. By using a base CCHP system, the energy and economic analysis are presented as the contribution of the solar system from the baseline. For comparison purposes, the analysis is made for the cities of Minneapolis (MN), Chicago (IL), New York (NY), Atlanta (GA), and Fort Worth (TX). Results show that solar thermal CCHP systems can effectively reduce the fuel energy consumption from the boiler. The potential of solar collectors in CCHP systems to reduce PEC and CO2 emission increases with the cooling demand; while the effectiveness of solar collectors to reduce primary energy consumption and CO2 emission, and the ability of the system to pay by itself from fuel savings, decreases with the number of solar collectors.Copyright

Simplified modeling of thermal storage tank for distributed energy heat recovery applications

A simplified mathematical model was developed to analyze a storage tank containing a stationary fluid with hot and cold heat exchanger coils. The model is to be used as a screening tool for determining tank size and configurations for operation with a given power generation unit in a combined cooling, heating and power (CCHP) system. As such, the model was formulated so that it requires minimal information about the thermo-physical properties of the fluids and design parameters in order to determine the temperature profiles of the stored fluid and the heat transfer fluid for turbulent flow inside the heat exchangers. The presented model is implemented computationally with varying number of nodes, before comparing it with a more detailed model that take into account the variation of thermo-physical properties, as well as the effects of thermal de-stratification and heat loss to the ambient. The simplified model provided accurate temperature predictions that could subsequently be used to design a stratified tank system for a given CCHP application.Copyright

Analysis of Autoregressive Energy Models of a Research House

Energy consumption from buildings is a major component of the overall energy consumption by end-use sectors in industrialized countries. In the United States of America (USA), the residential sector alone accounts for half of the combined residential and commercial energy consumption. Therefore, efforts toward energy consumption modeling based on statistical and engineering models are in continuous development. Statistical approaches need measured data but not buildings characteristics; engineering approaches need building characteristics but not data, at least when a calibrated model is the goal. Among the statistical models, the linear regression analysis has shown promising results because of its reasonable accuracy and relatively simple implementation when compared to other methods. In addition, when observed or measured data is available, statistical models are a good option to avoid the burden associated with engineering approaches. However, the dynamic behavior of buildings suggests that models accounting for dynamic effects may lead to more effective regression models, which is not possible with standard linear regression analysis. Utilizing lag variables is one method of autoregression that can model the dynamic behavior of energy consumption. The purpose of using lag variables is to account for the thermal energy stored/release from the mass of the building, which affects the response of HVAC equipment to changes in outdoor or weather parameters. In this study, energy consumption and outdoor temperature data from a research house are used to develop autoregressive models of energy consumption during the cooling season with lag variables to account for the dynamics of the house. Models with no lag variable, one lag variable, and two lag variables are compared. To investigate the effect of the time interval on the quality of the models, data intervals of 5 minutes, 15 minutes, and one hour are used to generate the models. The 5 minutes time interval is used because that is the resolution of the acquired data; the 15 minutes time interval is used because it is a common time interval in electric smart meters; and one hour time interval is used because it is the common time interval for energy simulation in buildings. The primary results shows that the use of lag variables greatly improves the accuracy of the models, but a time interval of 5 minutes is too small to avoid the dependence of the energy consumption on operating parameters. All mathematical models and their quality parameters are presented, along with supporting graphical representation as a visual aid to comparing models.Copyright