Optimizing Thermal Energy Storage For Cogeneration Applications: A Faculty And Engineering Technology Student Collaboration Using Excel

This paper has a two-fold purpose. Not only does it solve a significant engineering problem and present a solution for the optimization of thermal energy storage for use in cogeneration systems applications but it also identifies the importance of one-on-one faculty –student research and it how excel software can overcome the need for higherlevel mathematics. The problem is a familiar one to the engineers who must determine the optimum size of a thermal storage system that is not too large or too small for a customer’s thermal demand while matching it with the correct cogeneration system size (kwe). The problem’s solution however becomes an opportunity to enlist the help of an undergraduate student to help solve a fairly complicated problem. This pedagogy is seen as critical and necessary to the education of the engineering technology student; building self-confidence in his/her analytical skills to solve the problem via a “simple” spreadsheet that would otherwise require calculus and optimization techniques. No sooner has the student followed and contributed to the solution’s methodology that he realizes that he has actually used a probabilistic method in its solution: The Monte Carlo Method, a term that perhaps would frighten the student if revealed earlier but now becomes a part of his solutions “tool box”. This paper reports on the pedagogy of this collaboration as well as the useful results that were obtained. Introduction There is increasing emphasis in college education for undergraduates to conduct some level of research with their faculty mentors. Engineering Technology students are also expected to have a “hands-on” experience with real world problems that are faced by engineering professionals. This paper is a summary of the experience of one faculty mentor and his undergraduate colleague to combine both of these requirements into an effective educational experience for the student and the instructor. The first requirement is that the problem that needs to be solved must not only be a realworld engineering problem but one that has some reasonable likely hood of being solved in the time allowed. The only other requirement is that the student be a valued member of the team; taking on responsibilities that are essential to the project and ones that the faculty mentor would need to do if assistance were not available...in other words: no “make-work”, please. Meeting these two criteria results in benefit for both the student and the faculty mentor. P ge 969.1 Proceedings of the 2004 American Society of Engineering Education Annual Conference & Exposition Copyright © 2004, American Society of Engineering Education A corollary benefit that results from this study is the effective demonstration of the use of spreadsheets in engineering analysis. A spreadsheet computational platform is used and not a more “sophisticated” math software platforms. The use of spreadsheets provides additional strength to the student’s appreciation that spreadsheets are an effective analysis tool while also being virtually omnipresent and easy to learn and use. Problem Statement The theme of the project came about from a question that was poised by a client. The client was studying the optimization of a cogeneration system as it may be applied to an institutional, commercial and/or industrial energy user. A cogeneration system is defined here simply as a heat engine that is integrated with the necessary electric generator and heat recovery equipment so as to have both electric power and engine waste heat available for use by the customer. In many cogeneration systems the system is designed based on the amount of electric power that can be continuously used. The heat recovery from the heat engine that is sized based on the electric usage is then often not matched perfectly with the thermal energy needs of the user. In many instances the heat needs of the customer peak during some part of the day and are significantly reduced during other times of the day. While the electric power may be continuously used the waste heat may not be needed and thus must be rejected and thus not return an economic savings for the customer. In order to minimize the wasting of the recovered heat energy, many cogeneration systems have used thermal energy storage to “smooth” over the recovered energy until it is needed. The question that the client had was: How large a thermal storage system is needed in order to provide the most heat recovery and usage with the smallest outlay of initial cost and with the minimization of very valuable floor space? This paper answers this question by performing a very basic engineering thermodynamic First Law Analysis while also providing a venue for helping an engineering technology student gain confidence in his 1 analysis techniques while fortifying his understanding of the engineering technologist’s role in the engineering research that is performed for realworld engineering problems. The Analytical Model A computer model of the cogeneration and heat recovery system including a thermal (hot water) storage system was developed specifically for this problem statement. The model was prepared using Excel spreadsheet. The unique feature of the proposed solution was that it modeled many possible (or probable) fluctuations of the commercial or industrial user’s thermal demand. The spreadsheet was also programmed to model a variety of cogeneration systems that may be used by the industrial or commercial user. This former consideration was essential if a general result from the analysis was to be obtained. It is also the main reason why the question regarding the proper size for a thermal storage system remained unanswered in the literature. The technique presented via this paper is considered novel. 1 Throughout this paper reference may be made to the student author and thus the masculine pronoun is appropriate per the context used in the paper. P ge 969.2 Proceedings of the 2004 American Society of Engineering Education Annual Conference & Exposition Copyright © 2004, American Society of Engineering Education Figure 1 is a simple schematic of the cogeneration system, thermal energy storage and thermal energy demand by the user. The application of the First Law of Thermodynamics with this basic control volume is straight forward. As the electric power available from the heat engine is continuously generated so also is the heat recovery from the engine’s waste heat. However, this waste heat recovery can be used to heat the water in the storage tank only if the temperature of the thermal storage is below 200 F otherwise it must be rejected to the ambient. Any heat rejected to the environment obviously detracts from the economic viability of the cogeneration system and is to be avoided. Also, the thermal energy only has value to the energy user if the temperature of the thermal energy storage is above 160 F. These and other constraints used in this present study of the integrated cogeneration and thermal storage system are easily programmed by the analyst by typing into the “bordered” cells that are readily apparent in Figure 1. Excel cells that are not framed by bold lines are outputs from the calculations that are programmed into the spreadsheet. Exh. Ht. Rec. THERMAL RETURN WATER TANK ENGINE GEN. THERMAL SUPPLY FIGURE 1. SIMPLIFIED SCHEMATIC OF COGENERATION SYSTEM USED WITH FIRST LAW ANALYSIS Qdemand/Qeng.= 1.5 1 =MIN.Q demand Q,peak demand= 515583 Btu/hr Qfacility supply,Btu/Hr.= 515583 ENG. POWER= 60 kwe T,storage,hot= 200 F, STORAGE= 500 gal.s ENG. EFF= 0.28 T,storage,cold= 160 F MASS= 4171 LBm ENG. REJ. HT.= 0.47 0% =% BLR. HEAT 87% =ENGINE HEAT Time Incre.= 2 MIN.,Tstorage,initial= 180 F NET EFF.= 0.75 SUPPLY EFFECT. BTU/HR F F BTU/HR BTU 7.11E+06 TIME ENG. PWR.Qeng.sup.QdemandQstorage DTstorage Tstorage Qboiler ht. Qrej. Qboiler ht. Qrej. Qdemand Qeng.supply 0 60 343722 308261 35461 0.28 180.28 0.0 0.0 0.0 0.