Relevant bibliographies by topics / System energy simulation

Academic literature on the topic 'System energy simulation'

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Published: 14 March 2023

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Journal articles on the topic "System energy simulation"

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Haq, Ajaz Ul. "Modelling and Simulation of Energy Storage System for Grid-Connected Wind-PV System." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 591–99. http://dx.doi.org/10.31142/ijtsrd19048.

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Trung, Tran Thai, Seon-Ju Ahn, and Joon-Ho Choi. "Real Time Simulation of Distribution System with Distributed Energy Resources." Journal of Clean Energy Technologies 3, no. 1 (2015): 57–61. http://dx.doi.org/10.7763/jocet.2015.v3.169.

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Dash, Ritesh, Chinmaya Behera, Pratik Ranjan Behera, Manas Ranjan Sarangi, and Kunjan Kumar Mohapatra. "A Review on Hybrid Energy System and A Model Simulation." International Journal of Scientific Research 3, no. 5 (June 1, 2012): 150–53. http://dx.doi.org/10.15373/22778179/may2014/46.

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Barrett, Mark, and Catalina Spataru. "Dynamic Simulation of Energy System." Advanced Materials Research 622-623 (December 2012): 1017–21. http://dx.doi.org/10.4028/www.scientific.net/amr.622-623.1017.

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This paper investigates how society engenders demands for energy services that vary with time and climate, and how renewable and other energy resources can be deployed to meet these demands. Because the whole people-energy system is modeled, there is little detail about any component, instead an overall picture of how the entire system works is presented in this paper. It became apparent that the design and performance of dwelling energy systems, and to some extent the behavior of people, cannot be considered in isolation from the whole system. In order to get a picture of how the entire system works, the greater the diversity better overview can be obtained. But, from a practical perspective it is difficult to simultaneously model in detail a large number of people-dwelling combinations, alongside all other demands and electricity and other supply.
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Chaudhuri, A. S., and J. Jhampati. "System analysis and simulation—electric energy system." Annual Review in Automatic Programming 12 (January 1985): 389–94. http://dx.doi.org/10.1016/0066-4138(85)90408-2.

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Liu, Lei, Takeyoshi Kato, Paras Mandal, Alexey Mikhaylov, Ashraf M. Hemeida, Hiroshi Takahashi, and Tomonobu Senjyu. "Two cases studies of Model Predictive Control approach for hybrid Renewable Energy Systems." AIMS Energy 9, no. 6 (2021): 1241–59. http://dx.doi.org/10.3934/energy.2021057.

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<abstract><p>This work presents a load frequency control scheme in Renewable Energy Sources(RESs) power system by applying Model Predictive Control(MPC). The MPC is designed depending on the first model parameter and then investigate its performance on the second model to confirm its robustness and effectiveness over a wide range of operating conditions. The first model is 100% RESs system with Photovoltaic generation(PV), wind generation(WG), fuel cell, seawater electrolyzer, and storage battery. From the simulation results of the first case, it shows the control scheme is efficiency. And base on the good results of the first case study, to propose a second case using a 10-bus power system of Okinawa island, Japan, to verify the efficiency of proposed MPC control scheme again. In addition, in the second case, there also applied storage devices, demand-response technique and RESs output control to compensate the system frequency balance. Last, there have a detailed results analysis to compare the two cases simulation results, and then to Prospects for future research. All the simulations of this work are performed in Matlab®/Simulink®.</p></abstract>
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Babar, Deepali R. "Simulation of Hybrid Energy Storage System." International Journal for Research in Applied Science and Engineering Technology 6 (January 31, 2018): 1042–45. http://dx.doi.org/10.22214/ijraset.2018.1157.

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Dev, Nikhil, Satyapal, and Tarun Kumar Kurmi. "Simulation of CHP Energy Conversion System." INROADS- An International Journal of Jaipur National University 5, no. 1s (2016): 149. http://dx.doi.org/10.5958/2277-4912.2016.00029.1.

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Elhaj, Mohamed A., Jamal S. Yassin, and Ali Ahmed Mutordi. "Simulation of Solar Energy Storage System." Advanced Materials Research 658 (January 2013): 437–45. http://dx.doi.org/10.4028/www.scientific.net/amr.658.437.

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The present study deals with the main parameters of a storage tank-collector system, the proposal system included a flat plate solar collector coupling by a storage unit to serve the energy requirement of small Libyan family (3-5 persons).The studied parameters included the selection of the storage size needed for a given collector area and a given load under Libyan climatic condition. These parameters include the appropriate location for inlet and outlet ports of the hot water in the storage tank.A mathematical simulation model was written based on the given parameters and the input data of Misurata city in libya the location (L=32.15 N, 15.15W) as a case study. The developed program was carried out in visual basic 6.The final results showed that a storage tank with a capacity of (125 Litters per square meters) is sufficient to cover the requirement of Libyan family (3-5 persons). Also,. Furthermore, the hot water from the collector should be entered the storage tank at the upper portion of the tank to satisfy for the previous enhancement.
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Gough, M. C. B. "Component based building energy system simulation." International Journal of Ambient Energy 7, no. 3 (July 1986): 137–43. http://dx.doi.org/10.1080/01430750.1986.9675492.

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Dissertations / Theses on the topic "System energy simulation"

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Bousnane, Kafiha. "Real-time power system dynamic simulation." Thesis, Durham University, 1990. http://etheses.dur.ac.uk/6623/.

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The present day digital computing resources are overburdened by the amount of calculation necessary for power system dynamic simulation. Although the hardware has improved significantly, the expansion of the interconnected systems, and the requirement for more detailed models with frequent solutions have increased the need for simulating these systems in real time. To achieve this, more effort has been devoted to developing and improving the application of numerical methods and computational techniques such as sparsity-directed approaches and network decomposition to power system dynamic studies. This project is a modest contribution towards solving this problem. It consists of applying a very efficient sparsity technique to the power system dynamic simulator under a wide range of events. The method used was first developed by Zollenkopf (^117) Following the structure of the linear equations related to power system dynamic simulator models, the original algorithm which was conceived for scalar calculation has been modified to use sets of 2 * 2 sub-matrices for both the dynamic and algebraic equations. The realisation of real-time simulators also requires the simplification of the power system models and the adoption of a few assumptions such as neglecting short time constants. Most of the network components are simulated. The generating units include synchronous generators and their local controllers, and the simulated network is composed of transmission lines and transformers with tap-changing and phase-shifting, non-linear static loads, shunt compensators and simplified protection. The simulator is capable of handling some of the severe events which occur in power systems such as islanding, island re-synchronisation and generator start-up and shut-down. To avoid the stiffness problem and ensure the numerical stability of the system at long time steps at a reasonable accuracy, the implicit trapezoidal rule is used for discretising the dynamic equations. The algebraisation of differential equations requires an iterative process. Also the non-linear network models are generally better solved by the Newton-Raphson iterative method which has an efficient quadratic rate of convergence. This has favoured the adoption of the simultaneous technique over the classical partitioned method. In this case the algebraised differential equations and the non-linear static equations are solved as one set of algebraic equations. Another way of speeding-up centralised simulators is the adoption of distributed techniques. In this case the simulated networks are subdivided into areas which are computed by a multi-task machine (Perkin Elmer PE3230). A coordinating subprogram is necessary to synchronise and control the computation of the different areas, and perform the overall solution of the system. In addition to this decomposed algorithm the developed technique is also implemented in the parallel simulator running on the Array Processor FPS 5205 attached to a Perkin Elmer PE 3230 minicomputer, and a centralised version run on the host computer. Testing these simulators on three networks under a range of events would allow for the assessment of the algorithm and the selection of the best candidate hardware structure to be used as a dedicated machine to support the dynamic simulator. The results obtained from this dynamic simulator are very impressive. Great speed-up is realised, stable solutions under very severe events are obtained showing the robustness of the system, and accurate long-term results are obtained. Therefore, the present simulator provides a realistic test bed to the Energy Management System. It can also be used for other purposes such as operator training.
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McDonald, Christopher Ernest. "Framework for a visual energy use system." Thesis, [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-1892.

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Botha, Cornelis Petrus. "Simulation of the human energy system / Cornelis Petrus Botha." Thesis, North-West University, 2002. http://hdl.handle.net/10394/9623.

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Preface - Biotechnology is generally accepted to be the next economical wave of the future. In order to attain the many benefits associated with this growing industry simulation modelling techniques have to be implemented successfully. One of the simulations that ne' ed to be performed is that of the human energy system. Pharmaceutical companies are currently pouring vast amounts of capital into research regarding simulation of bodily processes. Their aim is to develop cures, treatments, medication, etc. for major diseases. These diseases include epidemics like diabetes, cancer, cardiovascular diseases, obesity, stress, hypertension, etc. One of the most important driving forces behind these diseases is poor blood sugar control. The blood glucose system is one of the major subsystems of the complete human energy system. In this study a simulation model and procedure for simulating blood glucose response due to various external influences on the human body is presented. The study is presented in two parts. The first is the development of a novel concept for quantifying glucose energy flow into, within and out of the human energy system. The new quantification unit is called ets (equivalent teaspoons sugar). The second part of the study is the implementation of the ets concept in order to develop the simulation model. Development of the ets concept - In the first part of the study the ets concept, used for predicting glycaemic response, is developed and presented. The two current methods for predicting glycaemic response due to ingestion of food are discussed, namely carbohydrate counting and the glycaemic index. Furthermore, it is shown that it is currently incorrectly assumed that 100% of the chemical energy contained in food is available to the human energy system after consumption. The ets concept is derived to provide a better measure of available energy from food. In order to verify the ets concept, two links with ets are investigated. These are the links with insulin response prediction as well as with endurance energy expenditure. It is shown that with both these links linear relationships provide a good approximation of empirical data. It is also shown that individualised characterisation of different people is only dependent on a single measurable variable for each link. Lastly, two novel applications of the ets concept are considered. The first is a new method to use the ets values associated with food and energy expenditure in order to calculate both short-acting and long-acting insulin dosages for Type 1 diabetics. The second application entails a new quantification method for describing the effects of stress and illness in terms of ets. Development of the blood glucose simulation model - The second part of the study presents a literature study regarding human physiology, the development for the blood glucose simulation model as well as a verification study of the simulation model. Firstly, a brief overview is given for the need and motivation behind simulation is given. A discussion on the implementation of the techniques for construction of the model is also shown. The procedure for solving the model is then outlined. During the literature study regarding human physiology two detailed schematic layouts are presented and discussed. The first layout involves the complex flow pathways of energy through the human energy system. The second layout presents a detailed discussion on the control system involved with the glucose energy pathway. Following the literature review the model for predicting glycaemic response is proposed. The design of the component models used for the simulations of the internal processes are developed in detail as well as the control strategies implemented for the control system of the simulation model. Lastly, the simulation model is applied for glycaemic response prediction of actual test subjects and the quality of the predictions are evaluated. The verification of the model and the procedure is performed by comparing simulated results to measured data. Two evaluations were considered, namely long-term and short-term trials. The quality of both are determined according to certain evaluation criteria and it is found that the model is more than 70% accurate for long-term simulations and more than 80% accurate for short-term simulations. Conclusion - In conclusion, it is shown that simplified simulation of the human energy system is not only possible but also relatively accurate. However, in order to accomplish the simulations a simple quantification method is required and this is provided by the ets concept developed in the first part of this study. Some recommendations are also made for future research regarding both the ets concept and the simulation model. Finally, as an initial endeavour the simulation model and the ets concept proposed in this study may provide the necessary edge for groundbreaking biotechnological discoveries.
PhD (Mechanical Engineering) North-West University, Potchefstroom Campus, 2003
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Williams, S. K. "Power system optimisation and stability studies using real-time simulation." Thesis, University of Bath, 1986. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370667.

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Weingarten, Leopold. "Physical Hybrid Model : Measurement - Experiment - Simulation." Thesis, Uppsala universitet, Fasta tillståndets fysik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176412.

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A method has been developed, Physical Hybrid Model, to investigate the physical large scale electrical effects of a Battery Energy Storage System (BESS) on a distribution grid by scaling the response from a small size Research Development and Demonstration (RD&D) platform. In order to realize the model the control system of an existing RD&D platform was refurbished and stability of components ensured. The Physical Hybrid Model proceeds as follows: Data from a distribution grid are collected. A BESS cycle curve is produced based on analyzed measurements. Required BESS power and capacity in investigated grid is scaled down by factor k to that of the physical test installation of the RD&D platform. The scaled BESS cycle is sent as input to control of the battery cycling of the RD&D platform. The response from the RD&D platform is scaled – up, and used in simulation of the distribution grid to find the impact of a BESS. The model was successfully implemented on a regional distribution grid in southern Sweden.
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Chitas, Dimosthenis. "Modeling and Simulation of a Small-Scale Polygeneration Energy System." Thesis, KTH, Kraft- och värmeteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-175830.

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The polygeneration is an innovative and sustainable solution which has become an attractive concept. The simultaneous production of electricity, heating and cooling including hot and cold water respectively in autonomous smaller energy systems can manage a more flexible and environmentally friendly system. Furthermore distributed generation and micro scale polygeneration systems can perform the increase of the utilized renewable energy sources in the power generation. The aforementioned energy systems can consist of several power generation units however the low emission levels, the low investment costs and the fuel flexibility of microturbines are some of the reasons that the study of the microturbines in polygeneration systems is a crucial necessity. In this study, an autonomous small-scale polygeneration energy system is investigated and each component is analyzed. The components of the system are a microturbine, a heat recovery boiler, a heat storage system and an absorption chiller. The purpose of this work is the development of a dynamic model in Matlab/Simulink and the simulation of this system, aiming to define the reliability of the model and understand better the behavior of such a system. Special focus is given to the model of the microturbine due to the complexity and the control methods of this system. The dynamic model is mainly based on thermodynamic equations and the control systems of the microturbine on previous research works. The system has as a first priority the electricity supply while thermal load is supplied depending on the electric demand. The thermal load is supplied by hot water due to the heat recovery which takes place at the heat recovery boiler from the flue gases of the microturbine. Additionally the design of the system is investigated and an operational strategy is defined in order to ensure the efficient operation of the system. For this reason, after creating the load curves for a specific load, two different cases are simulated and a discussion is done about the simulation results and the future work.
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Swedenborg, Samuel. "Modeling and Simulation of Cooling System for Fuel Cell Vehicle." Thesis, Uppsala universitet, Elektricitetslära, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-326070.

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This report is the result of a master’s thesis project which covers the cooling system in Volvo Cars’ fuel cell test vehicle. The purpose is to investigate if the existing cooling system in the fuel cell test vehicle works with the current fuel cell system of the vehicle, in terms of sufficient heat rejection and thus sustaining acceptable temperature levels for the fuel cell system. The project also aims to investigate if it is possible to implement a more powerful fuel cell system in the vehicle and keep the existing cooling system, with only a few necessary modifications. If improvements in the cooling system are needed, the goal is to suggest improvements on how a suitable cooling system can be accomplished. This was carried out by modeling the cooling system in the simulation software GT-Suite. Then both steady state and transient simulations were performed. It was found that the cooling system is capable of providing sufficient heat rejection for the current fuel cell system, even at demanding driving conditions up to ambient temperatures of at least 45°C. Further, for the more powerful fuel cell system the cooling system can only sustain sufficient heat rejection for less demanding driving conditions, hence it was concluded that improvements were needed. The following improvements are suggested: Increase air mass flow rate through the radiator, increase pump performance and remove the heat exchanger in the cooling system. If these improvements were combined it was found that the cooling system could sustain sufficient heat rejection, for the more powerful fuel cell system, up to the ambient temperature of 32°C.
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Garay, Rosas Ludwin. "System Simulation of Thermal Energy Storage involved Energy Transfer model in Utilizing Waste heat in District Heating system Application." Thesis, KTH, Kraft- och värmeteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-161726.

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Nowadays continuous increase of energy consumption increases the importance of replacing fossil fuels with renewable energy sources so the CO2 emissions can be reduced. To use the energy in a more efficient way is also favorable for this purpose. Thermal Energy Storage (TES) is a technology that can make use of waste heat, which means that it can help energy systems to reduce the CO2 emissions and improve the overall efficiency. In this technology an appropriate material is chosen to store the thermal energy so it can be stored for later use. The energy can be stored as sensible heat and latent heat. To achieve a high energy storage density it is convenient to use latent heat based TES. The materials used in this kind of storage system are called Phase Change Materials (PCM) and it is its ability of absorbing and releasing thermal energy during the phase change process that becomes very useful. In this thesis a simulation model for a system of thermal energy transportation has been developed. The background comes from district heating systems ability of using surplus heat from industrials and large scale power plants. The idea is to implement transportation of heat by trucks closer to the demand instead of distributing heat through very long pipes. The heat is then charged into containers that are integrated with PCM and heat exchangers. A mathematical model has been created in Matlab to simulate the system dynamics of the logistics of the thermal energy transport system. The model considers three main parameters: percentage content of PCM in the containers, annual heat demand and transport distance. How the system is affected when these three parameters varies is important to visualize. The simulation model is very useful for investigation of the economic and environmental capability of the proposed thermal energy transportation system. Simulations for different scenarios show some expected results. But there are also some findings that are more interesting, for instance how the variation of content of PCM gives irregular variation of how many truck the system requires, and its impact on the economic aspect. Results also show that cost for transporting the heat per unit of thermal energy can be much high for a small demands compared to larger demands.
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Bouwer, Werner. "Designing a dynamic thermal and energy system simulation scheme for cross industry applications / W. Bouwer." Thesis, North-West University, 2004. http://hdl.handle.net/10394/592.

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The South African economy, which is largely based on heavy industry such as minerals extraction and processing, is by nature very energy intensive. Based on the abundance of coal resources, electricity in South Africa remains amongst the cheapest in the world. Whilst the low electricity price has contributed towards a competitive position, it has also meant that our existing electricity supply is often taken for granted. The economic and environmental benefits of energy efficiency have been well documented. Worldwide, nations are beginning to face up to the challenge of sustainable energy - in other words to alter the way that energy is utilised so that social, environmental and economic aims of sustainable development are supported. South Africa as a developing nation recognises the need for energy efficiency, as it is the most cost effective way of meeting the demands of sustainable development. South Africa, with its unique economic, environmental and social challenges, stands to benefit the most from implementing energy efficiency practices. The Energy Efficiency Strategy for South Africa takes its mandate from the South African White Paper on Energy Policy. It is the first consolidated governmental effort geared towards energy efficiency practices throughout South Africa. The strategy allows for the immediate implementation of low-cost and no-cost interventions, as well as those higher-cost measures with short payback periods. An initial target has been set for an across sector energy efficiency improvement of 12% by 2014. Thermal and energy system simulation is globally recognised as one of the most effective and powerful tools to improve overall energy efficiency. However, because of the usual extreme mathematical nature of most simulation algorithms, coupled with the historically academic environment in which most simulation software is developed, valid perceptions exist that system simulation is too time consuming and cumbersome. It is also commonly known that system simulation is only effective in the hands of highly skilled operators, which are specialists in their prospective fields. Through previous work done in the field, and the design of a dynamic thermal and energy system simulation scheme for cross industry applications, it was shown that system simulation has evolved to such an extent that these perceptions are not valid any more. The South African mining and commercial building industries are two of the major consumers of electricity within South Africa. By improving energy efficiency practices within the building and mining industry, large savings can be realised. An extensive investigation of the literature showed that no general suitable computer simulation software for cross industry mining and building thermal and energy system simulation could be found. Because the heating, ventilation and air conditioning (HVAC) of buildings, closely relate to the ventilation and cooling systems of mines, valuable knowledge from this field was used to identify the requirements and specifications for the design of a new single cross industry dynamic integrated thermal and energy system simulation tool. VISUALQEC was designed and implemented to comply with the needs and requirements identified. A new explicit system component model and explicit system simulation engine, combined with a new improved simulation of mass flow through a system procedure, suggested a marked improvement on overall simulation stability, efficiency and speed. The commercial usability of the new simulation tool was verified for building applications by doing an extensive building energy savings audit. The new simulation tool was further verified by simulating the ventilation and cooling (VC) and underground pumping system of a typical South African gold mine. Initial results proved satisfactory but, more case studies to further verify the accuracy of the implemented cross industry thermal and energy system simulation tool are needed. Because of the stable nature of the new VISUALQEC simulation engine, the power of the simulation process can be further extended to the mathematical optimisation of various system variables. In conclusion, this study highlighted the need for new simulation procedures and system designs for the successful implementation and creation of a single dynamic thermal and energy system simulation tool for cross industry applications. South Africa should take full advantage of the power of thermal and energy system simulation towards creating a more energy efficient society.
Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2005.
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Van, Heerden Eugene. "Integrated simulation of building thermal performance, HVAC system and control." Thesis, University of Pretoria, 1997. http://hdl.handle.net/2263/37304.

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Practicing engineers need an integrated building, HVAC and control simulation tool for optimum HVAC design and retrofit. Various tools are available to the researchers, but these are not appropriate for the consulting engineer. To provide the engineer with a tool which can be used for typical HVAC projects, new models for building, HVAC and control simulation are introduced and integrated in a user-friendly, quick-to-use tool. The new thermal model for buildings is based on a transfer matrix description of the heat transfer through the building shell. It makes provision for the various heat flow paths that make up the overall heat flow through the building structure. The model has been extensively verified with one hundred and three case studies. These case studies were conducted on a variety of buildings, ranging from a 4m2 bathroom, to a 7755 m2 factory building. Eight of the case studies were conducted independently in the Negev Desert in Israel. The thermal model is also used in a program that was custom-made for the AGREMENT Board (certification board for the thermal performance of new low-cost housing projects). Extensions to the standard tool were introduced to predict the potential for condensation on the various surfaces. Standard user patterns were incorporated in the program so that all the buildings are evaluated on the same basis. In the second part of this study the implementation of integrated simulation is discussed. A solution algorithm, based on the Tarjan depth first-search algorithm, was implemented. This ensures that the minimum number of variables are identified. A quasi-Newton solution algorithm is used to solve the resultant simultaneous equations. Various extensions to the HVAC and control models and simulation originally suggested by Rousseau [1] were implemented. Firstly, the steady-state models were extended by using a simplified time-constant approach to emulate the dynamic response of the equipment. Secondly, a C02 model for the building zone was implemented. Thirdly, the partload performance of particular equipment was implemented. Further extensions to the simulation tool were implemented so that energy management strategies could be simulated. A detailed discussion of the implications of the energy management systems was given and the benefits of using these strategies were clearly illustrated, in this study. Finally, the simulation tool was verified by three case studies. The buildings used for the verification ranged from a five-storeyed office and laboratory building, to a domestic dwelling. The energy consumption and the dynamics of the HVAC systems could be predicted sufficiently accurately to warrant the use of the tool for future building retrofit studies
Thesis (PhD)--University of Pretoria, 1997.
gm2014
Mechanical and Aeronautical Engineering
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Books on the topic "System energy simulation"

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United States. Energy Information Administration, ed. NEMS, the National Energy Modeling System: A preview. Washington, DC: Energy Information Administration, 1992.

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Truong, Long V. Simulation of a flywheel electrical system for aerospace applications. Cleveland, Ohio: National Aeronautics and Space Administration, Glenn Research Center, 2000.

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J, Wolff Frederick, Dravid Narayan V, and NASA Glenn Research Center, eds. Simulation of a flywheel electrical system for aerospace applications. Cleveland, Ohio: National Aeronautics and Space Administration, Glenn Research Center, 2000.

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Jiao, Zhuang. Distributed-Order Dynamic Systems: Stability, Simulation, Applications and Perspectives. London: Springer London, 2012.

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P, Van Hooser Katherine, and United States. National Aeronautics and Space Administration., eds. A general fluid system simulation program to model secondary flows in turbomachinery. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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Yu, Yi-Hsiang. Preliminary results of a RANS simulation for a floating point absorber wave energy system under extreme wave conditions. [Golden, CO]: National Renewable Energy Laboratory, 2011.

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Hermann, Meer, Klingert Sonja, Somov Andrey, and SpringerLink (Online service), eds. Energy Efficient Data Centers: First International Workshop, E2DC 2012, Madrid, Spain, Mai 8, 2012, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Li, Kang. Life System Modeling and Intelligent Computing: International Conference on Life System Modeling and Simulation, LSMS 2010, and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, Wuxi, China, Deptember 17-20, 2010, Proceedings, Part I. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Desideri, Umberto, Giampaolo Manfrida, and Enrico Sciubba, eds. ECOS 2012. Florence: Firenze University Press, 2012. http://dx.doi.org/10.36253/978-88-6655-322-9.

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The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology.
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International Conference on Life System Modeling and Simulation (2010 Wuxi (Jiangsu Sheng), China). Life system modeling and intelligent computing: International Conference on Life System Modeling and Simulation, LSMS 2010, and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, Wuxi, China, September 17-20, 2010 : proceedings. Berlin: Springer, 2010.

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Book chapters on the topic "System energy simulation"

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Bazan, Peter, Marco Pruckner, David Steber, and Reinhard German. "Hierarchical Simulation of the German Energy System and Houses with PV and Storage Systems." In Energy Informatics, 12–23. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25876-8_2.

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Zhang, Dongni, Xunwen Su, Xianzhong Xu, Dawei Wang, and Siyu Chen. "Modeling and Simulation of Photovoltaic Grid-Connected System." In Green Energy and Networking, 267–75. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62483-5_28.

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Behura, Arun K., Spandan Shah, Aman Kumar, and Gaurav Dwivedi. "Investigation and Simulation of Rooftop Solar Photovoltaic System." In Springer Proceedings in Energy, 69–83. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0235-1_6.

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Banerjee, Binayak, Dilan Jayaweera, and Syed Islam. "Modelling and Simulation of Power Systems." In Smart Power Systems and Renewable Energy System Integration, 15–28. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30427-4_2.

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Harish, V. S. K. V., Nayan Kumar Singh, Arun Kumar, Karan Doshi, and Amit Vilas Sant. "Modelling and simulation of heating ventilation and air-conditioning system." In Renewable Energy Integration with Building Energy Systems, 39–62. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003211587-3.

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Luther, J., and J. Schumacher-Gröhn. "INSEL — A Simulation System for Renewable Electrical Energy Supply Systems." In Tenth E.C. Photovoltaic Solar Energy Conference, 457–60. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3622-8_117.

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Sulukan, Egemen, Tanay Sıdkı Uyar, Doğancan Beşikci, Doğuş Özkan, and Alperen Sarı. "Energy System Analysis, Simulation and Modelling Practices in Turkey." In Lecture Notes in Energy, 485–506. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40738-4_21.

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Gibbs, Colin L. "Physiological factors determining cardiac energy expenditure." In Simulation and Imaging of the Cardiac System, 358–76. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4992-8_26.

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Atilgan, Ibrahim, and Cevdet Aygun. "Simulation of Double Effect Absorption Refrigeration System." In Progress in Sustainable Energy Technologies Vol II, 685–703. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07977-6_45.

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Breukels, Jeroen, Roland Schmehl, and Wubbo Ockels. "Aeroelastic Simulation of Flexible Membrane Wings based on Multibody System Dynamics." In Airborne Wind Energy, 287–305. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39965-7_16.

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Conference papers on the topic "System energy simulation"

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FELSMANN, Clemens, Steffen ROBBI, and Elisabeth ECKSTADT. "Reduced Order Building Energy System Modeling In Large-scale Energy System Simulations." In 2017 Building Simulation Conference. IBPSA, 2013. http://dx.doi.org/10.26868/25222708.2013.1341.

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Roe, Curtis, A. P. Meliopoulos, Jerome Meisel, and Thomas Overbye. "Power System Level Impacts of Plug-In Hybrid Electric Vehicles Using Simulation Data." In 2008 IEEE Energy 2030 Conference (Energy). IEEE, 2008. http://dx.doi.org/10.1109/energy.2008.4781048.

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Finkbeiner, Konstantin, Paul Mathis, Florian Hintz, Elena Bykhovskaya, Leon Engelmeyer, Leon Engelmeyer, Dirk Bohne, and Dirk Mu¨ller. "Modeling a Building Energy System for Development of Energy Efficient Systems of Shopping Centers." In 2017 Building Simulation Conference. IBPSA, 2017. http://dx.doi.org/10.26868/25222708.2017.824.

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Mao, Wenbo, Feng Li, Peiran Shi, Gang Wang, and Peng Xu. "Precise Load Curtailment Simulation United with Power System Simulation." In 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2019. http://dx.doi.org/10.1109/ei247390.2019.9061737.

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Alikerimova, T. D. "RENEWABLE ENERGY AS A SYSTEM: SIMULATION ENERGY DEVELOPMENT." In RENEWABLE ENERGY: CHALLENGES AND PROSPECTS. ALEF, 2020. http://dx.doi.org/10.33580/2313-5743-2020-8-1-520-524.

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Abbas, Farukh, Sun Yingyun, and Usama Rehman. "Hybrid Energy Management System with Renewable Energy Integration." In 2015 Seventh International Computational Intelligence, Modelling and Simulation (CIMSim). IEEE, 2015. http://dx.doi.org/10.1109/cimsim.2015.26.

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Mavundla, Jabulisile S., Akshay K. Saha, Nelson M. Ijumba, Leon Chetty, and Edward Chikuni. "Modelling and Simulation of SOFC System." In Power and Energy Systems. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.714-024.

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Jones, Phillip, Xiaojun Li, and Ester Coma and Jo Patterson. "The SOLCER Energy Positive House: Whole System Simulation." In 2017 Building Simulation Conference. IBPSA, 2017. http://dx.doi.org/10.26868/25222708.2017.341.

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Ming-ming, Shi, Zhou Bo, and Wei Jia-dan. "Simulation research on a novel distributed generation system." In Energy Storage. IEEE, 2011. http://dx.doi.org/10.1109/pesa.2011.5982941.

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Chen, Chao, Wei Xi, and Changsong Qin. "General Secondary Equipment Simulation Drive System." In 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2021. http://dx.doi.org/10.1109/ei252483.2021.9713336.

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Reports on the topic "System energy simulation"

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Eberle, Annika, Irina Tsiryapkina, Steve Peterson, Laura Vimmerstedt, Dylan Hettinger, and Daniel Inman. An Overview of the Waste-to-Energy System Simulation (WESyS) Model. Office of Scientific and Technical Information (OSTI), October 2020. http://dx.doi.org/10.2172/1710170.

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Chandler, Shawn. Global Time-Independent Agent-Based Simulation for Transactive Energy System Dispatch and Schedule Forecasting. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2209.

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Trowbridge, L. D. Sensitivity analysis of the residential energy use module of the Commercial and Residential Energy Use Emissions Simulation System (CRESS). Office of Scientific and Technical Information (OSTI), July 1987. http://dx.doi.org/10.2172/5979998.

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Kelley, B., H. Scott, C. Sun, and N. Venethongkham. Energy Resilience for Mission Assurance: Agile Co-simulation for Cyber Energy System Security (ACCESS), Model Advancements for Resilience Analysis. Office of Scientific and Technical Information (OSTI), August 2022. http://dx.doi.org/10.2172/1883445.

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Trowbridge, L. D. Sensitivity analysis of the commercial energy use module of the Commercial and Residential Energy Use and Emissions Simulation System (CRESS). Office of Scientific and Technical Information (OSTI), March 1987. http://dx.doi.org/10.2172/6723510.

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Judkoff, R., and J. Neymark. Home energy rating system building energy simulation test (HERS BESTEST). Volume 2, Tier 1 and Tier 2 tests reference results. Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/162497.

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Judkoff, R., and J. Neymark. Home energy rating system building energy simulation test (HERS BESTEST): Volume 1, Tier 1 and Tier 2 tests user's manual. Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/171372.

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McDonald, J., and D. South. The Commercial and Residential Energy Use and Emissions Simulation System (CRESS): Selection process, structure, and capabilities. Office of Scientific and Technical Information (OSTI), February 1990. http://dx.doi.org/10.2172/6798219.

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Solomon, A. D., M. D. Morris, J. Martin, and M. Olszewski. Development of a simulation code for a latent heat thermal energy storage system in a space station. Office of Scientific and Technical Information (OSTI), April 1986. http://dx.doi.org/10.2172/5777340.

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Pullammanappallil, Pratap, Haim Kalman, and Jennifer Curtis. Investigation of particulate flow behavior in a continuous, high solids, leach-bed biogasification system. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600038.bard.

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Abstract:
Recent concerns regarding global warming and energy security have accelerated research and developmental efforts to produce biofuels from agricultural and forestry residues, and energy crops. Anaerobic digestion is a promising process for producing biogas-biofuel from biomass feedstocks. However, there is a need for new reactor designs and operating considerations to process fibrous biomass feedstocks. In this research project, the multiphase flow behavior of biomass particles was investigated. The objective was accomplished through both simulation and experimentation. The simulations included both particle-level and bulk flow simulations. Successful computational fluid dynamics (CFD) simulation of multiphase flow in the digester is dependent on the accuracy of constitutive models which describe (1) the particle phase stress due to particle interactions, (2) the particle phase dissipation due to inelastic interactions between particles and (3) the drag force between the fibres and the digester fluid. Discrete Element Method (DEM) simulations of Homogeneous Cooling Systems (HCS) were used to develop a particle phase dissipation rate model for non-spherical particle systems that was incorporated in a two-fluid CFDmultiphase flow model framework. Two types of frictionless, elongated particle models were compared in the HCS simulations: glued-sphere and true cylinder. A new model for drag for elongated fibres was developed which depends on Reynolds number, solids fraction, and fibre aspect ratio. Schulze shear test results could be used to calibrate particle-particle friction for DEM simulations. Several experimental measurements were taken for biomass particles like olive pulp, orange peels, wheat straw, semolina, and wheat grains. Using a compression tester, the breakage force, breakage energy, yield force, elastic stiffness and Young’s modulus were measured. Measurements were made in a shear tester to determine unconfined yield stress, major principal stress, effective angle of internal friction and internal friction angle. A liquid fludized bed system was used to determine critical velocity of fluidization for these materials. Transport measurements for pneumatic conveying were also assessed. Anaerobic digestion experiments were conducted using orange peel waste, olive pulp and wheat straw. Orange peel waste and olive pulp could be anaerobically digested to produce high methane yields. Wheat straw was not digestible. In a packed bed reactor, anaerobic digestion was not initiated above bulk densities of 100 kg/m³ for peel waste and 75 kg/m³ for olive pulp. Interestingly, after the digestion has been initiated and balanced methanogenesis established, the decomposing biomass could be packed to higher densities and successfully digested. These observations provided useful insights for high throughput reactor designs. Another outcome from this project was the development of low cost devices to measure methane content of biogas for off-line (US$37), field (US$50), and online (US$107) applications.
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