Modelica Analysis of Thermally Connected Residential Appliances

With the United States being the world’s second largest consumer of primary energy, research into areas of significant consumption can provide large impacts in terms of the global energy consumption. Buildings account for 41% of U.S. total energy consumption with the residential sector making up a majority. Household appliances account for the second largest site energy consumption at 27%, after the HVAC system for the U.S. residential sector. Thermally integrating residential appliances by leveraging waste heat recovery goes outside U.S. federal standards and has not been adequately explored by connecting all residential appliances. Limited studies exist focused only on single appliances connected to waste heat recovery or being thermally integrated. Modelica appliance models have been developed for four household appliances: refrigerator-freezer (RF), dishwasher (DW), clothes dryer (CD), and clothes washer (CW). The Modelica models capture individual use and the predictions of the RF and DW were compared against available experimental data. The individual models have been connected to a simple storage tank model to simulate the integrated appliance system. Modelica predicts the energy savings under the integrated system and captures any impact from integration

Modelica Household Dishwater Model with External Heat Loop

With the United States being the world’s second largest consumer of primary energy, research into areas of significant consumption can provide large impacts in terms of the global energy consumption. Buildings account for 41% of U.S. total energy consumption with the residential sector making up a majority. Household appliances account for the second largest site energy consumption at 27%, after the HVAC system for the U.S. residential sector. Thermally integrating residential appliances by leveraging waste heat recovery goes outside U.S. federal standards and has not been adequately explored by connecting all residential appliances. Limited studies exist focused only on single appliances connected to waste heat recovery or being thermally integrated. As part of a thermally connected system, individual appliance models are developed in Modelica and are tuned with available experimental data from the manufacturer. The dishwasher (DW) has better opportunity as a heat sink to offset the internal heater, 0.17 kWh of electricity/cycle for heating wash water. Due to the integration approach required with the dishwasher, a detailed accounting of major components is required. The thermal mass of the DW cavity and dishware, the fluctuating flow rates of each spray arm, and the final water sump temperature required are all captured. After tuning, the DW model of the traditional system shows an agreement within ±5% for most water sump temperatures

Dynamic Optimal Control of a CO2 Heat Pump Coupled with Hot and Cold Thermal Storages

This study presents a model-based dynamic optimization strategy for a dual-mode CO2 heat pump coupled with hot and cold thermal storages, which was proposed as a high-efficiency smart grid enabling option in heating and cooling services for buildings or industry. Dynamic optimal control for simultaneously charging of hot and cold thermal storages is very delicate. The optimal control of compressor discharge pressure were commonly used for optimal control of heat pump systems. In this study, the outlet water temperatures of hot and cold tanks are used as indicators in the dynamic optimal strategy for charging of hot and cold storages using a dual-mode heat pump. The Modelica based dynamic model of the coupled system was developed and validated. To optimize the overall coefficient of performance (COP) during energy process, the transient total COP is optimized by genetic algorithm based on Modelica-based modeling of dynamic system. A dynamic optimal control strategy was developed and implemented into an experimental system. Test results show that this developed model-based dynamic optimal control strategy is able to search the optimal transient total COP and optimize the overall COP of such coupled systems during energy charging; and the optimal results is better than those obtained using another two experiment-based methods

Experimental Analysis and Design Improvements on Combined Viper Expansion Work Recovery Turbine and Flow Phase Separation Device Applied in R410A Heat Pump

In light of recent trends towards energy efficiency and environmental consciousness, the heating, ventilation, air conditioning and refrigeration (HVAC&R) industry has been pushing for technological developments to meet both of these needs. As such, several solutions for harnessing the energy released from refrigerants during the expansion process of a conventional vapor-compression cycle have been developed to increase overall cycle efficiency. The study presented in this paper focuses on investigating the potential impact of installing an energy recovery expansion device known as the Viper Expander into an R410A heat pump. The Viper Expander operates by using a nozzle to accelerate the high pressure R410A into a high velocity jet of fluid impinging on a micro-turbine impeller. The impeller is coupled to a generator, which harvests the kinetic energy of the refrigerant by converting it into electrical energy that can be fed back into one of the system components, such as a fan or compressor motor. Previous Viper Expander iterations have not met performance expectations and thus, a major redesign was pursued. To improve the Viper Expander design, flow visualization of the two-phase refrigerant leaving the nozzle has been performed. Additionally, a housing redesign that will allow the Viper Expander to act as both an expansion work recovery device as well as a flash tank economizer has been proposed and modeled as a system solution

Analysis of a Rotating Spool Expander for Organic Rankine Cycles in Heat Recovery Applications

The increasing cost of energy, coupled with the recent drive for energy security and climate change mitigation have provided the impetus for harnessing renewable energy sources as viable alternatives to conventional fossil fuels. Furthermore, recovering heat that is discharged from power plants, automobiles and various other industrial processes is of growing interest. Nevertheless, technologies attempting to provide small-scale heat recovery solutions have seen very limited commercialization. This is broadly due to two reasons: lack of historical research and development in the area of waste-heat recovery and small-scale power generation due to technical and cost impediments; and technical challenges associated with scaling the technology from utility-scale to commercial-scale, particularly with regard to expansion machines (turbines). However, due to rising primary energy costs and the environmental premium being placed on fossil fuels, the conversion from low-grade heat to electrical energy as well as small-scale distributed power generation is of increasing interest. In this regard, this project focuses on a novel rotating spool expansion machine at the heart of an Organic Rankine Cycle (ORC), which in turn is used as a heat recovery system. A comprehensive simulation model of the rotating spool expander is presented. The spool expander provides a new rotating expansion mechanism with easily manufactured components. Apart from efficiency improvements compared with other rotary machines, the spool expander also has the ability to control the expansion ratio using a novel mechanically-driven suction valve mechanism. Another advantage is the relocation of the face sealing surfaces to the outer radius of the device. The spool expander is also scalable to a size range (50-200 kW) that is too large for conventional positive displacement machines, and too small for dynamic machines with respect to manufacturability, efficiency and cost. A detailed analytical geometry model of the spool expander and the suction valve mechanism is presented. This geometry model forms a part of a comprehensive model that includes submodels for friction, leakage, and heat transfer. The results of the comprehensive model are validated using experimental data from a 50 kW prototype expander in an ORC system. Given the promise of the technology, this paper explores the design space using both a simulation based approach as well as an experimental prototype for concept validation

Validation of a Charge-Sensitive Vapor-Injected Compression Cycle Model with Economization

In recent years, research on economized vapor injected (EVI) compression systems showed potential improvements to both cooling capacity and coefficient of performance (COP). In addition, the operating range of compressors can be extended by reducing the discharge temperature. However, the optimum operation of such systems is directly related to the amount of refrigerant charge, which often is not optimized. Therefore, an accurate charge estimation methodology is required to further improve the operation of EVI compression systems. In this paper, a detailed cycle model has been developed for the economized vapor injected (EVI) compression system. The model aims to predict the performance of EVI systems by imposing the amount of required refrigerant charge as an input. In the cycle model, the EVI compressor was mapped based on the correlation of Tello-Oquendo et al. (2017), whereas evaporator, condenser and economizer heat exchanger models were constructed based on the available ACHP models (Bell, 2010). With respect to charge inventory, the 2-point regression model from Shen et al. (2009) was used to account for inaccurate estimation of refrigerant volumes, ambiguity in slip flow model, solubility of refrigerant in the lubricating oil, among others. The cycle model has been validated with experimental performance data taken with a 5-ton Environmental Control Unit (ECU) that utilizes EVI technology. The developed cycle model showed very good agreement with the data with a MAE in COP of less than 4%. Furthermore, the estimated charge inventory has been compared to the one-point regression model. Results showed that the former method allowed to predict the charge inventory with an MAE of less than 0.5%

Development and Validation of a Mechanistic Vapor-Compression Cycle Model

Detailed models are crucial tools for engineers in designing and optimizing systems. In particular, mechanistic modeling of vapor compression systems for accurate performance predictions at both full- and part-load conditions have been improved significantly in the past decades. Yet, fully deterministic models present still challenges in estimating charge inventory in order to optimize the performance. In this work, a generalized framework for simulating vapor compression cycles (VCC) has been develvoped with emphasis on a charge-sensitive model. In order to illustrate the capabilities of the tool, a direct–expansion (DX) cycle has been considered. In the cycle model, the compressor was mapped by employing the ANSI/AHRI 540 10-coefficient correlation, the evaporator and the condenser were constructed based on the ACHP models (Bell, 2010). Furthermore, a TXV model was implemented based on Li and Braun (2008) formulation. With respect to the charge inventory estimation, the two-point regression model proposed by Shen et al. (2009) was used to account for inaccurate estimation of refrigerant volumes, ambiguous flow patterns for two-phase flow, and amount of refrigerant dissolved in the oil. The solution scheme required manufacturer input data for each component as well as the amount of refrigerant charge. Hence, the degree of superheating at the evaporator outlet, the subcooling at the condenser outlet and the perfromance parameters of the VCC system can be predicted. The model was validated with available experimental and numerical data available in literature. The simulation results demonstrated that the proposed model is more accurate and more generic than other methods presented in the literature