An engineering analysis of a closed cycle plant growth module

The SOLGEM model is a numerical engineering model which solves the flow and energy balance equations for the air flowing through a growing environment, assuming quasi-steady state conditions within the system. SOLGEM provides a dynamic simulation of the controlled environment system in that the temperature and flow conditions of the growing environment are estimated on an hourly basis in response to the weather data and the plant growth parameters. The flow energy balance considers the incident solar flux; incoming air temperature, humidity, and flow rate; heat exchange with the roof and floor; and heat and moisture exchange with the plants. A plant transpiration subroutine was developed based plant growth research facility, intended for the study of bioregenerative life support theories. The results of a performance analysis of the plant growth module are given. The estimated energy requirements of the module components and the total energy are given

Preliminary Retro-Commissioning Study on Optimal Operation for the Heat Source System of a District Heating Cooling Plant

In order to improve the energy performance of a district heating and cooling (DHC) plant, the expected performance of the plant is studied using simulations based on mathematical models. A complete heat source system model, equipped with an embedded module that automatically determines the on/off states of heat source equipment using cooling/heating loads, has been developed and validated using actual performance measurements. The mean error between the simulated and measured total energy consumption was 4.2%. Using the developed model, three proposals for improving the plant operation are simulated in order to determine how much energy can be saved. The simulation result shows that the three proposals, automating primary water flow rate, fully open bypass valve of heat exchanger during no-ice-thermal-discharge period, and increase chilled water supply temperature to 8°C, could reduce plant total energy consumption by 2.1%, 0.7% and 3.3% respectively

Model Advancement And Hil Setup For Testing A P2 Phev Supervisory Controller

Teams participating in Advanced Vehicle Technology Competitions such as EcoCAR3 are often bound by limited time and resources. Moreover, vehicle and component downtime due to mechanical and electrical issues reduce the time available for testing activities demanded by the Controls/Systems Modeling and Simulation teams. Therefore, the teams would benefit from identifying new approaches and being more pragmatic and productive in order to achieve satisfactory progress in the competition. This thesis summarizes the approach taken to improve the simulation accuracy of the Wayne State University EcoCAR3 team’s Pre-transmission Parallel Hybrid Electric Vehicle plant model and HIL setup. Focus is on testing the Hybrid Supervisory Controller energy management and diagnostic functionality to be successful in the emissions and energy consumption event. After thorough literature research it is determined that a varying fidelity forward dynamic HEV plant model can produce accurate energy consumption simulation results. Initially, data obtained from manufacturers is used to model the components such as IC Engine, Electric Machine, Energy Storage System (ESS), transmission, differential, chassis and the ECUs. Later, test benches are setup to optimize and refine the individual model parameters by comparing the simulated results with the actual results obtained from component testing and on-road vehicle testing. Finally, the total vehicle plant model is validated by comparing the simulated results with the P2 PHEV on-road test data. The accuracy of the plant model determines the ability to optimize the Hybrid Supervisory Controller code to achieve maximum energy efficiency. Apart from model accuracy improvement, the Hardware In Loop (HIL) test setup is also discussed. HIL system is essential for validating the Hybrid Supervisory Controller’s functionalities in real time. The challenges during modeling and HIL setup are discussed and more improvements that can be done during the final year are recommended based on the research

Self-optimizing Control of Cooling Tower for Efficient Operation of Chilled Water Systems

The chilled-water systems, mainly consisting of electric chillers and cooling towers, are crucial for the ventilating and air conditioning systems in commercial buildings. Energy efficient operation of such systems is thus important for the energy saving of commercial buildings. This paper presents an extremum seeking control (ESC) scheme for energy efficient operation of the chilled-water system, and presents a Modelica based dynamic simulation model for demonstrating the effectiveness of the proposed control strategy. The simulated plant consists of a water-cooled screw chiller and a mechanical-draft counter-flow wet cooling tower. The ESC scheme takes the total power consumption of the chiller compressor and the tower fan as feedback, and uses the fan speed setting as the control input. The inner-loop controllers for the chiller operation include two proportional-integral (PI) control loops for regulating the evaporator superheat and the chilled water temperature. Simulation was conducted on the dynamic simulation model of the whole plant including the screw chiller and the cooling tower for different scenarios. The simulation results demonstrated the effectiveness of the proposed ESC strategy in searching for the optimal tower fan speed set-point under tested circumstances, and the potential for energy saving is also evaluated

Long-Term Electricity Supply-Demand Planning Simulation Using TEEP Model

This paper reports the application of new developed Tool for Electricity Energy Planning (TEEP), an accounting framework based bottom-up model to simulate long-term electricity supply-demand planning. The simulation is carried out using electricity sector data of Banyuwangi regency in East Java province, Indonesia. The projection of electricity demand and supply which consider fossil fuel as well as renewable energy potential is taken into account in the simulation to find the resources allocation implications and generation costs. The total electricity demand would increase up to 2,027.5 GWh from the initial value of 783.4 GWh. In the case of generation mix, the total generation costs of coal fired power plant could be reduced by 450 Million US$ and potential coal saving would be 4.375 thousand ton, among other findings

Advancement And Validation Of A Plug-In Hybrid Electric Vehicle Model Utilizing Experimental Data From Vehicle Testing

The objective of the research into modeling and simulation was to provide an iterative improvement to the Wayne State EcoCAR 2 team\u27s math-based design tools for use in evaluating different outcomes based on hybrid powertrain architecture tweaks, controls code development and testing. This thesis includes the results of the team\u27s work in the EcoCAR 2 competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions. Plant model validations and advancements brought the vehicle plant model directionally closer to the actual vehicle\u27s experimental data and achieved a significant error reduction in 10 of 11 metrics detailed in the research. The EcoCAR 2 competition events provided the opportunity for the team to get experimental data of the vehicle\u27s behavior on the vehicle chassis dyno and the vehicle on road testing from General Motors proving ground test tracks. Experimental data was used from 5 sources to validate and advance the vehicle plant model: 1. Component Test Benches 2. HIL Test Bench 3. Component on Dynamometer (Dyno) 4. Vehicle on Chassis Dyno 5. Vehicle On Road The advancement of the electric motor powertrain and the vehicle chassis portions of the vehicle plant model provided significant error reduction (at least a 10% reduction) in: * Dynamic Performance metrics (2 of 3 had more than 10% error reduction): o 9% --\u3e 0% 0-60 mph Acceleration o 15% --\u3e 19% 50-70 mph Acceleration o 37% --\u3e 3% Braking Distance, 60-0 mph deceleration * Emissions & Energy Consumption metrics (8 of 8 had more than 10% error reduction): Utility Factor (UF) is from SAE J1711 standard for measuring the exhaust emissions and fuel economy of HEV\u27s and PHEV\u27s o 49% --\u3e 16% Total Vehicle Range (ESS + Fuel Tank) o 11% --\u3e 0.2% Charge Depletion Range o 43% --\u3e 24% Charge Sustaining Fuel Consumption o 47% --\u3e 27% UF-Weighted Fuel Energy Consumption o 9% --\u3e 1% UF-Weighted AC Electric Energy consumption o 38% --\u3e 21% UF-Weighted Total Energy Consumption o 45% --\u3e 26% UF-Weighted Well To Wheel Petroleum Energy Use o 43% --\u3e 31% UF-Weighted Well To Wheel GHG Emissions However, significant error (more than 10%) still exists and more work is needed in: * 1 of 3 Dynamic Performance metrics * 6 of 8 Emissions & Energy Consumption metrics Future work includes adding a torque converter plant model between the engine plant model and the transmission plant model on the front wheel drive powertrain, implementing identified advancements into the engine and transmission plant models, and additional analysis for validation of the engine and transmission plant models. The vehicle plant model now provides higher confidence and higher accuracy (in most cases) for the simulation results, making the vehicle plant model significantly more useful for evaluating fuel economy, dynamic performance, and emissions improvement results when testing the team\u27s controls code changes for optimization

Tårs 10000 m2 CSP + Flat Plate Solar Collector Plant - Cost-Performance Optimization of the Design

AbstractA novel solar heating plant with Concentrating Solar Power (CSP) collectors and Flat Plate (FP) collectors has been put into operation in Tårs since July 2015. To investigate economic performance of the plant, a TRNSYS-Genopt model, including a solar collector field and thermal storage tank, was established. The optimization showed that there was a synergy in combining CSP and FP collectors. Even though the present cost per m2 of the CSP collectors is high, the total energy cost is minimized by installing a combination of collectors in such solar heating plant. It was also found that the CSP collectors could raise flexibility in the control strategy of the plant. The TRNSYS-Genopt model is based on individually validated component models and collector parameters from experiments. Optimization of the cost performance of the plant has been conducted in this paper. The simulation model remains to be validated with annual measured data from the plant

Heat absorption properties of ground material for solar chimney power plants

One of the major challenges to the widespread application of the solar chimney power plant is its low-power conversion efficiency because of the three technological processes involved. The chimney efficiency is difficult to improve, and thus enhancing the collector or turbine performance can considerably improve the total plant efficiency. This work focused on enhancing the energy conversion efficiency of the collector and also extending the operation time using a heat storage medium. The solar to thermal conversion and thermal storage capabilities of six ground materials that are potentially available in Malaysia were studied experimentally and numerically. The experimental model was designed such that the six materials were exposed to the same operation boundary conditions. The numerical studies were conducted using ANSYS software, where the geometrical models were developed and simulated using FLUENT for the fluid flow and energy/thermal field studies. The selected ground materials were ceramic, black stones, sawdust, dark-green painted wood, sand, and pebbles. The simulation and experimental results are in good agreement in terms of air stream velocity and energy conversion efficiency. The results showed that the different materials have different heat storage capacities, and that ceramics extend the operation with improved efficiency until nighttime. The results also showed that ceramic and black stones have better performance than the other materials. However, black stones are recommended as the absorbing material for solar chimney power plants in Malaysia and regional countries because they are readily available

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility

Embedding food quality in simulation modeling for milk supply chains

This thesis is part of a research study by the German Federal Ministry of Food, Agriculture and Consumer Protection (BMELV), aiming energy savings by producing milk and whey concentrates instead of milk powders, whose production process is highly energy intensive. Although the new proposal is more sustainable, higher logistic efforts are likely to be necessary. The main objective of this study is to evaluate the trade-off between quality level of the product and logistic costs throughout the whole supply chain, and for that purpose, a simulation study has been implemented using the software Plant Simulation. The current process for powders has been compared to 4 alternative processes for concentrates; which combined with two parameters (delivery frequency and cooling temperature) generate 16 different scenarios. In order to design the simulation model, a top-down approach is used, allowing to independently model each of the processes involved, as well as to easily modify the model for more advanced stages of the bio-processing research. The simulation model is highly focused on individual batch quality, by means of quality prediction models, and batch traceability, both intrinsic to the model and its dynamic behavior (programmed by methods). Finally, the simulation outcomes for each scenario, i.e. average product quality and total costs, have been compared to the powders reference scenario.Outgoin