Heejin Cho

Supervisory Feed-Forward Control for Real-Time Topping Cycle CHP Operation

This paper presents an energy dispatch algorithm for real-time topping cycle cooling, heating, and power (CHP) operation for buildings with the objective of minimizing the operational cost, primary energy consumption (PEC), or carbon dioxide emission (CDE). The algorithm features a supervisory feed-forward control for real-time CHP operation using short-term weather forecasting. The advantages of the proposed control scheme for CHP operation are (a) relatively simple and efficient implementation allowing realistic real-time operation, (b) optimized CHP operation with respect to operational cost, PEC, or CDE, and (c) increased site-energy consumption resulting in less dependence on the electric grid. In the feed-forward portion of the control scheme, short-term electric, cooling, and heating loads are predicted using the U.S. Department of Energy benchmark small office building model. The results are encouraging regarding the potential saving of operational cost, PEC, and CDE from using the control system for a CHP system with electric and thermal energy storages.

Comprehensive uncertainty analysis of a Wiebe function-based combustion model for pilot-ignited natural gas engines

Abstract This paper presents a comprehensive uncertainty analysis of a Wiebe function-based combustion model for advanced low-pilot-ignited natural gas (ALPING) combustion in a single-cylinder research engine. The sensitivities, uncertainty magnification factors (UMFs), and uncertainty percentage contributions (UPCs) of different experimental input variables and model parameters were investigated. First, the Wiebe function model was validated against experimental heat release/mass burned fraction profiles and cylinder pressure histories for three pilot injection timings (start of injection (SOI)): −20°, −40°, and −60° after top dead center (ATDC). Second, the sensitivities and UMFs of predicted cylinder pressure histories were determined. Finally, crank angle-resolved uncertainties were quantified and mapped as ‘uncertainty bounds’ in predicted pressures, which were compared with measured pressure curves with error bars for cyclic variations. The Wiebe function-based combustion model with a quadratic interpolation equation for the specific heat ratio (γ) provided reasonable cylinder pressure and heat release/mass burned fraction predictions for all SOIs (better for −20° and −60° ATDC SOIs compared with −40° ATDC). Uncertainty analysis results indicated that γ (parameters in the quadratic interpolation equation), compression ratio, mass and lower heating value of natural gas trapped in the cylinder, overall trapped mass, and ignition delay were important contributors to the overall uncertainty in predicted cylinder pressures. For all SOIs, γ exhibited the highest UPC values (80–90 per cent) and therefore, γ must be determined with the minimum possible uncertainty to ensure satisfactory predictions of cylinder pressure histories. While the importance of γ in single-zone combustion models is well recognized, the specific contribution of the present analysis is quantification of the crank angle-resolved UPCs of γ and other model parameters to the overall model uncertainty. In this paper, it is shown that uncertainty analysis provides a unique methodology for quantitative validation of crank angle-resolved predictions from any type of engine combustion model with the corresponding experimental results. It is also shown that uncertainties in both predicted and measured cylinder pressures and heat release rates must be considered while validating any engine combustion model.

Operation of a CCHP System Using an Optimal Energy Dispatch Algorithm

The Combined Cooling, Heating, and Power (CCHP) systems have been widely recognized as a key alternative for thermal and electric energy generation because of the outstanding energy efficiency, reduced environmental emissions, and relative independence from centralized power grids. Nevertheless, the total energy cost of CCHP systems can be highly dependent on the operation of individual components and load balancing. The latter refers to the process of fulfilling the thermal and electrical demand by partitioning or “balancing” the energy requirement between the available sources of energy supply. The energy cost can be optimized through an energy dispatch algorithm which provides operational/control signals for the optimal operation of the equipment. The algorithm provides optimal solutions on decisions regarding generating power locally or buying power from the grid. This paper presents an initial study on developing an optimal energy dispatch algorithm that minimizes the cost of energy (i.e., cost of electricity from the grid and cost of natural gas into the engine and boiler) based on energy efficiency constrains for each component. A deterministic network flow model of a typical CCHP system is developed as part of the algorithm. The advantage of using a network flow model is that the power flows and efficiency constraints throughout the CCHP components can be readily visualized to facilitate the interpretation of the results. A linear programming formulation of the network flow model is presented. In the algorithm, the inputs include the cost of the electricity and fuel and the constraints include the cooling, heating, and electric load demands and the efficiencies of the CCHP components. This algorithm has been used in simulations of several case studies on the operation of an existing micro-CHP system. Several scenarios with different operational conditions are presented in the paper to demonstrate the economical advantages resulting from optimal operation.Copyright

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

An Efficient Method to Find Solutions for Transcendental Equations with Several Roots

This paper presents a method for obtaining a solution for all the roots of a transcendental equation within a bounded region by finding a polynomial equation with the same roots as the transcendental equation. The proposed method is developed using Cauchy’s integral theorem for complex variables and transforms the problem of finding the roots of a transcendental equation into an equivalent problem of finding roots of a polynomial equation with exactly the same roots. The interesting result is that the coefficients of the polynomial form a vector which lies in the null space of a Hankel matrix made up of the Fourier series coefficients of the inverse of the original transcendental equation. Then the explicit solution can be readily obtained using the complex fast Fourier transform. To conclude, the authors present an example by solving for the first three eigenvalues of the 1D transient heat conduction problem.

Extend EnergyPlus to Support Evaluation, Design, and Operation of Low Energy Buildings

During FY10-11, Pacific Northwest National Laboratory in collaboration with the EnergyPlus development team implemented the following high priority enhancements to support the simulation of high performance buildings: (1) Improve Autosizing of Heating, Ventilation, and Air Conditioning (HVAC) Components; (2) Life-Cycle Costing to Evaluate Energy Efficiency Upgrades; (3) Develop New Model to Capture Transformer Losses; (4) Enhance the Model for Electric Battery Storage; and (5) Develop New Model for Chiller-Tower Optimization. This report summarizes the technical background, new feature development and implementation details, and testing and validation process for these enhancements. The autosizing, life-cycle costing and transformer model enhancements/developments were included in EnergyPlus release Version 6.0, and the electric battery model development will be included in Version 7.0. The model development of chiller-tower optimization will be included in a later version (after Version 7.0).

Assessment of CHP System Performance With Commercial Building Benchmark Models in Different U.S. Climate Zones

Combined Cooling, Heating, and Power (CHP) systems have been widely recognized as an alternative for electric and thermal energy generation because of their outstanding energy efficiency, reduced environmental emissions, and relative independence from centralized power grids. The performance of CHP systems depends on the type of buildings and climate conditions. Recently the U.S. Department of Energy (DOE) has developed a set of standard benchmark building models. According to the DOE [1], these models cover approximately 70% of the commercial building energy use. This paper evaluates and discusses the simulations of the performance of CHP systems for several commercial building benchmark models in 16 locations representing the U.S. climate zones described in the DOE report. The evaluation has been carried out using an optimal energy dispatch algorithm. The performance index for the optimization process is varied in order to investigate the impact of optimizing operational cost, primary energy consumption, and carbon dioxide emission. The results of this simulation can be used as a guideline to end-users when deciding on energy alternatives for their buildings or by policy makers deciding on regulations for cost, primary energy, or carbon dioxide emissions.Copyright

Oscillating Heat Pipes for Waste Heat Recovery in HVAC Systems

Oscillating heat pipes (OHPs) were experimentally assessed as a passive-type heat transfer device for air-to-air heat exchange in a typical Heating Ventilation & Air conditioning system (HVAC) with adjacent air streams at different temperatures. The objective is to utilize, otherwise wasted thermal energy to pre-heat or pre-cool air in order to reduce the payload on HVAC systems, thus reducing energy consumption. OHPs can achieve effective thermal conductivities on-the-order of 10,000 W/m-K via no internal wicking structure and hence can perform aforementioned heat transfer task while providing an aerodynamic form factor. A unique working fluid with limited research inside OHPs, but with properties desirable for low grade heat fluxes, i.e. n-pentane with 70 % fill ratio, was chosen as the working fluid to achieve maximum heat transfer. Aerodynamic performance, in terms of pressure drop, was evaluated and juxtaposed with heat transfer gain/loss. The OHP thermal performance and total heat transfer for hot-environment HVAC operation was benchmarked with an empty/evacuated OHP with same overall dimensions. Results indicate that the current, atypically-long OHP is fully-capable of operating in the air-to-air convection mode for waste heat recovery for typical HVAC operating conditions. Since the OHP is passive, cost effective, and relatively aerodynamic (no fins were used), the potential cost savings for its integration into HVAC systems can be significant.Copyright

Evaluation of Regression Analysis Based Building Hourly Thermal Load Prediction Algorithms Under Climate Change

This study presents performance of two ARX (auto-regressive with exogenous, i.e., external, inputs) building hourly thermal load prediction models under influence of climate change. ARX building thermal load prediction models are of particular interest not only for their higher prediction accuracy but also for computational efficiency. Precise thermal load prediction is a significant aspect of energy planning for mixed energy distribution systems in regional and national level as well as in intelligent building energy management and control. However, in order to ensure reliability, prediction models should be able to account for influence from climate change in the upcoming years. Performance and robustness of the models over five consecutive years have been evaluated. A case study with medium office reference building in Atlanta, GA has been carried out to demonstrate prediction accuracy of both models over the period utilizing a widely accepted building energy simulation software. Results have been evaluated using statistical criteria to quantify the effect of climate change on prediction accuracy.Copyright

Technical and Economical Analysis of a Micro-CHP Facility Based on Dynamic Simulation: A Case Study

Combined Heating and Power (CHP) generation systems have been widely recognized as a key alternative for heat and electricity generation due to their outstanding energy efficiency, reduced emissions, and relative independence from centralized power grids. Similar to CHP systems, micro-CHP (micro-Cooling, Heating, and Power) systems consist of power cogeneration systems and thermally-activated components such as absorption chillers, water tanks, boilers and air handling units. There have been many studies in regard to steady-state models following load profiles in order to demonstrate the economic advantage of CHP systems. However, there has not been much work using dynamic simulation of CHP systems, which include the transient response of the building along with the rest of the CHP components. This paper presents both technical and economical results from the dynamic simulation of the micro-CHP system used to model the test facility at Mississippi State University (MSU). The results are compared to a dynamic model using a conventional heating and cooling system. TRNSYS, a dynamic simulation program, is used to simulate the time response of the micro-CHP system based on the transient heating, cooling, and electric power demand of a test facility. The performance and costs of a conventional heating and cooling system are assessed using TRNSYS and the results are then compared against the simulated performance of the micro-CHP system. Details of the simulation model include geometric and material information (e.g., size and type of walls and windows), internal gains (following the equipment and occupancy schedules), local weather information (e.g., ambient temperature, relative humidity, and solar radiation), and estimated infiltration of the test facility.© 2007 ASME