• Energy Research

A simplified analytical model is developed to determine the energy performance of an underground air tunnel. The model assumes that the air tunnel-ground system reaches periodic and quasi-steady state behavior after some days of operation. The model can predict the air temperature variation along the air tunnel for any hour of the day. It can also determine the daily mean and amplitude of the total cooling/heating effect of the tunnel. Parametric analysis is conducted to determine the effect of tunnel hydraulic diameter and air flow rate on the heat transfer between ground and air inside the tunnel. The model is validated against measured data.

A simplified analytical model is developed to determine the energy performance of an underground air tunnel. The model assumes that the air tunnel-ground system reaches periodic and quasi-steady state behavior after some days of operation. The model can predict the air temperature variation along the air tunnel for any hour of the day. It can also determine the daily mean and amplitude of the total cooling/heating effect of the tunnel. Parametric analysis is conducted to determine the effect of tunnel hydraulic diameter and air flow rate on the heat transfer between ground and air inside the tunnel. The model is validated against measured data.

Abstract A new electrical lighting and daylighting simulation analysis environment is developed to help designers assess optimal design configurations and operating strategies for electrical lighting fixtures in order to reduce energy use. In this paper, two applications of the simulation environment are presented to optimize the electrical lighting circuiting layouts design and the location of desks within daylight spaces. The results from these applications illustrate how the simulation environment and optimal daylight-base lighting controls can help building and lighting engineers and green building consultants improve the design of lighting and daylighting systems in order to construct and operate high energy performance buildings.

Abstract A new electrical lighting and daylighting simulation analysis environment is developed to help designers assess optimal design configurations and operating strategies for electrical lighting fixtures in order to reduce energy use. In this paper, two applications of the simulation environment are presented to optimize the electrical lighting circuiting layouts design and the location of desks within daylight spaces. The results from these applications illustrate how the simulation environment and optimal daylight-base lighting controls can help building and lighting engineers and green building consultants improve the design of lighting and daylighting systems in order to construct and operate high energy performance buildings.

This paper provides a numerical solution for simultaneous heat and moisture transfer within frozen soil beneath slab foundations of refrigerated warehouses. The developed solution is validated using data from experimental tests. A parametric analysis is then performed to determine the impact of slab insulation levels and to estimate the time required to reach steady-state ground-coupled heat transfer conditions. Finally, the solution is utilized to determine an effective soil thermal conductivity that could be used in a purely heat conduction model for ground-coupled heat transfer beneath freezers.

This paper provides a numerical solution for simultaneous heat and moisture transfer within frozen soil beneath slab foundations of refrigerated warehouses. The developed solution is validated using data from experimental tests. A parametric analysis is then performed to determine the impact of slab insulation levels and to estimate the time required to reach steady-state ground-coupled heat transfer conditions. Finally, the solution is utilized to determine an effective soil thermal conductivity that could be used in a purely heat conduction model for ground-coupled heat transfer beneath freezers.

Abstract This paper describes simulation-based results of an investigation of a commercial cooling plant with an ice storage system. Various ice storage systems, chiller compressors, and building types were analyzed under four different control strategies. Optimal control as the strategy that minimizes the total operating cost (demand and energy charges) served as a benchmark to assess the relative performance of three conventional controls (chiller-priority, constant-proportion, and storage-priority control) and to determine aspects in need of improvement in order to apply these conventional controls better and to enhance the cost saving potential of ice storage systems. Independent of the non-cooling electrical load profile, it was found that good efficiency of the cooling plant in the icemaking mode and rate structures with strong load-shifting incentives are prerequisites for making cool storage successful. Chillers with poor performance at subfreezing evaporator temperatures require significant on- to off-peak differentials in the energy and demand rates to yield substantial savings. The relative performance benefit of optimal control over conventional controls increases when rate-based load-shifting incentives are weak. With cooling-related electrical loads being large compared to non-cooling loads, all conventional controls improve their performance when slowly recharging during off-peak periods to contain off-peak demand. On-peak demand reduction of storage-priority is near-optimal for many cases. Guidelines are presented to improve the load-shifting performance of chiller-priority and constant-proportion control.

Abstract This paper describes simulation-based results of an investigation of a commercial cooling plant with an ice storage system. Various ice storage systems, chiller compressors, and building types were analyzed under four different control strategies. Optimal control as the strategy that minimizes the total operating cost (demand and energy charges) served as a benchmark to assess the relative performance of three conventional controls (chiller-priority, constant-proportion, and storage-priority control) and to determine aspects in need of improvement in order to apply these conventional controls better and to enhance the cost saving potential of ice storage systems. Independent of the non-cooling electrical load profile, it was found that good efficiency of the cooling plant in the icemaking mode and rate structures with strong load-shifting incentives are prerequisites for making cool storage successful. Chillers with poor performance at subfreezing evaporator temperatures require significant on- to off-peak differentials in the energy and demand rates to yield substantial savings. The relative performance benefit of optimal control over conventional controls increases when rate-based load-shifting incentives are weak. With cooling-related electrical loads being large compared to non-cooling loads, all conventional controls improve their performance when slowly recharging during off-peak periods to contain off-peak demand. On-peak demand reduction of storage-priority is near-optimal for many cases. Guidelines are presented to improve the load-shifting performance of chiller-priority and constant-proportion control.

An overview of commonly used methodologies based on the artificial intelligence approach is provided with a special emphasis on neural networks, fuzzy logic, and genetic algorithms. A description of selected applications to building energy systems of AI approaches is outlined. In particular, methods using the artificial intelligence approach for the following applications are discussed: Prediction energy use for one building or a set of buildings (served by one utility), Modeling of building envelope heat transfer, Controlling central plants in buildings, and Fault detection and diagnostics for building energy systems.