Moncef Krarti

Development of a Predictive Optimal Controller for Thermal Energy Storage Systems

This paper describes the development and simulation of a predictive optimal controller for thermal energy storage systems. The “optimal” strategy minimizes the cost of operating the cooling plant over the simulation horizon. The particular case of a popular ice storage system (ice-on-coil with internal melt) was investigated in a simulation environment. Various predictor models were analyzed with respect to their performance in forecasting cooling load data and information on ambient conditions (dry-bulb and wet-bulb temperatures). The predictor model provides load and weather information to the optimal controller in discrete time steps. An optimal storage charging and discharging strategy was planned at every time step over a fixed look-ahead time window utilizing newly available information. The first action of the optimal sequence of actions was executed over the next time step and the planning process was repeated at every following time step. The effect of the length of the planning horizon was inves...

Energy audit of building systems : an engineering approach

Introduction to Energy Audit Types of Energy Audits General Procedure for a Detailed Energy Audit Common Energy Conservation Measures Case Study: Audit of an Office Building Verification Methods of Energy Savings Energy Sources and Utility Rate Structures Energy Resources Electricity Rates Natural Gas Rates Utility Rates for Other Energy Sources Economic Analysis Basic Concepts Inflation Rate Compounding Factors Economic Evaluation Methods Among Alternatives Life-Cycle Cost Analysis Method General Procedure for an Economic Evaluation Financing Options Energy Analysis Tools Ratio-Based Methods Inverse Modeling Methods Forward Modeling Methods Electrical Systems Review of Basics Electrical Motors Lighting Systems Electrical Appliances Electrical Distribution Systems Power Quality Building Envelope Basic Heat Transfer Concepts Simplified Calculation Tools for Building Envelope Audit Selected Retrofits for Building Envelope Secondary HVAC Systems Retrofit Types of Secondary HVAC Systems Ventilation Systems Ventilation of Parking Garages Indoor Temperature Controls Upgrade of Fan Systems Common HVAC Retrofit Measures Central Heating Systems Basic Combustion Principles Boiler Efficiency Improvements Existing Boiler Tune-Up Cooling Equipment Basic Cooling Principles Types of Cooling Systems Water Distribution Systems District Cooling Systems Multichiller Systems Energy Conservation Measures Energy Management Control Systems Basic Control Principles Energy Management Systems Control Applications Compressed Air Systems Review of Basic Concepts Common Energy Conservation Measures for Compressed Air Systems Thermal Energy Storage Systems Types of TES Systems Principles of TES Systems Charging/Discharging of TES systems TES Control Strategies Measures for Reducing Operating Costs Cogeneration Systems History of Cogeneration Types of Cogeneration Systems Evaluation of Cogeneration Systems Case Study Heat Recovery Systems Types of Heat Recovery Systems Performance of Heat Recovery Systems Simplified Analysis Methods Water Management Indoor Water Management Outdoor Water Management Swimming Pools Methods for Estimating Energy Savings General Procedure Energy Savings Estimation Models Applications Uncertainty Analysis Case Studies Reporting Guidelines Reporting a Walk-Through Audit Case Study 1: Walk-Through Audit of a Residence Case Study 2: Standard Audit of a Residence Case Study 3: Audit of a Museum References Appendices

Guidelines for improved performance of ice storage systems

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.

ANALYTICAL MODEL FOR HEAT TRANSFER IN AN UNDERGROUND AIR TUNNEL

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.

Building Energy Use Prediction and System Identification Using Recurrent Neural Networks

Following several successful applications of feedforward neural networks (NNs) to the building energy prediction problem a more difficult problem has been addressed recently: namely, the prediction of building energy consumption well into the future without knowledge of immediately past energy consumption. This paper will report results on a recent study of six months of hourly data recorded at the Zachry Engineering Center (ZEC) in College Station, TX. Also reported are results on finding the R and C values for buildings from networks trained on building data.

ITPE technique applications to time-varying two-dimensional ground-coupling problems

Abstract The interzone temperature profile estimation (ITPE) procedure is used to find two-dimensional analytical series solutions for the time-varying heat transfer between ground and slab-on-grade floors or basements. The undisturbed soil temperature is approximated as a sinusoidal function of time and the ITPE procedure is coupled with the complex temperature technique to derive the steady-periodic solutions for both configurations. The influence of insulation and of a fixed-temperature water table on the temporal behavior of slab-on-grade floors and basements is treated analytically for the first time.

Analytical Model to Predict Annual Soil Surface Temperature Variation

An analytical model is developed to predict the annual variation of soil surface temperature from readily available weather data and soil thermal properties. The time variation is approximated by a first harmonic function characterized by an average, an amplitude, and a phase lag. A parametric analysis is presented to determine the effect of various factors such as evaporation, soil absorptivity, and soil convective properties on soil surface temperature. A comparison of the model predictions with experimental data is presented. The comparative analysis indicates that the simplified model predicts soil surface temperatures within ten percent of measured data for five locations.

An overview of artificial intelligence-based methods for building energy systems

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.

Parametric Analysis of Active and Passive Building Thermal Storage Utilization

Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and on weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the buildings massive structure or by using active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this paper investigates the merits of harnessing both storage media concurrently in the context of optimal control for a range of selected parameters. A parametric analysis was conducted utilizing an EnergyPlus-based simulation environment to assess the effects of building mass, electrical utility rates, season and location, economizer operation, central plant size, and thermal comfort. The findings reveal that the cooling-related on-peak electrical demand and utility cost of commercial buildings can be substantially reduced by harnessing both thermal storage inventories using optimal control for a wide range of conditions.

Foundation heat loss from heated concrete slab-on-grade floors

Abstract In recent years, there has been a renewed interest in heated concrete slab floors to provide for space heating in both residential and commercial buildings. The existing design procedures for these heating systems are based on simplified thermal models with several assumptions. In particular, the simplified models assume that both the upper and the lower concrete slab surface are isothermal and that the heat transfer through the bottom of the slab surfaces is uniformly distributed over the entire surface. In this paper, a more realistic and flexible model for heated or cooled concrete slab floors is considered to determine the heat transfer between the concrete slab and the ground. In particular, steady-state and steady-periodic semi-analytical solutions are developed to determine the temperature field within the ground medium and within the concrete slab-on-grade floor where hot or chilled water pipes are embedded. The solution presented in this paper is applied to determine the ground heat loss/gain for a heated or cooled floor under various design conditions including the level of floor insulation, and the temperature of the water pipes. These solutions are obtained using the interzone temperature profile estimation (ITPE) procedure. Detailed analysis is presented to determine the effect of the slab insulation configuration on soil and slab temperature field and on the monthly variation of the total slab heat loss.