Evaluation of Ground Source Heat Pump Energy, Demand, and Greenhouse Potential in Colorado Residential Buildings

ABSTRACT This paper summarizes the results of a detailed energy analysis carried out for a typical Colorado residence using three different HVAC systems for 10 distinct locations in Colorado. The HVAC systems considered in the analysis include: 78% efficient furnace with a 13 SEER air conditioner Vertical well ground source heat pump with a heating COP of 3.5 and a cooling EER of 17.1 Slinky ground source heat pump with a heating COP of 3.5 and a cooling EER of 17.

Optimal Control Strategies for Switchable Transparent Insulation Systems Applied to Smart Windows for US Residential Buildings

This paper evaluates the potential energy use and peak demand savings associated with optimal controls of switchable transparent insulation systems (STIS) applied to smart windows for US residential buildings. The optimal controls are developed based on Genetic Algorithm (GA) to identify the automatic settings of the dynamic shades. First, switchable insulation systems and their operation mechanisms are briefly described when combined with smart windows. Then, the GA-based optimization approach is outlined to operate switchable insulation systems applied to windows for a prototypical US residential building. The optimized controls are implemented to reduce heating and cooling energy end-uses for a house located four US locations, during three representative days of swing, summer, and winter seasons. The performance of optimal controller is compared to that obtained using simplified rule-based control sets to operate the dynamic insulation systems. The analysis results indicate that optimized controls of STISs can save up to 81.8% in daily thermal loads compared to the simplified rule-set especially when dwellings are located in hot climates such as that of Phoenix, AZ. Moreover, optimally controlled STISs can reduce electrical peak demand by up to 49.8% compared to the simplified rule-set, indicating significant energy efficiency and demand response potentials of the SIS technology when applied to US residential buildings. &nbsp;</p

ISEC2005-76077 ANALYSIS OF ELECTRICAL ENERGY SAVINGS FROM DAYLIGHTING THROUGH SKYLIGHTS

ABSTRACT This paper provides a simplified analysis tool to assess the energy saving potential of daylighting for commercial buildings through skylights. Specifically, the impact of daylighting is investigated for various fenestration opening sizes, glazing types, control strategies, and geographic locations. A top floor of a prototypical office building has been considered in the analysis. The results obtained for the office building can be applied to other types of buildings such as retails stores, schools, and warehouses. Based on the simulation analysis results, it was determined that skylight to floor ratio more than 0.3 does not affect significantly the lighting energy savings. An optimum value of skylight to floor area ratio was found to be 0.2 to minimize the annual total building energy use

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

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 weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very simple short-term prediction models to realize almost all of the theoretical potential of this control strategy. Further work evaluated the impact of modeling accuracy on the model-based closed-loop predictive optimal controller to minimize utility cost. The following guidelines have been derived: For an internal heat gain dominated commercial building, reasonable geometry simplifications are acceptable without a loss of cost savings potential. In fact, zoning simplification may improve optimizer performance and save computation time. The mass of the internal structure did not show a strong effect on the optimization. Building construction characteristics were found to impact building passive thermal storage capacity. It is thus advisable to make sure the construction material is well modeled. Zone temperature setpoint profiles and TES performance are strongly affected by mismatches in internal heat gains, especially when they are underestimated. Since they are a key factor in determining the building cooling load, efforts should be made to keep the internal gain mismatch as small as possible. Efficiencies of the building energy systems affect both zone temperature setpoints and active TES operation because of the coupling of the base chiller for building precooling and the icemaking TES chiller. Relative efficiencies of the base and TES chillers will determine the balance of operation of the two chillers. The impact of mismatch in this category may be significant. Next, a parametric analysis was conducted to assess the effects of building mass, utility rate, building location and season, thermal comfort, central plant capacities, and an economizer on the cost saving performance of optimal control for active and passive building thermal storage inventory. The key findings are: (1) Heavy-mass buildings, strong-incentive time-of-use electrical utility rates, and large on-peak cooling loads will likely lead to attractive savings resulting from optimal combined thermal storage control. (2) By using economizer to take advantage of the cool fresh air during the night, the building electrical cost can be reduced by using less mechanical cooling. (3) Larger base chiller and active thermal storage capacities have the potential of shifting more cooling loads to off-peak hours and thus higher savings can be achieved. (4) Optimal combined thermal storage control with a thermal comfort penalty included in the objective function can improve the thermal comfort levels of building occupants when compared to the non-optimized base case. Lab testing conducted in the Larson HVAC Laboratory during Phase 2 showed that the EnergyPlus-based simulation was a surprisingly accurate prediction of the experiment. Therefore, actual savings of building energy costs can be expected by applying optimal controls from simulation results

Evaluation of Ground-Source Variable Refrigerant Flow System for US Office Buildings

This paper evaluates the energy performance of ground-source variable refrigerant flow (VRF) systems to condition office buildings located in various U.S. climates. Specifically, the performance of the ground-source VRF systems was determined and evaluated against that achieved by conventional space heating and cooling systems, including packaged terminal air-conditioners (PTACs), water-source heat pumps (WSHPs), ground-source heat pumps (GSHPs), and water-source VRF systems. A comparative analysis shows that ground-source VRF systems require significantly lower source energy uses than other heating and cooling systems in all U.S. climates, ranging from 21% to 50% for PTACs, from 36% to 52% for WSHPs, from 22% to 49% for GSHPs, and from 4% to 19% for water-source VRFs. These results indicate that ground-source VRFs can be suitable heating and cooling systems for all U.S. climates when designing high-energy-performance commercial buildings

A SIMPLIFIED METHOD TO ESTIMATE COOLING ENERGY SAVINGS FROM NIGHT VENTILATION FOR OFFICE BUILDINGS

ABSTRACT This paper provides a simplified analysis method and to evaluate the potential of night ventilation to save cooling energy for office buildings. Specifically, impacts on cooling energy performance are investigated for various combinations of night ventilation flow rates and duration periods. The analysis results indicate that an increase of ventilation duration period and volume rate leads to greater night ventilation benefits for dwellings located in Denver, CO. However, an increase of the ventilation volume rate above 5 air changes per hour has a little impact on cooling energy savings. When the ventilation period is short (less than 10 hours), and the flow rate is high (more than 3 ACH), the cooling energy savings from night ventilation increase linearly with the ventilation duration period length. A simplified calculation method has been developed based on the results of a series of parametric simulation analyses. Commercial building designers and operators can use the proposed simplified calculation tool to assess the effectiveness of night ventilation in reducing cooling energy use

Energy productivity analysis framework for buildings : a case study of GCC region

A new analysis framework is developed and applied to assess the benefits of building energy efficiency policies and programs. One of the main advantages of the new energy productivity analysis is that it accounts for both economic and energy performances of energy efficiency actions using only one metric. Specifically, the approach applies the concept of energy productivity to the building sector and accounts for both value added and energy savings of energy efficiency measures. Moreover, the proposed analysis accounts for all quantifiable benefits of energy efficiency programs including economic, environmental, and social. In this paper, the general guidelines for the energy productivity analysis are first described. Then, the analysis is applied to evaluate energy efficiency renewable energy programs for both existing and new buildings in the Gulf Cooperation Council (GCC) countries. The analysis results indicate that retrofitting the existing building stock can provide significant benefits and can improve the energy productivity of the building sector in all GCC countries and free up large energy volumes and investment potentials to the development of other economic sectors. In particular, the analysis indicates that reduction in energy consumption, peak demand, and carbon emissions due to deep retrofit programs for the existing building stock can double the energy productivity of the GCC region

Pyeongchan Ihm Design Optimization of Energy Efficient Office Buildings in Tunisia

Optimal and cost-effective energy efficiency design and operation options are evaluated for office buildings in Tunisia. In the analysis, several design and operation features are considered including orientation, window location and size, high performance glazing types, wall and roof insulation levels, energy efficient lighting systems, daylighting controls, temperature settings, and energy efficient heating and cooling systems. First, the results of the optimization results from a sequential search technique are compared against those obtained by a more time consuming brute-force optimization approach. Then, the optimal design features for a prototypical office building are determined for selected locations in Tunisia. The optimization results indicate that utilizing daylighting controls, energy efficient lighting fixtures, and low-e double glazing, and roof insulation are required energy efficiency measures to design high energy performance office buildings throughout climatic zones in Tunisia. In particular, it is found that implementing these measures can cost-effectively reduce the annual energy use by 50% compared to the current design practices of office buildings in Tunisia

Evaluation of Energy Efficiency Potential for the Building Sector in the Arab Region

The paper overviews the current energy demand trends in the building sector for the Arab region using reported historical energy consumption. Moreover, the paper describes the current energy efficiency policies and regulations for all the Arab countries specific to both residential and commercial buildings. Finally, the paper evaluates potential benefits for large-scale energy efficiency programs specific to new and existing building stocks within the Arab region using a bottom-up analysis approach. The analysis of the available energy consumption for all the Arab countries has shown that the Arab region presents a significant variation in energy consumption levels between its sub-regions and countries. Indeed, the Arab region includes oil-producing countries such as Saudi Arabia with the largest energy use per capita in the World with over 9000 kWh/person of electricity used annually in buildings. However, the same region has the least developed countries such as Sudan and Yemen with the lowest energy use per capita in the World with barely 100 kWh/person/year of electrical consumption. The review of the existing regulations has indicated that several Arab countries have not implemented any energy efficiency codes and standards for building envelope, lighting, heating and cooling equipment, and appliances. A cost-effectiveness analysis has indicated that the Arab region can incur significant benefits in upgrading the energy efficiency of its new and existing buildings especially its households. Specifically, the adoption and the enforcement of stringent energy efficiency codes for new residential and commercial buildings can result in a reduction of 12.7 TWh/year in final annual energy consumption for the Arab region. Moreover, retrofit programs targeting existing buildings can save up to 470 TWh or a third of the building sector final energy consumption per year after 2030. Combining comprehensive energy efficiency requirements for new buildings and extensive retrofit programs for existing buildings would reduce the total final energy consumption of the building sector in the Arab region by 600 TWh by 2030 and by 900 TWh by 2050 if all the energy programs start to be implemented by 2020

“Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory”

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 weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building’s massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigates the merits of harnessing both storage media concurrently in the context of predictive optimal control. The analysis, modeling, and simulation research presented in this topical report covers the first of three project phases. Based on the new dynamic building simulation program EnergyPlus, we added a utility rate module, two thermal energy storage models, and incorporated a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods. The objective function is the total utility bill including the cost of heating and a time-of-use electricity rate with demand charges. The evaluation of the combined optimal control assumes perfect weather prediction and match between the building model and the actual building counterpart. The analysis shows that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be drastically reduced and justify the development of a predictive optimal controller that accounts for uncertainty in predicted variables and modeling mismatch in real time