Trade-Off Between Energy Consumption and Utility Cost in the Optimal Control of Active and Passive Building Thermal Storage Inventory

Solar Energy ◽  
2004 ◽  
Author(s):  
Gregor P. Henze
Keyword(s):  
Optimal Control ◽  
Energy Consumption ◽  
Thermal Energy ◽  
Peak Load ◽  
Electrical Energy ◽  
Thermal Storage ◽  
Commercial Building ◽  
Trade Off ◽  
Massive Structure ◽  
Utility Cost

In contrast to building energy conversion equipment, less improvement has been achieved in thermal energy distribution, storage and control systems in terms of energy efficiency and peak load reduction potential. Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates are designed to 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 (passive storage) or by using active thermal energy storage systems such as ice storage. Recent theoretical and experimental work showed that the simultaneous utilization of active and passive building thermal storage inventory can save significant amounts of utility costs to the building operator, yet in many cases at the expense of increased electrical energy consumption. This article investigates an approach to ensure that a commercial building utilizing both thermal batteries does not incur excessive energy consumption. The model-based predictive building controller is modified to trade off energy cost against energy consumption. This work shows that buildings can be operated in a demand-responsive fashion to substantially reduce utility costs, however, at the expense of increased energy consumption. Placing a greater emphasis on energy consumption led to a reduction in the savings potential. In the limiting case of energy-optimal control, the reference control was replicated, i.e., if only energy consumption is of concern, neither active nor passive building thermal storage should be utilized. On the other hand, cost-optimal control suggests strongly utilizing both thermal storage inventories.

Energy and Cost Minimal Control of Active and Passive Building Thermal Storage Inventory

2005 ◽  
Vol 127 (3) ◽  
pp. 343-351 ◽  
Author(s):  
Gregor P. Henze
Keyword(s):  
Optimal Control ◽  
Energy Consumption ◽  
Thermal Energy ◽  
Peak Load ◽  
Cost Savings ◽  
Electrical Energy ◽  
Thermal Storage ◽  
Coefficient Of Performance ◽  
Electrical Energy Consumption ◽  
Electricity Cost

In contrast to building energy conversion equipment, less improvement has been achieved in thermal energy distribution, storage and control systems in terms of energy efficiency and peak load reduction potential. Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid and time-of-use electricity rates are designed to 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 building’s massive structure (passive storage) or by using active thermal energy storage systems such as ice storage. Recent theoretical and experimental work showed that the simultaneous utilization of active and passive building thermal storage inventory can save significant amounts of utility costs to the building operator, yet increased electrical energy consumption may result. The article investigates the relationship between cost savings and energy consumption associated with conventional control, minimal cost and minimal energy control, while accounting for variations in fan power consumption, chiller capacity, chiller coefficient-of-performance, and part-load performance. The model-based predictive building controller is employed to either minimize electricity cost including a target demand charge or electrical energy consumption. This work shows that buildings can be operated in a demand-responsive fashion to substantially reduce utility costs with marginal increases in overall energy consumption. In the case of energy optimal control, the reference control was replicated, i.e., if only energy consumption is of concern, neither active nor passive building thermal storage should be utilized. On the other hand, cost optimal control suggests strongly utilizing both thermal storage inventories.

Parametric Analysis of Active and Passive Building Thermal Storage Utilization*

2005 ◽  
Vol 127 (1) ◽  
pp. 37-46 ◽  
Author(s):  
Guo Zhou ◽  
Moncef Krarti ◽  
Gregor P. Henze
Keyword(s):  
Optimal Control ◽  
Parametric Analysis ◽  
Thermal Storage ◽  
Plant Size ◽  
Commercial Buildings ◽  
Electricity Rates ◽  
Massive Structure ◽  
Wide Range ◽  
Electrical Loads ◽  
Utility Cost

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 building’s 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.

Parametric Analysis of Active and Passive Building Thermal Storage Utilization

Solar Energy ◽  
2004 ◽  
Author(s):  
Guo Zhou ◽  
Moncef Krarti ◽  
Gregor P. Henze
Keyword(s):  
Optimal Control ◽  
Parametric Analysis ◽  
Thermal Storage ◽  
Plant Size ◽  
Commercial Buildings ◽  
Electricity Rates ◽  
Massive Structure ◽  
Wide Range ◽  
Electrical Loads ◽  
Utility Cost

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 building’s 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.

Energy Conservation and Storage Systems

2002 ◽  
Vol 20 (5) ◽  
pp. 391-399 ◽  
Author(s):  
Ayhan Demirbaş
Keyword(s):  
Energy Management ◽  
Thermal Energy ◽  
Waste Heat ◽  
Storage Systems ◽  
Electrical Energy ◽  
Thermal Storage ◽  
Energy Costs ◽  
Thermal Battery ◽  
Storage Technology ◽  
And Storage

In response to increasing electrical energy costs and the desire for better lad management, thermal storage technology has recently been developed. Storage of thermal energy in the form of sensible and latent heat has become an important aspect of energy management with the emphasis on efficient use and conservation of the waste heat and solar energy in industry and buildings. Thermal storage has been characterized as a kind of thermal battery.

scholarly journals Reduction of Energy Intensity in Broiler Facilities: Methodology and Strategies

2021 ◽  
Vol 8 ◽  
Author(s):  
Catherine Baxevanou ◽  
Dimitrios Fidaros ◽  
Ilias Giannenas ◽  
Eleftherios Bonos ◽  
Ioannis Skoufos
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Thermal Energy ◽  
Energy Intensity ◽  
Electrical Energy ◽  
Energy Performance ◽  
Advanced Technology ◽  
Energy Audit ◽  
Wind Potential ◽  
Technology Level

Broiler facilities consume a lot of energy resulting in natural source depletion and greater greenhouse gas emissions. A way to assess the energy performance of a broiler facility is through an energy audit. In the present paper, an energy protocol for an energy audit is presented covering both phases of data collection and data elaboration. The operational rating phase is analytically and extendedly described while a complete mathematical model is proposed for the asset rating phase. The developed energy audit procedure was applied to poultry chambers located in lowland and mountainous areas of Epirus Greece for chambers of various sizes and technology levels. The energy intensity indices varied from 46 to 89 kWh/m2 of chamber area 0.25–0.48 kWh/kg of produced meat or 0.36–1.3 kWh/bird depending on the chamber technology level (insulation, automation, etc.) and the location where the unit was installed. The biggest energy consumer was heating followed by energy consumption for ventilation and cooling. An advanced technology level can improve energy performance by ~ 27%−31%. Proper insulation (4–7 cm) can offer a reduction of thermal energy consumption between 10 and 35%. In adequately insulated chambers, the basic heat losses are due to ventilation. Further energy savings can be achieved with more precise ventilation control. Automation can offer additional electrical energy saving for cooling and ventilation (15–20%). Energy-efficient lights can offer energy saving up to 5%. The use of photovoltaic (PV) technology is suggested mainly in areas where net-metering holds. The use of wind turbines is feasible only when adequate wind potential is available. Solar thermal energy is recommended in combination with a heat pump if the unit's heating and cooling systems use hot/cold water or air. Finally, the local production of biogas with anaerobic fermentation for producing thermal or electrical energy, or cogenerating both, is a choice that should be studied individually for each farm.

scholarly journals Improving performance of direct expansion air conditioning systems while reducing electricity consumption through using hybrid energy

2021 ◽  
Vol 289 ◽  
pp. 01014
Author(s):  
Ahmed Al–Okbi ◽  
Yuri Vankov ◽  
Hakim Kadhim
Keyword(s):  
Energy Consumption ◽  
Thermal Energy ◽  
Air Conditioning ◽  
Electrical Energy ◽  
Coefficient Of Performance ◽  
Electricity Production ◽  
Conventional System ◽  
Solar Thermal Energy ◽  
Continuous Power ◽  
Air Conditioning Systems

At the present time, operating hybrid air-conditioning systems that use solar energy to saving electrical energy while improving the performance has become necessary to protect the environment, reduce pollution and emissions caused by using fuels and gases. In Iraq, temperatures reach half the boiling point at summer, therefore the demand for air conditioning systems increases, air conditioning systems consume more than half of average electricity production which affects on reliability and stability of the electrical energy thus leads to a continuous power outage. So, the issue of using renewable energies becomes more attractive. Because of saving energy leads to ensuring the reliability of electricity and reduces the consumption of fuels and gases that pollute on the environment and negatively affect on the ozone layer. In the current research, the atmosphere of Baghdad city was used to collect solar thermal energy and convert it into thermal energy through an evacuated solar collector by water and combine it with a conventional air conditioner in the part that follows the compressor in order to reduce the electrical energy consumption on the compressor and increase coefficient of performance. Several tests were conducted on the proposed system to compare results with the conventional system and evaluate performance. The results showed that the coefficient of performance with the hybrid system became 8.97 more efficient instead of 4.27 compared to the conventional system, and the energy consumption decreased by 52%.

scholarly journals Modifikasi Pengering Tipe Tray Dryer Dengan Penambahan Insulator

2020 ◽  
Vol 4 (4) ◽  
pp. 422-431
Author(s):  
Iqbal Fahri Tobing ◽  
Mustaqimah Mustaqimah ◽  
Raida Agustina
Keyword(s):  
Energy Consumption ◽  
Thermal Energy ◽  
Performance Test ◽  
Raw Materials ◽  
Electric Energy ◽  
Electrical Energy ◽  
Energy Calculation ◽  
Drying Process ◽  
Drying Time ◽  
Drying Efficiency

Abstrak. Pengering tipe Tray Dryer merupakan salah satu alat pengering rak atau pengering kabinet yang dapat digunakan untuk mengeringkan berbagai jenis bahan baku makanan. Alat pengering ini dirancang dengan tipe paralel flow tray dimana udara panas yang dihasilkan akan disirkulasikan sejajar dengan permukaan rak pengering dan bekerja menggunakan sumber energi listrik. Penelitian ini bertujuan untuk memodifikasi pengering tray dryer dengan penambahan insulator dan mengetahui konsumsi energi alat pengering tray dryer pada pengeringan kunyit. Parameter pengujian uji kinerja alat tanpa bahan meliputi distribusi suhu, kelembaban relatif dan kecepatan aliran udara dan untuk perhitungan konsumsi energi meliputi penggunaan energi listrik, perhitungan energi thermal, energi mengeringkan bahan, energi untuk menguapkan air bahan, efisiensi pengeringan, energi kipas dan kehilangan energi melalui cerobong. Pada pengujian pengering tray dryer suhu yang digunakan adalah 55°C. Hasil penelitian menunjukkan bahwa secara fungsional dan struktural alat pengering tray dryer setelah dimodifikasi dengan melapisi dinding luar ruang pengering dapat beroperasi dengan baik, proses pengeringan lebih cepat dan energi yang digunakan juga sedikit dibandingkan dengan sebelum dimodifikasi. Konsumsi energi listrik pada alat pengering tray dryer setelah dimodifikasi pada saat proses pengeringan dengan suhu 35oC selama 6,5 jam sebesar 35,33 kWh (127,2 MJ), pada suhu 45oC sebesar 24,26 kWh (88,06 MJ) dengan lamanya pengeringan selama 4,5 jam dan suhu 55oC sebesar 18,89 kWh (68,01 MJ) dengan lama pengeringan selama 3,5 jam, hal ii disebabkan lama pengeringan merupakan salah satu faktor yang menyebabkan besar kecilnya konsumsi energi listrik. Konsumsi energi thermal selama proses pengeringan dengan suhu 35°C adalah sebesar 17,53 MJ, suhu 45°C sebesar 19,54 MJ dan suhu 55°C sebesar 21,34 MJ. Berdasarkan hasil kalkulasi antara energi listrik dan energi thermal didapatkan efisiensi pengeringan pada suhu 35°C sebesar 27,80%, suhu 45°C sebesar 22,2% dan suhu 55°C sebesar 31,4%.Modification Of Tray Dryer With InsulatorAbstract. Tray Dryer is a type of dryer or cabinet dryer that can be used to dry various types of food raw materials. This dryer is designed with a parallel flow tray type where the hot air generated will be circulated parallel to the surface of the drying rack and work using an electric energy source. This study aims to modify the tray dryer with the addition of an insulator and determine the energy consumption of dryer dryers in turmeric drying. The test parameters of the performance test of equipment without material include temperature distribution, relative humidity and air flow velocity and for the calculation of energy consumption including the use of electrical energy, thermal energy calculation, energy drying material, energy to evaporate material water, drying efficiency, fan energy and energy loss through chimney. In testing the tray dryer dryer the temperature used is 55 ° C. The results showed that functionally and structurally the tray dryer after being modified by covering the outer walls of the drying chamber could operate well, the drying process was faster and the energy used was also less compared to before it was modified. Electric energy consumption in the tray dryer after being modified during the drying process with a temperature of 35oC for 6.5 hours amounted to 35.33 kWh (127.2 MJ), at a temperature of 45oC of 24.26 kWh (88.06 MJ) with a duration drying for 4.5 hours and a temperature of 55oC of 18.89 kWh (68.01 MJ) with a drying time of 3.5 hours, this is due to the length of drying is one of the factors causing the size of the electrical energy consumption. The consumption of thermal energy during the drying process with a temperature of 35 ° C is 17.53 MJ, a temperature of 45 ° C is 19.54 MJ and a temperature of 55 ° C is 21.34 MJ. Based on the results of calculations between electrical energy and thermal energy obtained drying efficiency at a temperature of 35 ° C at 27.80%, a temperature of 45 ° C at 22.2% and a temperature of 55 ° C at 31.4%

scholarly journals Influence of Population Density on CO2 Emissions Eliminating the Influence of Climate

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1193
Author(s):  
Pedro J. Zarco-Periñán ◽  
Irene M. Zarco-Soto ◽  
Fco. Javier Zarco-Soto
Keyword(s):  
Energy Consumption ◽  
Population Density ◽  
Co2 Emissions ◽  
Thermal Energy ◽  
Electrical Energy ◽  
Renewable Energies ◽  
Thermal Origin ◽  
Extreme Groups ◽  
The City

More than 50% of the world’s population lives in cities. Its buildings consume more than a third of the energy and generate 40% of the emissions. This makes cities in general and their buildings in particular priority points of attention for policymakers and utilities. This paper uses population density as a variable to know its influence on energy consumption and emissions produced in buildings. Furthermore, to show its effect more clearly, the influence of the climate was eliminated. The usual energy consumption in buildings is thermal and electrical. The study was carried out at the city level, both per inhabitant and per household. The area actually occupied by the city was considered. The proposed method was applied to the case of Spanish cities with more than 50,000 inhabitants. The results show that the higher the population density, the higher the energy consumption per inhabitant and household in buildings. The consumption of thermal energy is elastic, while that of electrical energy is inelastic, varying more than 100% between extreme groups. Regarding CO2 emissions, the higher the population density, the higher the emissions. Emissions of electrical origin barely vary by 2% and are greater than those of thermal origin. In addition, the proportion of emissions of electrical origin, with respect to the total, decreases with increasing population density from 74% to 55%. This research aims to help policymakers and utilities to take the appropriate measures that favor the use of renewable energies and reduce CO2 emissions.

scholarly journals Forecasting Load on PT PLN (Persero) Metro Substations (GI) Using Combined Methods for Electrical Needs in Metro City 2019 - 2029

Electrician ◽  
2019 ◽  
Vol 13 (2) ◽  
pp. 43
Author(s):  
Candra Saigustia
Keyword(s):  
Energy Consumption ◽  
Technological Progress ◽  
Peak Load ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Growth Data ◽  
Combined Method ◽  
Energy Needs ◽  
Technological Developments ◽  
Number Of Customers

Abstract — Electricity consumption in Metro City has increased along with the increase in population, economic activity, technological progress and growth of households. Electrical energy is needed for the interests of industry, households and other activities as well as to support increasingly advanced technological developments The researcher used load forecasting with a combined method based on economic growth, population growth, and the growth of households in Metro City. The data used in this study are growth data that occurred from 2014 to 2018. The results of this paper is forecasting the number of customers, load energy consumption (MWh), total energy requirements (MWh), connected power (kVA), and peak load (MW). Energy consumption growth every year has the same tendency as in previous years. In the household sector, energy consumption will grow higher each year than other sectors. In 2029, it estimated that the peak load that will occur at Metro substations, PT PLN (Persero) Rayon Metro City is 92.62 MW.Keywords — Forecasting, Electrical Energy Needs, Combined Method, PT PLN, Metro City

scholarly journals Optimal schedule and temperature control of stratified water heaters

2021 ◽  
Author(s):  
J.A.A. Engelbrecht ◽  
MJ Ritchie ◽  
MJ Booysen
Keyword(s):  
Optimal Control ◽  
Energy Consumption ◽  
Search Algorithm ◽  
Control Strategies ◽  
Optimal Schedule ◽  
Electrical Energy ◽  
Hot Water ◽  
Energy Usage ◽  
Water Heater ◽  
Water Heaters

Water heating is a major component of domestic electrical energy usage, in some countries contributing to 25% of the residential sector energy consumption. Demand response strategies can reduce the time-of-use costs and overall electrical energy consumption. We present a method to reduce the electrical energy usage itself. Our novel heating schedule control minimises the electric water heater's energy usage without compromising user convenience. We achieve optimal control, while taking into account the natural temperature stratification of the water in the tank, using the A* search algorithm. Since previous research assumes a one-node thermal model, we also assess the effect of excluding stratification. We match three optimal control strategies to a baseline: the standard "always on'" thermostat control. The first two strategies respectively match the temperature and the energy of the hot water supplied by the water heater. The third, a variation on the second, includes a method of preventing the growth of Legionella bacteria. We tested 77 water heaters over four weeks, a week for each season, and all three strategies saved energy. The median savings were 6.3% for temperature-matching, 21.9% for energy-matching and 16.2% for energy-matching with Legionella prevention. Taking stratification into account increased these savings by 1.2%, 5.4% and 5.5% respectively.

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