Minimum Set Point Research Articles

Toward Sustainable Farming: Implementing Artificial Intelligence to Predict Optimum Water and Energy Requirements for Sensor-Based Micro Irrigation Systems Powered by Solar PV

Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order to achieve sustainable farming in arid regions, there is an urgent need to use artificial intelligence (AI) to predict and estimate the optimum water and energy requirements for the irrigation of date palms. Therefore, this study aimed to predict the optimum water and energy requirements for date palm irrigation depending on the optimum water use efficiency (WUE) and yield in arid conditions. To achieve this aim, four solar-powered micro irrigation systems were developed and evaluated under six irrigation levels for date palm irrigation. Soil moisture sensor-based controllers were used to automate irrigation scheduling for the micro irrigation systems. The water pumping in these systems was powered using a solar photovoltaic (PV) system. In addition, four machine-learning (ML) algorithms, including linear regression (LR), support vector regression (SVR), long short-term memory (LSTM) neural network, and extreme gradient boosting (XGBoost), were developed and validated for prediction purposes. These models were developed in Python programing language using the Keras library. The results indicated that the optimum WUS was achieved when the maximum setpoints of irrigation control were adjusted at the field capacity and by adjusting the minimum setpoints at 40, 50, 70, and 80% of the available water (AW). The optimum yield was achieved by adjusting the minimum setpoints at 60, 70, 80, and 90% of AW for subsurface irrigation, subsurface drip irrigation, drip irrigation, and bubbler irrigation, respectively. Therefore, the dataset was prepared at these levels for four years to train and test the models, and a fifth year was used to validate the performance of the best model. The evaluation of the models showed that the LSTM followed by XGBoost models were more accurate than the SVR and LR models for predicting the optimum irrigation water and energy requirements. The validation result showed that the LSTM was able to predict the water and energy requirements for all irrigation systems with R2 ranging from 0.90 to 0.92 based on limited meteorological variables and date palm age. The findings of the current study demonstrated that the developed LSTM model can be a powerful tool in irrigation water and energy management as a fast and easy-to-use approach.

Analysing the Economic Viability of Implicit Demand Response Control of Thermal Energy Storage in Hot Water Tanks

Demand-responsive control of electrically heated hot water storage tanks (HWSTs) is one solution, already present in the building stock, to stabilise volatile energy networks and markets. This has been put into sharp focus with the current energy crisis in Europe due to reduced access to natural gas. Furthermore, increasing proportions of intermittent renewable energy will likely add to this volatility. However, the adoption of demand response (DR) by consumers is highly dependent on the economic benefit. This study assesses the economic potential of DR of centralised HWSTs through both an analysis of spot price data and an optimisation algorithm approximating DR control. The methods are applied to a case study apartment building in Norway using current pricing models and examine the effect of the demand profile, electricity prices, heating power and storage capacity on energy cost and energy flexibility. Unit cost savings from DR are closely linked to the variation in unit energy price during the optimisation period. Increasing the storage capacity or the heating power increases the flexibility with a diminishing rate of return. However, increasing storage capacity does not result in cost savings as additional heat losses are greater than the saving from shifting demand, except for during highly volatile electricity price periods. Changing the minimum setpoint temperature improves the cost curve as a greater thermal storage capacity can be achieved without increasing heat loss. Systems utilising a smaller heating power are more economical due to the dominant role of the monthly price related to the peak energy demand of the system.

Una alternativa para la producción de superficies de doble curvatura en láminas de fibrocemento a través de mecanizado de tres ejes

El presente trabajo describe el proceso y resultados del mecanizado de un material compuesto de matriz de cemento reforzado con Sílice y fibras naturales, comercialmente conocido como fibrocemento. El mecanizado se realizó en una lámina comercial de 10 mm de espesor, a partir de una superficie de doble curvatura en un centro de mecanizado ROLAND - MDX 40A, por medio de un proceso de desbaste y posterior acabado en 3 ejes, con el uso de herramientas de corte comerciales de carburo de tungsteno. Para la obtención de la geometría, se utilizó Rhinoceros 5 con el complemento Grasshopper para la parametrización del modelo y RhinoCAM para la generación de los códigos G que permitieron ejecutar los procesos de mecanizado. La geometría parametrizada en la lámina partió de un módulo de un paraboloide Hiperbólico, el cual tomaba sus dimensiones, según las medidas de la placa en su largo, ancho y profundidad y el número de veces que el usuario deseaba replicar en un patrón rectangular este módulo. El proceso de mecanizado se realizó sin refrigeración y con herramientas de corte estándar, por lo que la velocidad de avance, profundidad de corte y avance de la herramienta se ajustaron a parámetros mínimos que permitieron conservar la vida útil de la herramienta y el cuidado del equipo durante los procesos de mecanizado y así obtener un acabado superficial aceptable, esto tuvo como consecuencia, un tiempo lento los procesos, los cuales podrían ser optimizados utilizando sistemas de refrigeración o herramientas especializadas en el mecanizado de materiales cerámicos. La técnica de manufactura empleada en este material y desarrollada en este trabajo, puede ser aplicada en la fabricación de piezas con volúmenes bajos de producción o elementos especializados, en sectores tales como la Ingeniería y manufactura, el sector Eléctrico, la industria de la construcción y arquitectura, el arte y diseño y la fabricación de Mobiliario.

Analysis of thermostat control in dutch dwellings

In the previous Chapter we made a sensitivity analysis based on actual energy consumption and heating behavior, on the whole OTB sample using methods like Markov chain and Monte Carlo analysis. In this Chapter (Chapter 5) a deeper analysis of heating behavioral patterns is reported. The study included 61 houses randomly chosen from the Netherlands, monitored for 2 months during March and April 2011. The thermostat use patterns of households were studied as well as chosen maximum and minimum set points each day for the whole sample. Then these patterns were correlated with the household and dwelling characteristics of the sample. Unfortunately, the collected energy consumption data for this sample was not reliable to be included in the analysis. This Chapter deals with the Research Question III-1 of this thesis: (Chapter 1, Section 3, pg. 16-17) “ III. What are the behavioral patterns and profiles of energy consumption? The sub-question is: What are the behavioral patterns of thermostat control? How do they relate to the household characteristics, revealing behavioral profiles?” The research reported in this Chapter was conducted by Bedir, borrowing the dataset of Sonja van Dam. The data was collected through monitoring, by and for Sonja van Dam for her PhD research, using ENECO’s means of data collection. The analysis in this Chapter was done, and the paper was written by Bedir. The co-author has given permission to include this research in this thesis. This chapter is being prepared to be published as a scientific journal article. It was formerly published as a conference paper: Bedir, M. Van Dam, S. (2013) Analysis of Thermostat Control Behavior in Dwellings: Evidence from monitoring in the Netherlands. Plea 2013, Proceedings of 29th Conference of Sustainable Architecture for a Renewable Future, Germany (CD)

Analysis of thermostat control in dutch dwellings: occupants’ behavioral profiles

In the previous Chapter we made a sensitivity analysis based on actual energy consumption and heating behavior, on the whole OTB sample using methods like Markov chain and Monte Carlo analysis. In this Chapter (Chapter 5) a deeper analysis of heating behavioral patterns is reported. The study included 61 houses randomly chosen from the Netherlands, monitored for 2 months during March and April 2011. The thermostat use patterns of households were studied as well as chosen maximum and minimum set points each day for the whole sample. Then these patterns were correlated with the household and dwelling characteristics of the sample. Unfortunately, the collected energy consumption data for this sample was not reliable to be included in the analysis. This Chapter deals with the Research Question III-1 of this thesis: (Chapter 1, Section 3, pg. 16-17) “ III. What are the behavioral patterns and profiles of energy consumption? The sub-question is: What are the behavioral patterns of thermostat control? How do they relate to the household characteristics, revealing behavioral profiles?” The research reported in this Chapter was conducted by Bedir, borrowing the dataset of Sonja van Dam. The data was collected through monitoring, by and for Sonja van Dam for her PhD research, using ENECO’s means of data collection. The analysis in this Chapter was done, and the paper was written by Bedir. The co-author has given permission to include this research in this thesis. This chapter is being prepared to be published as a scientific journal article. It was formerly published as a conference paper: Bedir, M. Van Dam, S. (2013) Analysis of Thermostat Control Behavior in Dwellings: Evidence from monitoring in the Netherlands. Plea 2013, Proceedings of 29th Conference of Sustainable Architecture for a Renewable Future, Germany (CD)

Air diffusion performance index (ADPI) of overhead-air-distribution at low cooling loads

The air diffusion performance index (ADPI) concept and its implementation in the diffuser selection guideline (ASHRAE Handbook-Fundamentals, 2009) provide designers a simple method to design overhead-air-distribution systems. However, the current guideline considers only five diffuser types and the range of sensible cooling loads used to develop the guideline (65W/m2–250W/m2) is high for current buildings. Applying this outdated guideline may cause draft discomfort and/or unnecessary fan-energy waste. This paper presents new experimental results to update the ADPI-based guideline to include 15 diffuser types at low cooling loads of 25W/m2 and 50W/m2. Compared to the high loads in the current guideline, the ADPI values generated in this work are greater due to the lower loads used. Most ceiling-mounted diffusers produce higher ADPI at a large range of airflow than do sidewall and other diffuser types. ADPI for ceiling diffusers has the least variation with changes in loads or airflow rates. The results show that the minimum airflow set-point for a variable air volume system varies with diffuser type. For ceiling diffusers other than round and perforated diffusers, the minimum set-point can be reduced to lower than 30% of the peak flow rate without significantly reducing ADPI.

Adaptive Hopping Probe Ion Conductance Microscopy of Live Cells at ∼5-10 NM Resolution

The inherent low imaging speed of hopping probe ion conductance microscopy (HPICM) poses a constraint for the study of living cells at super resolution. The duration of each imaging frame further increases when the cell topography requires large approach/retraction movements of the scanning pipette. We have modified our HPICM system to increase its imaging speed and sensitivity.We replaced the Z-scanner with a ∼18 kHz resonant frequency piezo assembly to allow for faster pipette movements. An external proportional-integral-derivative controller was used to decrease the delay in the Z-scanner. In our modified HPICM algorithm the approach speed adapts to the changes in the ionic current flowing through the pipette. Altogether, our changes to the HPICM system allowed for approach speeds up to 4X faster with delays of only ∼50μs. Our “adaptive” approach curve effectively reduced the noise floor by half, which improved the vertical resolution of the system to ∼5nm. We also introduced adaptive filtering of the ionic current, which decreased by half the minimum setpoint, thus improving the system's sensitivity.To test the performance of the improved HPICM setup, we imaged the vertically protruding stereocilia (∼0.5-3μm in height, ∼100-400nm in diameter) of the rat inner ear sensory cells. When we previously imaged these structures with HPICM, we used glutaraldehyde-fixed cells and each imaging frame took >44 min (Novak et al. Nat Methods, 2009). Now, the entire stereocilia bundle (∼9x9μm) in a live cell is imaged in ∼15 min and sub-regions of interest (∼2x2μm) in ∼3-6 min, with ∼10-30nm XY resolution, even with the hop amplitudes of 3-5μm.Our improved HPICM system allows for the faster imaging of live cells at nanometer resolution, even in the cells with very convoluted topographies.Supported by NIDCD/NIH (R01DC008861, R01DC014658).

Demand-controlled ventilation for multiple-zone HVAC systems—Part 2: CO2-based dynamic reset with zone primary airflow minimum set-point reset (RP-1547)

In Part 1 of this article, a CO2-based dynamic reset was proposed and evaluated as an energy-saving demand-controlled ventilation strategy by reducing the outdoor airflow rate when the occupancy is under design occupancy. Further energy-saving potential still exists when the zone primary airflow rate is modulated or reset instead of only resetting the outdoor airflow. Two new control strategies are presented: a CO2-based dynamic reset, now combined with a zone primary airflow set-point reset in Part 2. The system level of these control strategies is the same as CO2-based dynamic reset in Part 1. The additional control features are added at the zone level. The zone primary airflow rate minimum set-point will first be reset to increase system ventilation efficiency, which will lead to a reduced system outdoor airflow rate. With this proposed dynamic reset with zone primary airflow set-point reset, the design minimum zone primary airflow rate can be designed lower than the regular set-point used in variable air volume terminal box minimum set-points. This new setting reduces the energy consumption for the system supply fan as well as energy consumption for terminal reheating. Both energy simulation and airflow simulation were conducted in different locations of a building. In this article, the results show that the proposed strategies of CO2-based dynamic reset with zone primary airflow set-point reset consume less energy when compared to CO2-based dynamic reset presented in Part 1 and the baseline case “without demand-controlled ventilation.” The average annual system outdoor airflow rates for the two options of the proposed demand-controlled ventilation are 44.1% and 45%, respectively, less than the outdoor airflow rate for the case without demand-controlled ventilation. Therefore, the proposed demand-controlled ventilation control strategies are suggested to consider for CO2-based demand-controlled ventilation for multiple-zone single duct VAV systems with terminal reheat.

Devising the law of automatic compensation for a failed engine in a going around plane

The paper presents a numerical simulation of an automatic go-around of an aircraft with a failed engine. When an engine fails, it reveals additional resistance force as well as entails unbalanced forces and moments at a roll and a yaw rotation. To quantify an automatic go-around of an aircraft with a failed engine, the value of the steady climb full gradient should not be lower than its minimum set point. Thus, for a four-engine airplane the minimum set value of the full steady climb makes up 2.7 %. An automatic go-around of an aircraft with a failed engine (with no regard to the failure compensation) is characterized by a decreased full gradient of the steady climb and the current gradient as well as a “sluggish” acceleration of the aircraft speed and climb. The synthesis of the law of automatic compensation for a failed engine is based on the principle of direct measurement of disturbances and their application in a loop control of the rudder. The measured disturbances typical of an engine failure include deviation of the set rotor speed of low-pressure fans for the left and right engines as well as a lateral acceleration in the direction of the failed engine. The devised law of automatic compensation for a failed engine in the rudder channel allows to increase the supply of a complete steady gradient of an aircraft climb by 2.0-3.0 % and improve the dynamics of velocity acceleration and the aircraft climb.

Demand controlled ventilation for multiple zone HVAC systems: CO2-based dynamic reset (RP 1547)

Demand controlled ventilation (DCV) is used to reduce the system outdoor airflow (OA) when the occupancy of the system is under design occupancy. However, the new versions of ASHRAE Standard 62.1-2010 make DCV more difficult to implement for multiple zone HVAC systems. This article proposes a CO2-based and occupancy-sensor-based dynamic reset of OA rate for multiple zone HVAC systems (“CO2-based DR”). This control strategy uses bioeffluent load estimation with a steady-state assumption to calculate and dynamically reset the system OA rate minimum set-point by solving the multiple-zone system equations for current conditions. Building energy and airflow simulations were implemented to assess the energy performance and indoor air quality of this control strategy. The simulation results showed that the average annual system OA rate for CO2-based DR is 14.6% less than the OA rate for without DCV, in which case the system OA is always maintained as constant. The annual monetary saving as a percentage of the baseline case (without DCV) is between 0.3% and 11.0% for 16 climate zones in the United States.

Analyses of Transpiration and Growth of Paprika (Capsicum annuum L.) as Affected by Moisture Content of Growing Medium in Rockwool Culture

Since the moisture content (MC) of growing medium closely related with the crop transpiration, the MC should be included to the environmental factors to be considered for irrigation control in soilless culture. The objective of this study was to analyze the transpiration of paprika plants using daily mean solar radiation (RAD) and vapor pressure deficit (VPD) as well as the growth of the plants at different MCs of rockwool growing media. The starting points of irrigation were controlled by a moisture sensor with minimum set points of 40%, 50%, and 60% of MCs. The canopy transpirations were measured for 80 to 120 days after transplanting and analyzed. The transpirations were well regressed with a combination of both RAD and VPD rather than daily mean RAD only under the controlled MCs. The transpiration at 60% MC was higher than those at 50% and 40% MCs. Leaf area, leaf fresh and dry weights at 60% MC were higher than those at 50% and 40% MCs while the number of leaves had no significant difference among the MCs. There were no significant differences in number of fruits and fruit size among all the MCs, while fruit weight was significantly lower at 40% MC than other treatments. Fresh and dry fruit yields were the highest at 60% MC. Therefore it was concluded that the transpiration was affected by the MC of rockwool growing medium and the minimum set point of 50-60% MC of rockwool growing medium gave better effects on the growth of the paprika plants.

図形と言葉で制御方法を表現した拡張ファジィ環境制御の基礎的検討

An extended fuzzy control software was designed to perform environmental control to save developing cost and debugging labor. In the software, the control know-how was represented as graphs with some phrases, named CIC operators (CIC: Correlation between Intention grade and Control setpoints). The graphs represented correlation between intention grade of environmental control and each greenhouse environmental condition. The phrases represented explanations of the control aim using the graphs and control messages for changing the environmental conditions. A score of control achievement was denoted by a minimum intention grade using the graphs in the time of environmental conditions. Then, the software tried to control the environment condition giving the minimum intention grade. The goal of software is to get the perfect score of control achievement.The control software was applied to simulation test for a greenhouse heating control. The results showed that the software could control the greenhouse inside air temperature using the three CIC operators to satisfy average setpoint, changing rate setpoint and minimum setpoint. Showing the phrase of the CIC operator and the present value of the greenhouse environment condition having the minimum intention grade could help the software developers and growers with understanding the software operation. The results suggested the possibility of a new high performance environmental controller.