Operation and Preliminary Energy Balance of a Portable Kelp Dryer in Maine

Seaweed (macroalgae) is a marine resource that has a high economic value. Seaweeds are important commodities as raw material for food or additives and as a source of biomass. One popular species of seaweed is Sugar kelp (Saccharina latissima) – a brown algae that is native to the Maine coast and also a commonly farmed species. It is a rich source of fibers, vitamins, minerals, and antioxidants. Seaweeds are highly perishable due to their high moisture content and will spoil quickly if not preserved, therefore a common practice is to dry the product to prolong storage life and to minimize the cost for transportation. A drying method using warm (not hot) air will extend seaweed shelf life and also retain many of the valuable bioactive components that are heat and/or UV sensitive. Thus, a controlled drying environment can best retain product and nutritional value and prevent degradation of the food quality. A first of a kind drying system with controlled temperature, air flow and exit humidity has been developed and assembled in the advanced manufacturing center (AMC) at the University of Maine. The drying system is built within a 40-foot-long shipping container. vi Inside the container, the seaweed is suspended from an oval shaped overhead conveyor system, where it slowly rotates around the length of the chamber. A utility room at one end of the container houses two parallel propane powered heaters with integral blowers, an exhaust fan and a control system. My project is looking at examining the drying time, the temperature and humidity within the drying process, the drying rate, and energy efficiency of the process. Several experiments were run during early and late springtime 2020 using wet towels or fresh Sugar kelp in the dryer. The drying system is equipped with five temperature and humidity sensors which logged data every 0.5 seconds. Examination of the drying runs shows that as air passes through the drying chamber it decreases in temperature and gains humidity, as expected. It became apparent that partial recycling of the air was important for achieving high exit humidity and lower energy cost. In early runs, the data showed that air was short circuiting through the dryer and circumventing the hanging material being dried. This flaw was partly resolved by adding some sheeting at the top of the conveyor and partially blocking two ventilation ports. We also noted that the temperature measurement of the incoming air was being affected by the level of recycle and furnace activity. It can also be seen that through the duration of the drying work, the exiting air shows a steady trend of rising temperature and decreasing RH. Analysis of the energy dynamics for the system shows that more data are needed to consistently close the energy balance, particularly with respect to metering the propane used, determining the temperatures of different surfaces of the dryer, the rate of air flow into and out of the system, as well as weather conditions, insolation rate and orientation to the sun. Estimated values for these variables suggest that insulating the walls of the container, except on bright sunny days, will likely be cost effective

Perancangan Prototipe Sistem Kendali Otomatis Pada Pengering Pakaian Berbasis Air Heater

Pengering pakaian diharapkan dapat bekerja secara otomatis dan dapat menjaga kualitas pakaian yang dikeringkan. Terdapat parameter penting pada proses pengeringan pakaian yaitu temperatur dan kelembaban. Untuk menjaga kualitas pakaian, perlu diperhatikan nilai temperatur pengeringan agar tidak melebihi batas temperatur pengeringan yang ditentukan pada setiap jenis pakaian. Oleh karena itu, diperlukan pengaturan setpoint temperatur pengeringan pakaian pada alat pengering pakaian. Pada penelitian ini dirancang prototipe pengendali yang dapat bekerja secara otomatis pada sebuah sistem pengering berbasis air heater. Prototipe yang dirancang terdiri atas air heater, sensor temperatur, sensor kelembaban, Arduino, dan tampilan antarmuka menggunakan LabVIEW. Proses pengeringan dioperasikan oleh pengguna melalui antarmuka dimana pengguna memasukan dua input yaitu jenis pakaian yang akan dikeringkan dan jumlahnya. Input tersebut digunakan pada penentuan nilai temperatur operasi pada air heater. Selama proses pengeringan, nilai temperatur maupun nilai kelembaban pada bilik pengering diukur menggunakan sensor tipe DHT22. Kedua nilai lalu tersebut ditampilkan melalui antarmuka LabVIEW. Nilai temperatur tersebut dibandingkan dengan nilai temperatur setpoint yang ditentukan berdasarkan jenis dan jumlah pakaian yang akan dikeringkan. Berdasarkan nilai perbandingan tersebut, LabVIEW mengirimkan nilai kendali berupa nilai PWM secara serial ke Arduino, yang merupakan sinyal kendali ke air heater. Kemudian, air heater bekerja menjaga temperatur pada bilik pengeringan agar sesuai setpoint selama proses pengeringan berjalan atau kondisi timer on. Jika nilai kelembaban telah mencapai kriteria kondisi kering dan waktu pengeringan telah habis, maka air heater akan masuk pada mode off. Berdasarkan hasil pengujian, prototipe sistem kendali yang dirancang mampu bekerja secara otomatis dan hasil pengeringan dapat mempertahankan kualitas pakaian. Selain itu penghematan energi listrik juga dimungkinkan dengan penggunaan pengendali otomatis pada pengering pakaian tersebut.The clothes dryer is expected to work automatically and can maintain the quality of the clothes. Temperature and humidity are the two main parameters in the process of drying clothes. The drying temperature affects the clothes conditions because each type of clothing has a certain temperature limit to maintain its quality. Therefore, it is necessary to set the temperature setpoint for drying clothes operation. This study designed a controller prototype that can work automatically in an air heater-based clothes dryer. The designed prototype consists of an air heater, temperature sensor, humidity sensor, Arduino, and an interface using LabVIEW. The drying process is operated by the user through an interface where the user inputs the type of clothing and the amount of clothing to be dried. The input is used to determine the temperature setpoint on the air heater. During the drying process, the temperature and humidity values in the drying chamber are read by the DHT22 sensor and then displayed on the interface. This temperature value is compared with the setpoint temperature which is determined based on the type and amount of clothes to be dried. Based on the comparison value, LabVIEW sends control values in the form of PWM values serially to Arduino, which are control signals to the air heater. Then, the air heater works to maintain the temperature in the drying chamber to match the setpoint during the drying process or when the timer is on. The air heater will turn off when the humidity has reached dry conditions and the drying time has been over. Based on the testing results, the control system prototype is able to work automatically, and the drying process can maintain the quality of the clothes. In addition, saving electrical energy is also possible with the use of the automatic controller

Review of Heat Pump Tumble Clothes Dryer Energy Efficiency and Related Technologies

As energy constraints and consumption in the world increase, it is important to investigate all areas of technology for improvement. In the residential building sector, clothes drying is a significant consumer of energy accounting for 6% of residential electricity in the U.S. (EPA, 2011). Heat pump technology has become increasingly popular for residential tumble clothes dryers. This paper presents a detailed review of heat pump tumble dryer research covering technologies for air conditioning waste heat recovery, recuperative heat exchangers, system modeling, and control optimization. Additional technologies related more broadly to vapor compression cycle enhancement are also reviewed, including alternative working fluids, variable-capacity systems, and component technologies. Future areas for research are identified to enable the next generation of heat pump dryer energy efficiency

Experimental Evaluation and Thermodynamic System Modeling of Thermoelectric Heat Pump Clothes Dryer

Electric clothes dryers in the US consume about 6% of residential electricity consumption. Available electric clothes dryers today are either based on electric resistance (low-cost but energy-inefficient) or vapor compression (energy-efficient but high-cost). Thermoelectric dryers have the potential to alleviate the disadvantages of both through a low-cost, energy-efficient solution. This paper presents experimental results and steady state simulation of a prototype thermoelectric dryer. A thermoelectric model is coupled with a psychrometric dryer system model to design the experimental prototype. The results from the prototype are used to calibrate the model and identify important parameters that affect performance, such as relative humidity of air leaving the drum.

Modeling and optimization of heating and drying processes in a clothes dryer

Many of the techniques have been proposed to improve the dryer efficiency. The drying process has not been analyzed thoroughly. The experimental results of 32 runs of a Frigidaire clothes dryer are presented. The dryer is fully instrumented to measure the instantaneous air temperatures, the instantaneous surface temperatures, the instantaneous power, and inlet, and outlet flow rates. The effect of many of the dryer parameters such as heater power, fan speed, drum speed, weight of clothes and initial moisture content were experimented, documented, and analyzed. The results were discussed and many new proposed techniques to improve the dryer performance were recommended.;Electric heaters are used in many industrial applications. There are many interacting parameters that affect the heater performance and contribute to its cost. Such parameters are coil length, coil diameter, the helix diameter, the number of turns, the coil emissivity, the heater wall emissivity, the applied voltage, the air flow rate, the air temperature at the heater outlet, and the heater dimensions. The heater coil was divided into four segments and the heater wall was divided into five sections. Energy and heat transfer equations were written for each segment of the coil, each section of the wall, and the air past each coil segment. Equations relating the configuration factors from the coil segments to the wall sections, to the heater dimensions were derived. EES was used to solve the system of two hundred non-linear equations. The effect of varying the heater parameters on the heater performance were studied and discussed. The objective function is constructed for the annual cost of an appliance electric heater using an estimate for the energy usage and the manufacturing cost. A detailed model for the electric heater is utilized to minimize the objective function relative to nine design variables, subject to thirteen inequality constraints. Experimental results are used to correlate the mass flux to the dryer input parameters. The correlation is used to determine the running cost. The objective function of the annual running cost plus the cost of the heater is optimized using different methods. The optimization results are presented and discussed

Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression

Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech processing. We provide an overview of natural gas forecasting. Next, the deep learning method, contrastive divergence is explained. We compare our proposed deep neural network method to a linear regression model and a traditional artificial neural network on 62 operating areas, each of which has at least 10 years of data. The proposed deep network outperforms traditional artificial neural networks by 9.83% weighted mean absolute percent error (WMAPE)

Modelica Analysis of Thermally Connected Residential Appliances

With the United States being the world’s second largest consumer of primary energy, research into areas of significant consumption can provide large impacts in terms of the global energy consumption. Buildings account for 41% of U.S. total energy consumption with the residential sector making up a majority. Household appliances account for the second largest site energy consumption at 27%, after the HVAC system for the U.S. residential sector. Thermally integrating residential appliances by leveraging waste heat recovery goes outside U.S. federal standards and has not been adequately explored by connecting all residential appliances. Limited studies exist focused only on single appliances connected to waste heat recovery or being thermally integrated. Modelica appliance models have been developed for four household appliances: refrigerator-freezer (RF), dishwasher (DW), clothes dryer (CD), and clothes washer (CW). The Modelica models capture individual use and the predictions of the RF and DW were compared against available experimental data. The individual models have been connected to a simple storage tank model to simulate the integrated appliance system. Modelica predicts the energy savings under the integrated system and captures any impact from integration

Solar Power

A wide variety of detail regarding genuine and proprietary research from distinguished authors is presented, ranging from new means of evaluation of the local solar irradiance to the manufacturing technology of photovoltaic cells. Also included is the topic of biotechnology based on solar energy and electricity generation onboard space vehicles in an optimised manner with possible transfer to the Earth. The graphical material supports the presentation, transforming the reading into a pleasant and instructive labor for any interested specialist or student