KONSERVASI ENERGI LISTRIK PADA BANGUNAN GEDUNG KANTOR BUPATI TOJO UNA-UNA

Electrical energy has a very important role in the economic, industrial and social development of the community, this causes an increase in the demand for electrical energy in line with the increase in people's welfare, economic and industrial growth. On the other side, energy sources that are commonly used for power generation are increasingly expensive and limited in availability and cause environmental pollution. Based on these considerations, it is necessary to implement an energy management program to preserve energy resources and use energy effectively. Energy consumption intensity (ECI) is a term used to determine the amount of electrical energy consumption in a room. The calculation of the intensity of energy consumption carried out at the Tojo Una-una regent's office in Central Sulawesi consists of 3 buildings with 129 rooms, it was found that 7 rooms were categorized as quite efficient and wasteful.

THE APPLICATION OF IOT SOLUTIONS IN GREENHOUSES WITH THE AIM OF REDUCING ELECTRICAL ENERGY CONSUMPTION

In this paper, we will show a prototype of a system designed based on Internet of Things solutions with the aim of optimizing electrical energy consumption in order to achieve desired conditions for the growth and development of plants located in the greenhouse. The physical parameters that this system monitors are temperature, relative humidity, soil humidity and luminescence levels. In this prototype, we have three measurement nodes with the task of collecting parameter data, processing them and sending resulting data, via wireless communication, to a receiver. The receiver forwards data to the application on PC. The application processes the data and displays it to the end user who can choose to automatically or manually control the devices that are inside of the greenhouse. Systems placed inside the greenhouse are heating, irrigation, lighting and ventilation systems.

Development of an Electrical Energy Consumption Model for Malaysian Households, Based on Techno-Socioeconomic Determinant Factors

Energy-saving strategies are required to address the increasing global CO2 and electrical energy consumption problems. Therefore, the determinant factors of electrical energy consumption consist of socio-demographic changes, occupant behavior, house and appliance characteristics, or so-called techno-socioeconomic factors, which all need to be assessed. Statistics models, such as the artificial neural network (ANN), can investigate the relationship among those factors. However, the previous ANN model only used limited factors and was conducted in the developed countries of subtropical regions with different determinant factors than those in the developing countries of tropical regions. Furthermore, the previous studies did not investigate the various impacts of techno-socioeconomic factors concerning the performance of the ANN model in estimating monthly electrical energy consumption. The current study develops a model with a more-in depth architecture by examining the effect of additional factors such as socio-demographics, house characteristics, occupant behavior, and appliance characteristics that have not been investigated concerning the model performance. Thus, a questionnaire survey was conducted from November 2017 to January 2018 with 214 university students. The best combination factors in explaining the monthly electrical energy consumption were developed from occupant behavior, with 81% of the variance and a mean absolute percentage error (MAPE) of 20.6%, which can be classified as a reasonably accurate model. The current study’s findings could be used as additional information for occupants or for companies who want to install photovoltaic or wind energy systems.

Bio-algae: a study of an interactive facade for commercial buildings in populated cities

Climate change, global energy demand, and greenhouse emissions from energy (formerly CO2 emissions from fuel combustion) have emerged as the most serious threats to humans, particularly in densely populated cities. As a result, there are calls to reconnect with nature and draw inspiration from its mechanisms as well as to use clean renewable energy resources. Thus, this paper presents a biomimicry approach—a strategy for achieving ecological balance—to biofuel using algae in a building facade, and considers a case study building in Giza city as an example of a populated city in Egypt for retrofitting its skin with a nature-inspired solution. Using mathematical calculation, energy load analysis, and interviews with interested specialists, architects, and building occupants about this technology, then compared the performance of the case study commercial building facade with the proposed algae facade for energy generate. The results indicate that electrical energy consumption can be reduced by 45 to 50%, and carbon emissions could be reduced. In addition, other benefits for the building environment and societal acceptance were revealed. The study concluded that using algae as an element of the building skin in densely populated cities as a biomimicry architecture strategy contributes to an innovative environmental approach.

Advanced Controlled Road Lighting System Concurrent with Users

The operation of a concurrent lighting system using LED luminaires is based on the detection of individual road users, the recognition of their lighting needs and adjusting the operating state of the individual lighting devices that make up the system to the expectations of each user. The luminaire’s lighting divided into three independently controlled parts allows reducing electrical energy consumption up to 33% in comparison to a conventional concurrent road lighting system.

Innovative exoskeleton mechanics

The authors have developed an integrated approach and technology for building an exoskeleton that minimizes human energy expenditures while walking. Optimized torque characteristics from an exoskeleton worn on one knee have reduced metabolic and electrical energy consumption. Studies have shown practical value and significance for application, namely, the lift increase of the exoskeleton and possibilities opening in medicine, for rescuers, tourists. Comparative analysis showed the way to solve the problems of mechanics when creating an exoskeleton to improve the quality of performing complex tasks.

Degradation of paraquat herbicide using hybrid AOP process: statistical optimization, kinetic study, and estimation of electrical energy consumption

Background This work studied the performance of UV/PS/TiO2NPs and UV/PI/TiO2NPs as hybrid advanced oxidation processes for degradation of paraquat in aqueous solution, because this very toxic herbicide is used third most widely. Results The effects of several factors such as UV irradiation, initial oxidant concentration, TiO2 nanoparticles dosage, and pH on the degradation efficiency were investigated. The process optimization was performed by the central composite design as a tool of response surface methodology for 30 mgL−1 of the herbicide initial concentration at 25 ℃ and 40 min of degradation process. Based on the results, a degradation efficiency of 77% and 90% were obtained for the UV/PS/TiO2NPs and UV/PI/TiO2NPs processes, respectively, in the optimum conditions. The mineralization efficiency of the paraquat solution using UV/PS/TiO2NPs and UV/PI/TiO2NPs processes are about 32% and 55%, respectively, after 40 min. The kinetic studies show that both processes follow a pseudo-first-order kinetic model, and the kinetic constants are 0.0299 min−1 for the PS process and 0.0604 min−1 for the PI process. The electrical energy consumption was estimated to be about 481.60 kWhm−3 for the PS process and 238.41 kWhm−3 for the PI process. Conclusions The degradation and mineralization efficiency of the paraquat solution using the UV/PI/TiO2NPs process was more than that of the UV/PS/TiO2NPs process at the optimum conditions after 40 min.