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the issue of rising electricity demand in the building sector is one of the major challenges. Therefore, the Building Management System (BMS) inside the building. Since the PV, national grid, and diesel generators supplies building electrical power, so the Energy Management System (EMS) technologies are necessary to study the priority of PV to supply building power to save energy. This paper proposes a Smart Building Management System (SBMS) used with Heating, Ventilation, and Air Conditioning (HVAC) in addition lighting systems. HVAC is controlled with occupancy sensors, temperature control, and load control. Lighting systems are controlled through occupancy sensors and daylight sensors to make them operate to minimize electricity consumption. Using Artificial Neural Network (ANN) control of the EMS in this work, SBMS and EMS are created and simulated using two case studies to supply public buildings. The first situation is SBMS without EMS and the second situation is SBMS with EMS. Finally, the results showed the impact of SBMS on the reduction of energy consumption for HVAC systems and lighting (20% on summer day and 11% on winter day), as the energy consumption was reduced for both HVAC and lighting by about (54% on a summer day and 44% on a winter day) because we added the scenario of case two to the one scenario case in a public building. [ABSTRACT FROM AUTHOR]

In line with the Malaysian government's efforts to increase renewable energy in energy generation to 30 percent by the year 2030, ambitious efforts are being made to promote the implementation of utility-scale solar PV plants with ample policy backing. The goal of the current study is to use PVsyst software to evaluate the economic and environmental assessment of On Ground PV (OPV) system. This paper serves as a pioneering study on the design, simulation, economic evaluation, and environmental assessment of a 300-kW grid-connected Photovoltaic (PV) system installed on the ground at Xiamen University Malaysia. The effectiveness of the proposed design is evaluated from 1st January 2022 to 31st December 2022 using the PVsyst software version 7.2, which works on accurate plant specifications. The simulation is performed using PVsyst 7.2 software to design the whole system properly. Four main systems were considered for this stare i) Assessment of geographical location and meteorological data, ii) Development of orientation analytics and optimal PV layout, iii) development of PV model which includes detailed losses calculation and shading analytics, iv) Development of technical performance, economic evaluation, and environmental assessment. The proposed PV design is expected to provide 100 % of the A5 building's lightning electricity energy consumption while reducing CO2 emissions by 3648.904 tonnes throughout the lifespan of the system's deployment. The article also documents significant emission reduction and cost analysis calculations for the proposed design. were evaluated for their monthly energy production, losses, greenhouse gasses (GHG) savings, and economic sustainability throughout the year 2022. [ABSTRACT FROM AUTHOR]

Cleaning robots have been used for many years to help clean places from households to roads. These autonomous machines play a significant role in ensuring public health and safety, by removing accumulated litter and filth. Clean roads are just as important as clean houses, for this, machines called "Street Sweepers" were developed. While earlier street sweepers were purely mechanical, modern street sweepers use electricity and can be manual, semi-autonomous or fully autonomous. There are often sharp objects on the road that occasionally puncture the tires of vehicles and sometimes, even a person's foot. This paper focuses on the design and testing a small robot to remove sharp ferromagnetic objects from the road. The robot will be equipped with an electromagnet to pick up the ferromagnetic objects, and a camera and an object detection algorithm to detect the objects. The robot would move on top of the detected object, then lower and activate the electromagnet to collect the debris and then drop it into a container. The collected materials will be discarded at a special post. A solar panel will be used to recharge its battery so as to keep it environment friendly. Several test trails conducted on the electromagnetic dropping mechanism showed potential for deployment in real-world scenarios. This contributes to the effectiveness and reliability of the whole system especially working of the metal collection mechanism controlled by the pulleys. [ABSTRACT FROM AUTHOR]

Abstract-As we all know that most of the electricity generated by fossil fuels. In view of increasing the demand of electricity in domestic, industrial, agriculture and commercial purposes. We are looking for alternate source, which is solar power generating by PV cells. Solar power generation depends on the availability of solar radiation and temperature throughout the day. MPPT method is used to generate more power and this technique is environmentally friendly. Various methods are there to control MPPT, which are AI, FLC, NN, Constant V/I and PO (Perturb and observe) methods. This paper explains modeling, simulation of MPPT algorithm for PV array using boost converter. At the end results obtained in MATLAB using Simulink. [ABSTRACT FROM AUTHOR]

Lowering Covid-19 cases globally and nationally provides a positive indication of economic growth, especially in Batam City, Indonesia. This condition is also followed by increased electrical energy consumption, particularly in residential houses. This paper presents an electrical energy audit process of a residential house using the IKE (Energy Consumption Intensity) parameter. The audit was conducted in a home with a building area of 226 m2 and an electrical capacity of 4400 VA. The result shows that the total electricity consumption of such a house is 1,266.34 kWh per month, to which the air-conditioning system contributed the most prominent electricity consumption of the whole facilities in the house. Providentially, the score of IKE is less than 8.5, which means such a residential house is categorized as very efficient energy consumption. Furthermore, the self-evaluating checklist technique has carried out to find the main factor that affects the electricity consumption of the air-conditioning system. Regarding the highest rating score on the self-evaluating checklist of air conditioning systems, the ceiling has a score of 77.5%. This result means that the ceiling needs to be evaluated to reduce the heat load of the house, which in turn reduces the electrical energy consumption of the air conditioning system. Finally, this work can use as an initial audit framework for assessing electrical energy consumption in residential houses in Indonesia. [ABSTRACT FROM AUTHOR]

Poverty is a common problem around the world. At the end of 2019, the emergence of the covid-19 virus exacerbated the situation of the poor. So various efforts are made to deal with this. This paper proposes a Multidimensional scaling method to identify characteristics that affect poverty in each Regency/city in West Sumatra. The main advantage of this method is a two-dimensional perceptual map that facilitates the presentation of research results. Multidimensional scaling analysis is a multiple-variable technique that involves creating a map to describe the position of an object with other objects based on similarity values. The analysis involved regencies/cities in West Sumatra with poverty characteristic variables. To determine the validity of the research results, testing using Rstudio obtained a stress value of 6.4% and an R2 value of 0.996. The results obtained is Padang Kota, Pariaman Kota, Dhamasraya, Padang Panjang Kota, and Sawahlunto have proximity to the poverty characteristics based on the type of residential floor made of soil (X2), do not have defecation facilities/ together with other households (X4), source of household lighting does not use electricity (X5), have a residential floor area of less than 8 m2 (X1), and do not have defecation facilities / together with other households (X4). It is hoped that the results of this study will be able to assist in handling poverty in every Regency/city in the province of West Sumatra. [ABSTRACT FROM AUTHOR]

A hybrid system for generating and distributing electricity for a multi-speed autonomous underwater vehicle is considered. Due to the wide range of electricity consumption, the task of controlling the parameters of the power grid arises. The complexity of the task lies in the constant change in the composition of consumers and the current they consume. Due to the novelty of the development of a multi-speed apparatus and the use of a hybrid system for the generation and distribution of electricity, the problem was not considered earlier in this formulation. To solve the problem of connecting consumers to power sources, it was presented in the form of a weighted directed graph, and the problem of connecting consumers to conductors was formalized as finding the shortest path in the graph. The paper proposes algorithms for controlling the connection / disconnection of consumers from the elements of the electrical network and the dynamic switching of consumers between current conductors, depending on the speed mode of the apparatus, based on the use of an algorithm based on Dijkstra's algorithm. The results of numerical experiments made it possible to estimate the energy consumption in the most unstable, most energy-intensive parts of the trajectory. This made it possible, in turn, to test the developed power grid control algorithms and make sure that the algorithmic decisions made were correct. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy worldwide, it has become imperative to explore and adopt sustainable energy practices. In this regard, predicting household electricity consumption accurately is essential, as it can help optimize energy usage and reduce waste. This paper focuses on using Long Short-Term Memory (LSTM) shows the neural networks to prevent household electricity consumption in India. The LSTM model was implemented using the Keras library in Python. The model was trained using the training set and tested using the testing set. The study demonstrated that LSTM neural networks are a promising approach to predicting household electricity consumption in India. Further research can be conducted to recover the accuracy of the perfect by including more variables such as household size, income, and appliance usage. [ABSTRACT FROM AUTHOR]

The unmatched construction increase happened in last decade and the domestic construction from late 80s can be labelled as inefficient energy units. Building sector consumes energy more than 54 % and residential sector around 24 % in north region. The rising cost of per unit energy is huge concern especially the cooling loads. The inefficient houses are raising the peak demand becomes a challenge to meet the demand versus generation. This issue must be addressed at micro level. The major energy loss happened through windows (being the crucial component of building services) and more heat inside the building than other components such as wall, roof etc. This paper investigates the possible reasons and gaps that why residential sector is not susceptible towards sustainable windows to lower their electricity bills. The research carried in two phases and questionnaire is framed to gather the data for analysis with aid of experts and literature reviews. It is concluded that awareness of occupant plays a pivotal role in advancement of sustainable windows besides other crucial factors such as orientation, make, glazing type etc. The collective efforts of architect, engineer, vendors and occupant can bridge the gap to reduce energy consumption. The initial cost of sustainable windows can be offset with savings and aid of government policies. [ABSTRACT FROM AUTHOR]

This paper presents the design and development of a reliable tracking and recording system to monitor energy that has been consumed by electrical appliances. The electrical energy resources management is a major concern worldwide especially toward the waste of electricity. The current electrical energy monitoring system can only be viewed when attached to the device and it is more difficult to track all devices at one time. The energy production is depending on the energy management activities to minimize the environmental impacts. Therefore, we introduce the Electrical Energy Consumption Monitoring System over IoT, targeted to measure electrical energy for home appliances such as air conditioners, water heaters, fans, lighting and others. The monitoring system consists of an electrical current sensor and a Raspberry pi IV microcontroller as the main core. The system will measure energy based on the rate of current flowing through the cables of electrical equipment and subsequently the energy consumption can be calculated. The measured values can be accessed directly via computer or smartphone. These reading values are stored in a database for future reference and comparison. On the server, Node-Red, influxDB and Grafana were installed. The use of IoT technology allows the rate of electricity consumption to be monitored anywhere quickly and accurately even at a distance. [ABSTRACT FROM AUTHOR]

The use of solar photovoltaic panel for generating power to contribute the power demand is presented in this paper. The system is installed at the rooftop of Islamic Senior High School Daarul Echsan Muhammadiyah Sragen (Madrasah Aliyah Muhammadiyah DIMSA). The purpose of this project is beside to contribute the power demand of the school, is also to be the learning tool for the students to understand how the power may be generated using the extensively available resources for free. The power so far used in the school is from the government electric utility company. The installed capacity is 23 kVA three-phase system. The photovoltaic panels placed on the roof is 8 x 545 Wp. The output of the panels is connected to 15 kW inverter and the output of the inverter is synchronized with the electricity grid. The produced energy is expected to contribute the electricity demand of the school. A number of measurements have been carried out relating the input parameter and the output voltage of the panels. This relation is essential for detail planning of development and operation of the generating system. The developed system is expected to sustainably operate for years therefore becoming a role model of fulfillment of energy demand in such way that is economical and environmentally friendly. [ABSTRACT FROM AUTHOR]