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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]

The increase in GHG emissions every year is produced by various activities, including school. School is one of the educational institutions that contribute to the implementation of sustainability practices, one of which is through the identification of carbon footprints. This paper aims to calculate the carbon footprint from school activities and CO2 emission absorb by vegetation in school open spaces. In this study, the carbon footprint was carried out from several sources according to The GHG Protocol, i.e., electricity consumption, LPG use in the school canteen, paper use, and transportation activities. Data was collected by a questionnaire survey to teachers, staff, and students. Emissions from the activities are calculated in CO2eq. The results showed that the carbon footprint produced from school activities was 83.04 tonCO2eq/year, with the largest portion of carbon footprint coming from the transportation of students, teachers, and staff, followed by electricity, paper use, and LPG. The existing vegetation in the school open space is only able to absorb carbon of 3 tonCO2eq/year from the total carbon footprint. Recommendations for reducing carbon footprint are planting more Red shoots (Syzygium oleana) on school grounds and vertical gardens with a green wall system using several types of plants. The estimated absorption by addition vegetation is 5.83 tonCO2eq/year. The total carbon footprint that can be reduced by school open space is 8.83 tonCO2eq/year. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic causes devastating impacts globally, including Surabaya. One of the significant impacts is that the increasing number of death cases, forcing every activity to comply with the health protocol for people safety. DISPENDUKCAPIL Surabaya (City Council for Civil Registration) faces the condition of increasing demand for the death certificate while the health protocol is obliged. To overcome this condition, DISPENDUKCAPIL transforms their service system from KLAMPID to KLAMPID COVID and the latest one into KLAMPID ONLINE. These transformations intend to reduce the crowd and direct human contact by shifting the activity into online activity. These transformations are proven in reducing transportation and human contact, however, increasing electricity and internet consumption. This study tries to assess the environmental impact change from each transformation. The SimaPro software calculation results for KLAMPID, KLAMPID COVID-offline submission, KLAMPID COVID-online submission, KLAMPID ONLINE-offline submission, and KLAMPID ONLINE-online submission generate 77.67 mPt, 169.31 mPt, 153.69 mPt, 61.74 mPt, and 54.53 mPt of environmental impact. It shows that there's an environmental impact jump during the KLAMPID COVID system because of the COVID-19 pandemic even though there is a reduction in transportation and paper use. [ABSTRACT FROM AUTHOR]

The conversion of sunlight to electricity using solar photovoltaic system have major drawback is to their poor efficiency and high initial cost. The solar photovoltaic system based energy can also use for Hybrid vehicle battery charging. Herein to improve solar system efficiency, this paper present intelligent FLC (Fuzzy Logic Controller) based solar MPPT (Maximum power point tracking) technique applied on solar system under variable irradiance (600-1000 w/m2) and 25°C temperature presented. For the solar MPPT, driven with boost converter and FLC improved output voltage. In this presented paper,the analysis has been done on MTALB simulink for other conventional MPPT techniques. The result shows that fuzzy logic controller based MPPT techniques gives improved result. [ABSTRACT FROM AUTHOR]

In this paper, the average daily power consumption is calculated as an example of a three-dimensional parking lot in zhengzhou. For its features, a photo-hydrogen complementary independent power supply system is designed, including PV system, controller, energy storage system and hydrogen energy system, etc. Firstly, according to the weather information of Zhengzhou City, the average daily power generation is predicted by the PVsyst software. Secondly, the capacity of the energy storage battery and the hydrogen energy system are determined through calculation. Lastly, the simulation model of photo-hydrogen complementary independent power supply system is built by Simulink. The result shows that the photo-hydrogen complementary power supply system proposed in this paper can effectively achieve energy complementation, can ensure the reliability of power supply, and can still meet the electricity demand of the three-dimensional parking lot through hydrogen energy system power generation in continuous rainy weather. [ABSTRACT FROM AUTHOR]

The operation of a university is strongly influenced by the availability of electrical energy. So that currently, electrical energy is one of the absolute and unavoidable basic needs of universities such as Hasanuddin University (Unhas). This is because at Unhas, there are modern learning and practicum facilities, both for the learning process, academic administration needs, and teaching media that generally use electrical energy-based equipment. Prior to the Covid-19 pandemic, Unhas's electricity consumption was relatively high. From 2018 to 2019, the average amount of electrical energy consumption was 14.3 GWh per year. Since entering 2020, the consumption of electrical energy has decreased to an average of 4.3 GWh. The decrease in usage is because at Unhas, there is often a policy of working from home for employees and lecturers, and studying at home for students. The decrease of 4.3 GWh was due to the absence of student activities at Unhas. So that it can be illustrated that the use of electrical energy of 4.3 GWh is an academic administrative activity. This paper aims to deliver an overview of the impact of covid 19 on the decline in electricity consumption at Unhas. [ABSTRACT FROM AUTHOR]

This paper presents an exploratory study that analysis the factors that influence the intention to use smart meters that measure electricity consumption. The authors used the technology acceptance model as a starting point for their research, taking into consideration other eight external variables: social influence, familiarity with smart meter technology, task-technology fit, compatibility, the level of trust in companies that supply electricity, price awareness, energy conservation intentions, and perception of the environmental problems. In this regard, it was developed a questionnaire that was applied to homeowners from a 5-year-old residential complex, from Bucharest, Romania, data being processed and analysed with SPSS statistical software. The results indicated that one of the most important factors that influence the intention to use smart meters is the compatibility with smart meter technology. Also, this study highlighted that price awareness and task-technology fit are also variables that strongly influence the attitude toward using a smart meter in the case of apartment owners from the residential complex. On the other hand, the intention to buy or attitude to use smart meters were not influenced by the level of trust in companies that supply electricity, and familiarity with smart meter technology, the homeowners being more concerned about energy conservation or environmental issues. Based on the results of this pilot study, at the end of the paper, the authors presented indications regarding the future research they will carry out to determine the most complete model of the factors that influence the use of smart meters in residential buildings in Romania. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to identify, analyze and develop a structural model for the identified factors that can influence the electricity distribution using Interpretive Structural Modeling (ISM) approach. From this study, the results specify that the key factors are demand fluctuations, personal protection, uninterrupted distribution, location, construction activities, consumption charges perspective, electrical subsidiary industries. The ISM framework has been developed in this paper, which is a first attempt to analyse the interrelationship among the electricity distribution impacting factors. This study will be useful for practitioners and power distribution companies (DISCOM) to understand the factors influencing electricity distribution. [ABSTRACT FROM AUTHOR]

Environmental pollution is at present a major global concern. Internal combustion engines toxic emissions are one of the primary air pollutants. To reduce the effects of fossil fuel emissions and address environmental issues, electric vehicles (EVs) are being aggressively promoted around the world. To estimate electric mobility as a good solution, almost 31% of India's population lives in cities. This number is projected to increase to 40% in 2030 and 50% in 2050. Electric-powered trains can help reduce urban air pollution, reduce emissions and improve fuel safety. In this paper, the impact of electric vehicles on grid and battery requirements in India's potential EV adoption scenario is analyzed. The government is motivating people to adopt electric vehicles. Studies suggest that high cost of electric cars, unavailability of charging infrastructure, myths related to electrical vehicles may serve as barriers to customer acceptance. On road EVs by 2030 has been called by Government of India. In this paper, the estimation has been done for number of EVs that will be sold in 2030 and the requirements of battery pack for EVs accordingly, and the electrical power required from grid for charging EVs. EV sales and other relevant details has been estimated to promote EVs. The future forecast evaluation predicted shows that by 2030, 5 to 7 percent of total electricity demand will be used to charge EVs. [ABSTRACT FROM AUTHOR]

There are the results of the electrical energy consumption research in a residential apartment building which is located in the Moscow region. Authors have given the information of the apartment electricity consumption with two people living. Research period is 2018 - 2022. Researchers have considered the main sources of electrical energy consumption in a typical apartment and in common property in this paper. It has been determinated the part of the considered apartment electrical energy consumption in the total consumption of electrical energy in an apartment building by authors of this paper. Researchers presented the information of the electric energy cost changes for the research period in the territory where were built considered building. It has been described the view and technical characteristics of the building by authors in this paper. There is the information of energy consumption in the cold, warm and transitional periods of the year. This work could be useful for companies which are in the field of managing common property, specialists from various areas of the municipal service complex, as well as developers who plan investments to residential construction in the Moscow region and other regions of the Russian Federation with similar climatic characteristics. This article is also could be used for the urban planning policy development in the field of providing electrical energy to settlements with a population less than 100 000 people. [ABSTRACT FROM AUTHOR]

The net zero emission commitment under Paris Agreement has fostered the clean energy transition agenda. ASEAN becomes the home of untapped renewable energy resources due to its geographic condition. However, the distribution of renewable energy is far from it has expected. It is not only limited extent due to the country spread, but also the high capital investment costs that caused sluggish progression. It is believed that the interconnection grid and integration energy market across region becomes a prominent key to broaden energy access and bolster the growth of Gross Domestic Product (GDP) as well. Hence, it is essential to study and analyze the scheme to foster the energy security across border through clean electricity that produced from renewable energy, particularly in ASEAN. The qualitative method through desk review approach was adopted for the paper work. There are two study objectives for this paper: (1) Renewable energy as export commodity in ASEAN which in line with ASEAN Power Grid (APG) agenda and (2) Indonesian future potential as renewable energy exporter. It is found that untapped renewable energy across ASEAN possibly meet the regional electricity demand through interconnected grid and electricity market integration. Such condition also supports the on-going APG project. Electricity trades are regulated through bilateral and multilateral agreement between countries with certain tariff. In this case, a comparison between Indonesia and Singapore about renewables export issue has been analyzed and studied. For attaining the status of renewable energy exporter in the future, it is suggested that Indonesia should deal with policy & regulation certainty (including its harmonization) and renewable energy infrastructure readiness. [ABSTRACT FROM AUTHOR]

Power to heat to power storage units, also known as Carnot batteries, are nowadays some of the most outstanding solutions for ensuring the response to the electricity demand in an energetic scenario based on non-dispatchable renewable sources like wind or photovoltaic technologies. One of the main challenges of this concept is how to store the electricity as heat in the most efficient way. In this paper the use of microwaves for converting electricity into thermal energy stored in molten salt is proposed. This paper explores the possibility of using microwaves for heating three different materials commonly considered as storage media in CSP applications: NaNO3, KNO3 and the solar salt mixture. The study focuses on permittivity measurements since this parameter allows distinguishing whether a material can be heated by microwaves or not. Further studies comparing both microwave and Joule heating methods will be presented in a future work at a later stage. The preliminary results of the feasibility of this CIEMAT's proposal are presented in this paper. [ABSTRACT FROM AUTHOR]

A study to investigate the feasibility of a hybrid or integrated energy system for UTM Ecopark facilities by HOMER Pro optimization is presented in this paper. The renewable energy investigated are solar PV, wind, pico hydro, and biogas which their sources are found to be significantly available in the eco-park. Data collection for renewable energy sources is gathered either from meteorological data (solar irradiation, wind), literature (UTM river flow rate), and interviewing UTM Ecopark's facilities users (feedstock for biogas, electricity demand). Simulation is done by optimizing the renewable energy system by minimizing the levelized cost of electricity (LCOE) that can fully supply the electricity demand, for two combinations of energy types: 1) PV, wind, hydro (PV-W-H) and 2) PV, wind, hydro, biogas (PV-W-H-B). The PV-W-H represents a zero emission energy system but at a higher LCOE (RM 0.919/kWh), while PV-W-H-B has the lowest LCOE (RM 0.52/kWh) but produces 62 kg CO2e/year. PV-W-H-B configuration's net present cost is RM 130k and PV-W-H's higher at RM 231k. [ABSTRACT FROM AUTHOR]

While it is evident that photovoltaic installations are becoming more and more widespread globally, demand for them in the Russian market remains low. Considering recent changes in the legal framework, which are beneficial for households with renewable energy, it is crucial to evaluate photovoltaic installation's economic feasibility for the Russian context, which is evaluated in this article. First, the authors created an hourly electricity consumption profile for a typical Russian multifamily house. Then a PV installation was designed and scaled to reach annual net-zero balance and net-zero balance in July for different ways of installing PV modules. After that, a monthly energy balance, considering underproduction and overproduction of electrical energy, was calculated. Finally the costs of PV electricity were calculated including purchased equipment, costs for installation as well as cost for buying electricity not covered by the PV modules and sold electricity during hours of overproduction. The economical evaluation was performed assuming a 30 year lifetime for the PV installation. It is concluded in this paper that PV installations can be profitable in the Russian market. [ABSTRACT FROM AUTHOR]

Foreseeing Electricity value utilization is the primary part of energy management, the sustenance which streamlines the inhabitants solace by subsiding the energy use. This paper proposes essence of ARIMA model which is utilized to figure the pinnacle utilization of power with different perspectives like irregularity, stable and autocorrelation of time series into thought. Autoregressive Integrated Moving Average Model (ARIMA) is a class of verifiable models for taking apart and expecting time series data. It unequivocally considers a set-up of standard plans in time series data, and as such gives a clear by and by staggering technique for making skilful time series realities. The three ARIMA models, which are very prodigious and energetic to foster a dependable model, are explored to conjecture power utilization for giving the necessary degree of execution. The built-in model is feasible to execute solid methodology and organize static forecast execution. The authentic monthly Area costs dataset from Energy power markets were considered over 12 month time period of 11years time block was taken into consideration to visualize the trend. [ABSTRACT FROM AUTHOR]

In Bangladesh, several gas turbine-based power plants often desynchronized from the national grid and remain in shutdown condition due to unstable grid frequency, lower electricity demand in the cold season, inclement weather etc. The main objective of this paper is to utilize those shutdown periods to lengthen off-line water wash cycle interval of gas turbines and to increase electricity generation. Two units of GE LM6000PC gas turbine has selected for this study. Since its initiation in 1998, the LM6000PC gas turbine has undergone a series of successful factory tests and several turbines have begun commercial operation. This paper provides an update of the LM6000PC performance and operating characteristics in Bangladesh, based upon data recorded in Max Power Limited's test facilities completed in 2018. It has found that a series of 3 hot water rinsing at 75-80 °C after every 120 hours of operation time can increase the water wash cycle interval by 33.3% of the original time. About 9% of energy has recovered that was lost due to the continuous running of a dirty compressor. The overall engine performance improved rapidly with hot water rinsing and yearly cost for water wash has reduced by 25%. [ABSTRACT FROM AUTHOR]

The metallurgical process of the copper production is a very complex process and requires the consumption of electrical energy in large quantities. One of the challenges of today is to reduce the use of electrical energy by increasing the energy efficiency of the system. This challenge can be solved by developing energy management in mining companies. In order to approach the development of energy management, it is necessary to create models for predicting the volume of copper production by investigating electricity consumption in the main production stages. In this paper, the consumption of electricity required in the process of copper production is analyzed on the example of a local mining company. Data on electricity consumption were collected for a period longer than one year and the parameters were divided according to the main phases of the metallurgical process. Two models for predicting copper production using artificial neural network were created and the most influential parameters were identified. The significance of the models is reflected in the efficient forecasting of the copper production and therefore the demand for electrical energy. Another advantage of the models is the increased possibility for rationalization of electricity consumption on the basis of the influential parameters. The models are recognized as flexible and can find their application in related companies. [ABSTRACT FROM AUTHOR]

In the late 1980s, Argentina faced frequent blackouts due to a lack of investment in generation capacity and high electricity demand growth. Argentina was one of the first developing countries to implement the liberalisation and privatisation of public utilities. In 2015, the Argentine electricity market faced a crisis due to low capacity investment. This arose from consumer prices that poorly reflected the true electricity cost, increasing risk for companies to invest in new generation capacity. Since 2016, Argentine government has called an auction to increase generation capacity; in addition, the government has cut incentive to consumers looking for reduce the electricity demand. Moreover, Argentina’s government is promoting policies to increase renewable energy share. However, it is unknown how renewable energies may affect security of supply and electricity price. This paper presents a simulation model to analyse policies for increasing generation capacity and promote renewable energy in Argentina. In this paper is concluded that renewable energies do indeed reduce the energy dependency of fossil fuels, and they lead to reduce electricity prices. [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]

This paper proposes a dual-layer coordination of energy management system (EMS) in stand-alone mode micro-grid (MG) system that considering demand response (DR) scheme in the means to reduce electricity cost at power and demand side. The main advantage of this method is that the coordination between power side and demand side can be balanced. While ensuring that operations at power side is economically controlled, the satisfaction of load demands can also be achieved. In this work, two strategies have been implemented, load shifting process based on pricing strategy as well as micro sources scheduling strategy. The performance of proposed approach has been tested based on the fixed load conditions. For the first layer EMS, the goal is set to reduce the electricity bill through load shifting process. In this EMS, five different selective modes of operation were considered during load shifting strategy implementation. In the second layer, the load profile from 20 houses has been used as the input data and aim has been paid to ensure the MG operates economically while ensuring a continuous electricity supply to the demand sides. For the economical consideration, the operation and maintenance (O&M) cost of MG also included. From the executed simulation, it has been found that from the first layer strategy, the maximum cost saving of electricity bill that able to be achieved is around 2.71%. In the second layer EMS however, the cost of O&M saving for fixed load condition is around 1.92%. [ABSTRACT FROM AUTHOR]

This paper presents electricity forecasting by integration of Nested Long Short Term Memory (NLSTM) as the another type of LSTM, Attention Mechanism (AM) as the technique for Neural Network and optimized by Cuckoo Search Optimizer (CSO) as the metaheuristic. It is important because of the electricity forecasting issue. Electricity is the crucial energy, due to the many sectors which is require it. Estimation of electricity consumption can enhance the effectiveness of generation and supply. The shortage and outage of electricity is the thing that should be avoided through the electricity forecasting. In order to create better forecasting result, the forecasting by NLSTM-AM will be combined. NLSTM-AM has several parameters which influence the network performance. Those parameters will be optimized by CSO. To discover the performance of this proposed method, the RMSE of this method will be compared by other algorithms. In this paper there are two datasets which will be used, those are Taiwan electricity consumption and Turkey electricity consumption. It is proved that NLSTM-AM-CSO has the smallest RMSE rather than other algorithms. [ABSTRACT FROM AUTHOR]

Electricity demand in Surakarta has grown by an average of 3.65% annually since 2014. On the other hand, there is also an increasing waste production in the city, producing 110,893 tons of waste in 2019. To overcome this two problems, the government of Surakarta collaborates with PT Solo Citra Metro Plasma Power to build 5 MW Waste-to-Energy (WTE) power plant in Surakarta. This paper will focus on feasibility analysis of WTE into 20 kV grid system owned by PT PLN (Persero). Load flow analysis, short circuit analysis, and total harmonic distortion analysis will be conducted using ETAP software. Simulation results showed that the smallest distribution losses occurred at Palur Substation by 87 kW. Meanwhile, short circuit current when the WTE entered the Palur Substation is 14.73 kA on the 20 kV Trafo-3 Pauwels Rail Bus and 6.12 kV on WTE Bus. Both voltage losses and short circuit current values are within the allowed limits under the ESDM regulation regarding Grid Code. THD at the connection point of GI Palur on peak load and off-peak load after the WTE is connected is still within the permissible limits (below 5%). THD analysis results are 0.31% for peak load and 0.32% for off-peak load. [ABSTRACT FROM AUTHOR]

The accuracy of electricity load demand forecasting is essential for avoiding energy waste and overuse. Hence, this paper aims to model the forecast electricity load demand by combining Empirical Mode Decomposition (EMD) with Group Method of Data Handling (GMDH) model. The proposed methodology works in three steps: it decomposes the original load data series into several Intrinsic Model Functions (IMFs) and one residual component, enables individual forecasting of each IMF and the residual using the GMDH model by using the Partial Autocorrelation Function (PACF) as the input variable, and aggregates all the forecasted values to yield the final prediction for electricity load demand. To compare the performance, another model is considered namely the combination of EMD with the Artificial Neural Network (EMD-ANN). The empirical result from the performance evaluation concluded that EMD-GMDH outperforms the EMD-ANN as well as the GMDH model without decomposing the time series. [ABSTRACT FROM AUTHOR]

The paper discusses the methodological issues of long-term projection of regional electricity consumption. We present a model for projecting electricity consumption for a 25-30-year period and provide a projection of power consumption to 2050. [ABSTRACT FROM AUTHOR]

Energy efficiency has been promoted in the last two decades in Latin America and the Caribbean (LAC) but recently it has gain ground as a mitigation strategy for climate change in order to achieve the commitments assumed in the National Determined Contributions (NDCs) of the Paris Agreement. The promotion of energy efficiency includes a wide range of policy instruments from economic incentives to regulatory and information approaches. Among the economic instruments the determination of energy prices is a central topic in energy efficiency discussion. Governments are interested in applying a price scheme to generate incentives to reduce energy consumption. In order to achieve this, first an analysis of the demand is required. In particular policy makers have to study how the demand responds to price incentives, in other words, price elasticity of energy demand is necessary to orientate energy efficiency actions. In this context, the objective of this paper is to perform a meta-analysis of the coefficient of price elasticity of electricity demand in the residential sector of LAC region and to discuss the results in terms of energy efficiency policies, taking into consideration the role of the rebound effect. This effect consists in reinvesting the financial saving from lower energy bills to access more energy services rather than to reduce energy demand. Another aim of this paper is to discuss the rebound effect in developing regions, as the economic context and the behavior of consumers may be different from developed regions. Findings show that residential electricity demand is inelastic (-0.252) in LAC region. Considering only this aspect, public policies aiming to increase energy prices, in order to improve energy efficiency, would not be effective. However, they are an adequate strategy to avoid the rebound effect. Finally, whether this effect should be avoided or incentivized depends on the definition of energy efficiency policy and on the stage of economic development of the country under study. [ABSTRACT FROM AUTHOR]

A new setup with an east-west facing horizontal single axis PV tracker array is being tested in full scale by European Energy and DTU, and compared to fixed tilt 25° south facing rows of similar PV panels. The PV panels at the tracker setup automatically follow the sun over the day. Compared to the fixed setup, the PV panels at the tracker setup have higher production in the morning and in the afternoon, where the PV panels are oriented towards east or west respectively, but less production during midday, where the PV panels are oriented horizontally. The total energy productions over the day and over the year are not very different for the two setups. However, the production profile for the tracker setup correlates better with the profile of the typical power consumption, and therefore has a higher value for the power system. The paper presents comparisons of the values of the production from comparable PV installations for the two different installation setups, based on measurements from the large-scale test installation at DTU. The values of the productions are indicated and compared based on the Nordpool Power Spot Market prices on an hourly basis. [ABSTRACT FROM AUTHOR]

In this paper we aimed to determine chaotic behavior of electricity consumption in the USA for the period from 1973:1 to 2018:3. For this purpose, nonlinear structure of the model was determined by BDS test. And then, Lyapunov Exponents was employed to specify chaotic behavior of electricity consumption in the USA. [ABSTRACT FROM AUTHOR]

The paper presents selected elements of logic synthesis of low power FSM. Authors focus on the problem of low power coding for internal states. Proposed coding algorithm leads to reduction of the number of switches and as a result reduction of dynamic power consumption. The paper shows, that effective coding algorithm is insufficient for effective FSM synthesis. A vital role in logic synthesis plays technology mapping. This process requires appropriate function decomposition. The paper presents methods of carrying out technology mapping which uses triangle tables. This method leads to appropriate decomposition path. The experimental results show that effective states coding must be associated with effective technology mapping. [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]

Malaysia is among the highest consumers in terms of energy consumption and intensity per capita in Asia. In 2020, per capita energy consumption in Malaysia will be 2.7 toe. Where it turns out to be higher than the neighboring country. Per capita electricity consumption has increased from 3 900 kWh per capita in 2010 to 4 600 kWh in 2020. The objective of this paper is to study the energy scenario in Malaysia, especially after going through the Covid 19 pandemic phase which has crippled almost the entire economic sector of the country and see how the potential for renewable energyin Malaysia after going through the pandemic phase. Where Malaysia is focusing on sustainable and prudent energy use and efficient resource management under the 11th Malaysia Plan (2016–2020) through introduction of the National Energy Efficiency Action Plan (NEEAP) (2016–2025). NEEAP provide instruments for the successful implementation ofenergy efficiency strategies in country through well-coordinated and cost-effective energy implementation efficiency measures in the industrial, commercial and residential sectors. Realize need to improve energy efficiency and conservationinitiatives, Malaysia is developing a comprehensive new Energy Efficiency and Conservation Act (EECA) in an effort to reach its country aspirations, as well as the effective use of energy across key sectors. EECA will outline the comprehensive measures necessary to promote the efficient use of energy, including goal setting, communication, and education. It will also initiate measures to reduce greenhouse gas emissions as a regulatory approach. [ABSTRACT FROM AUTHOR]

Saudi Arabia is one of the highest levels per capita in CO2 emissions and electricity uses in the world. At the same time, Saudi Arabia is one of the largest oil producers and exporters. It is also one of the largest oil consumers in the world. Based on the users' behavior, the policymakers in Saudi Arabia must initiate significant policy changes in electric power consumption. This paper presents the data from different sources and analyses the data to correlate user behavior regarding recent changes in some energy policies. For example, in 2016, the electricity prices increased by 40% for some more significant consumers, mainly the commercial sector. In 2018, there was another increase by more than 150% on average for all customers, including the residential sector, based on different categories. The study found that the average annual increase in electricity consumption (GWh) before 2016 was 6.19%, and the average growth of annual increase was 0.51% after 2016. Further analysis was carried out to understand the strength and weaknesses of recent policy changes and their impact on users' behaviors and consumption in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Solid Oxide Fuel Cells (SOFCs) have the tremendous potential to be the future solution of our energy demands. This paper attempts to model a three dimensional, single, high temperature solid oxide fuel cell operating at 800°C. The model has been prepared using the butler Volmer equations for charge transfer kinetics. For the flow of the gases in the porous gas electrodes, Brinkman Equations have been used, which are combination of Darcy's Law and the Navier Stokes Equations. We have analysed the electrical properties of SOFC developed in the model. From the simulation we have plotted the polarization curve of SOFC, which is in good agreement with the experimental data. The power characteristics representing the output power variation with the current density of the SOFC is also studied and optimum current density is defined. Additionally, the polarization characteristics representing the variation of the average current density of the SOFC with SOFC voltage is also studied. [ABSTRACT FROM AUTHOR]

These days, much effort is being put into lowering the consumption of electric energy and involving renewable energy sources. Many engineers and designers are trying to develop environment-friendly technologies worldwide. It is related to incorporating appropriate devices into such technologies. The object of this paper is to investigate these devices in connection with refrigeration systems. Ejectors can be considered such as these devices. The primary interest of this paper is to investigate the suitability of a numerical model for an ejector, which is incorporated into a refrigeration system. In the present paper, there have been investigated seven different test runs of working of the ejector with a working fluid R-1234ze(E). Some of the investigated cases seem to have a good agreement and there are no significant discrepancies between them, however, there are also cases that do not correspond to the experimental data at all. The ejector has been investigated in both on-design and off-design working modes. A comparison between the experimental and numerical data (CFD) performed by Ansys Fluent software is presented and discussed for both an ideal and a real gas model. In addition, an enhanced analytical model has been introduced for all runs of the ejector. [ABSTRACT FROM AUTHOR]

This paper presents optimization of electricity bill using single-phase modified Impedance Source Inverter (ISI) with dual input sources for residential appliances. The proposed converter has dual DC input ports (Solar and Battery), connected with ISI. The main advantages of the dual input system, if any one of the input fails, the second input is connected and vice versa. Compared to the existing voltage source converters, the ISI has more advantageous by providing the continuous flow of inductor current, better power factor and single stage power conversion, which intern reduces the number of components and overall cost of the system. An optimized case study has discussed based on single bedroom in Bangalore city. In this, the smart hybrid controller device, which is used, for swapping the dual input based on the weather conditions, energy consumed by the load. This work uses renewable energy sources as one of the input due to its effectiveness of energy in a small group like home, parks, and offices. Energy consumption calculation based on appliances, PV design calculation, boost control method and switching schemes those are analyzed and the optimization based load demand are discussed. Finally, the performance analysis of the load and the efficiency are discussed in this study. [ABSTRACT FROM AUTHOR]

Mine water entering catchment areas of underground kimberlite mines contains a significant amount of solid particles of various sizes, which explains frequent siltation of these mine workings, as well as intense hydroabrasive wear of operating pumping equipment, in particular impellers with sealing rings and hydraulic heel assembly. As you know, in the event of siltation, water collectors lose their initial storage capacity, and mechanical wear of the pumps is accelerated due to clogging of mesh filters of their receiving devices, as a result of which an emergency situation can arise up to partial flooding of the mining object. Thus, it can be seen that the reservoirs necessarily need to be periodically cleaned from settled mud-sludge slurry. The cleaning frequency of catchment areas of underground kimberlite mines in the Russian Federation is relatively small. Practice shows that in the conditions of underground kimberlite mines in the Russian Federation, the pumping equipment of water-drainage stations has too excessive pressure, which leads to unproductive financial costs of electricity consumption. This paper describes and scientifically substantiates a technical solution aimed at increasing the efficiency of drainage units of underground kimberlite mines in the Russian Federation, whose pumping equipment has excess pressure, through its utilization to combat mechanical impurities. [ABSTRACT FROM AUTHOR]

A PV (Photovoltaic) system is considered an eco-friendly source of energy and widely used for the generation of electricity. In this paper, to obtain the maximum yield from PV systems different conventional algorithm techniques are being used. The main objective is to provide background knowledge, implementation topology of PV system including a brief understanding of all the methods to tackle output power of such systems based on the MPPT (maximum power point tracking) technique. After comparative study (based on parameters like monitoring and convergence time, algorithm and sophistication of hardware, capacity to maintain partial shading, etc. of various methods, findings suggested DC-P&O (direct controlling perturb and observe) with ARM microcontroller gives better results for MPPT. Furthermore, this paper is intended to give insight into different intelligent algorithm techniques to choose a constraint-free methodology. [ABSTRACT FROM AUTHOR]

This paper investigated a Genetic Algorithm for parallel batch processing machine to reduce the tardiness and consumption of power charges. In manufacturing industries, a multiple type of jobs are manufacturer in a batch processor machine at a time. For every year, the large amount of the energy is used in manufacturing industry and recently the consumption of electricity charges has been increased. The main aim is to reduce the makespan, minimize the power charges and a production efficiency measurement for the purpose of the environment. In this paper, a mixed integer programming model is formulated. The problem has been solved effectively using the Genetic Algorithm. The performance measure has been analyzed for comparing the various types of the algorithms. [ABSTRACT FROM AUTHOR]

This paper uses intraday electricity demand data from Mahakam-East Kalimantan city as the basis of an empirical comparison of univariate methods for prediction up to a day-ahead. A notable feature of the time series is the presence of both an intraday and an intraweek seasonal cycle. The forecasting methods considered in the study include: Double seasonal ARIMA modeling of the daily demand profiles. The Double seasonal ARIMA methods performed well, the method that consistently performed the best was the double seasonal. [ABSTRACT FROM AUTHOR]

This paper presents the (preliminary) results of the project "Stronger Decentralization of the German Electricity-Heat-System" which was funded by the German federel state Rhineland-Palatinate. First, different strengths and weaknesses of decentralized systems are assessed and compared to centralized systems in general. For this assessment, it is distinguished between different dimensions of the power system that all could be either central or decentral: generation, flexibility, optimization and stakeholders. In the next step the electricity grid of Rhineland-Palatinate is simulated for the years 2030, 2040 and 2050 under the assumption of 95% CO2 reduction until 2050. The simulation model comprises the grid from the 110 kV level upwards. Loads, generation and flexibilities have been distributed according a detailed analysis of demographic factors, such as inhabitants, vehicles and households per region. In each case, different scenarios of a whole year are simulated in 1 hour steps. The scenarios differ in optimization goals, such as minimizing electricity costs or maximizing local consumption of electricity. Finally, for each scenario, certain KPIs, such as cost of electricity, own consumption, necesary grid extension, etc. are determined and compared to each other. This facilitates a holistic comparison of the advantages and disadvantages of decentralized and centralized systems. [ABSTRACT FROM AUTHOR]

This paper deals with actively studied terms "flexibility" and "resiliency" of electric power systems (EPS). Definitions and content of these new fundamental EPS properties are analysed. Objective trends in development of EPS with regard to these properties are discussed. Possible measures for improving flexibility and resiliency of EPS are suggested. [ABSTRACT FROM AUTHOR]

This paper offers the creation of a low-speed, three-phase knock-down radial generator with poles in the form of permanent magnets. Making this generator answers the challenges of developing water extraction devices at the micro- scale with the availability of generators for small-scale plants that can work at very low turns. The resulting generator is the result of preliminary research, which will be further developed to produce generators ready to be fabricated. Laboratory experimental results show that this generator has a very significant performance with an AC voltage for no-load of 4.5 V to 65 V, while with a load of 4.5 V to 33 V. The power generated by the generator at 100 rpm turns the output power to around 3W, while at 320 rpm, the output power can reach 25 W. The results of making this three-phase knock down radial generator in the future will be developed for household electricity use in remote areas, which can be assembled and repaired by themselves. [ABSTRACT FROM AUTHOR]

With the cost of solar electricity generated by photovoltaic (PV) systems dropping, the integration of PV into concentrating solar power (CSP) plants is under active consideration. PV systems are more economical in providing electricity directly to the grid during sunshine hours, whereas the main advantage of CSP plants is the availability of economical large thermal storage (TES), especially when molten salt is used as heat transfer and storage fluid. Several options to combine the strengths of the two technologies are evaluated in this paper, including: a small PV plant designed to supply the CSP plant's own consumption; hybrid CSP-PV plants where the CSP plant is mainly used to charge the storage while the PV system delivers electricity to the grid during the daytime and optionally charges the storage by means of electrical heaters ("eTES"); and finally a PV only system that provides electricity during daytime and additionally charges the thermal storage by electrical heaters. The different hybrid operation strategies are evaluated for a typical plant located in Southern Spain with mediocre direct solar irradiation. A sensitivity study on the impact of a high DNI CSP location like South Africa and an advantageous feed-in tariff at night on the plant's economics is presented. [ABSTRACT FROM AUTHOR]

The energy crisis triggered globally in the last quarter of 2021, forced Romania to go through a winter with liberalized electricity and gas prices, a period unprecedented in terms of consumer prices, accentuated by the result of closing energy targets that coalfired operations as a result of the imposition of EU conditions for the restructuring of the mining and energy sector. The year before, 2020, the COVID-19 pandemic, with restrictions imposed, produced a decrease in electricity demand, a decline in coal-fired power consumption, greatly reduced the share of gas in the energy mix, using preferential renewable energy sources. Subsequently, Russian gas prices have risen to record highs and, as a result, coal-fired power generation has returned to the European Union in 2021, although coal became more expensive and emission allowance prices doubled. In the context of the armed conflict between Russia and Ukraine, major price increases are expected worldwide, generating new risks of exposing the economy and new challenges in terms of ensuring Romania's independence and energy security. Against this background of these situations, can Romania still respect the European commitments of the Green Pact, meet these challenges and respond to the needs of the communities affected by the projected programs? The present paper aims at a critical assessment of the current situation of the Romanian coal mining and future trends of using a "clean coal" as a variant to respond to the requirements of the environmental concerns. [ABSTRACT FROM AUTHOR]