Showing papers in "EAI Endorsed Transactions on Energy Web in 2022"

Task Scheduling Techniques for Energy Efficiency in the Cloud

Abstract: Energy efficiency is a key goal in cloud datacentre since it saves money and complies with green computing standards. When energy efficiency is taken into account, task scheduling becomes much more complicated and crucial. Execution overhead and scalability are major concerns in current research on energy-efficient task scheduling. Machine learning has been widely utilized to solve the problem of energy-efficient task scheduling, however, it is usually used to anticipate resource usage rather than selecting the schedule. The bulk of machine learning approaches are used to anticipate resource consumption, and heuristic or metaheuristic algorithms utilize these predictions to choose which computer resource should be assigned to a certain activity. As per the knowledge and research, none of the algorithms have independently used machine learning to make an energy-efficient scheduling decision. Heuristic or meta-heuristic approaches, as well as approximation algorithms, are frequently used to solve NP-complete problems. In this paper, we discuss various studies that have been used to solve the problem of task scheduling which belongs to a class of NP-hard. We have proposed a model to achieve the objective of reduced energy consumption and CO2 emission in a cloud environment. In the future, the model shall be implemented in MATLAB and would be assessed on various parameters like makespan, execution time, resource utilization, QoS, Energy utilization, etc.

Towards Multi-Model Big Data Road Traffic Forecast at Different Time Aggregations and Forecast Horizons

Abstract: Due to its usefulness in various social contexts, from Intelligent Transportation Systems (ITSs) to the reduction of urban pollution, road traffic prediction represents an active research area in the scientific community, with strong potential impact on citizens’ well-being. Already considered a non-trivial problem, in many real applications an additional level of complexity is given by the large amount of data requiring Big Data domain technologies. In this paper, we present the first steps of a novel approach integrating both classic and machine learning models in the Spark-based big data architecture of the H2020 CLASS project, and we perform preliminary tests to see how usually little-considered variables (different data aggregation levels, time horizons and traffic density levels) influence the error of the different models.

Linking Sustainable Mobility Criteria to Policymaking: Results of Multi-Criteria Analysis

Abstract: With increasing emissions from the transport sector, the need to reduce emissions is becoming increasingly acute. The EC's Climate Law aims to re-duce emissions by 55% by 2030, while the growing transport sector is the slowest to meet these targets. Only a few European Union (EU) countries met the 2020 renewable energy source target in the transport sector, which indicates that major changes are needed to meet the new EU requirements. As each country has limited financial resources, it is necessary to assess the impact of the policy before its implementation. In this study, a survey of 19 industry experts was conducted to identify the most promising policy in-struments for reducing emissions in the road transport sector, as well as to identify the most promising fuels for which more resources should be devoted. In this publication, data analysis was performed by the combined Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology. The obtained data can be further used for in-depth analysis such as cost-benefit analysis or complex system dynamics analysis for later use in sustainable policy formulation.

Improved Spectral Efficiency and Connectivity in RSMA based 5G V2X Systems

Abstract: Vehicle to everything (V2X) faces several challenges including high data rate, low latency and stable connectivity requirements. Due to increased number of connected vehicles, Interference too appears to be a serious issue in V2X systems. Consequently, careful selection of multiple access techniques can lead to improved interference mitigation together with higher spectral efficiency and data rate. Vehicle mobility with growing traffic density is a demanding task that affects probability of vehicle connectivity, thereby resulting into requirement of sustained vehicle linkage for ongoing traffic safety. In this regard, our paper employs Rate Splitting Multiple Access (RSMA) technique, which considers change of both channel strength and direction for improved interference mitigation leading towards enhanced spectral efficiency. RSMA is optimized for weighted sum rate, further; it is integrated with mobility management to demonstrate sustained connectivity in the presence of increased traffic density. Presented results have been found promising, both in terms of spectral efficiency and stable connectivity. RSMA 5G V2X outperformed at higher Signal to noise ratio (SNR) values and on average achieved 25% better spectral efficiency compared to Non Orthogonal Multiple Access (NOMA) technique.

Thermodynamic Simulation of Producer Gas Combustion from Biomass Gasification

Abstract: The use of new and renewable energy for the application on gas burners is beneficial for the environment. This study aims to determine the effect of excess air during the combustion of producer gas from biomass gasification to release heat used as a fuel gas burner. Simulations are carried out by applying mass and energy balance, showing that an increase in excess air will decrease the non-adiabatic and adiabatic flame temperature. The result showed that an increase in excess of air reduces the amount of heat released to the environment for the same flame temperature. The maximum adiabatic flame temperature is at 1725.430C, while the non-adiabatic ranges from 600 to 8000C. Furthermore, heat is released in the range of 20.1 kW to 28.8 kW, and excess air from 0 to 40%.

Sensors and Simulations for Transport Resilience

Abstract: With the aim of enhancing resilience, the need for method of its measurement arises. To apply the method, resilience indicators must be identified and collected. In this paper we deal with questions of acquisition of indicators, needed to assess resilience of the transport system of the city. More specifically, we will look at the sensors and simulation and their possibilities in this task. That is why the first part of the paper will start with introduction of the Laboratory of Simulation and Modelling of Crisis Phenomena in Transport, and of the simulation program VR®Forces, that we plan to use for application of this paper´s outcomes and for further research of resilience. In second part of this article, we will briefly guide the reader through our view on resilience with focus on transport system of the city. Next, we will move to identification of transport resilience indicators, that could be obtained by the use of sensors within the traffic network and its vehicles or devices, and also indicators, that we can obtain by the use of simulation. Identification of sensors, usable for this task will follow. Finally, the possible use of modelling and simulation in collection of resilience indicators will be explained.

Design and control of STATCOM fed Distributed Generation using Fuzzy Controller based Reverse voltage Technique

Abstract: Power quality enhancement is one of the major concerns from the last few years due to fluctuations occurring in the power transmission and distribution. This paper presents the design of distributed generation system for reducing power quality problems in the distribution system and grid side supply. It involves the design of distributed generation using renewable energy source and also reverse voltage technique based multilevel inverter for integration into the grid. This paper also presents the design of fuzzy controller based modified synchronous rotating frame theory for regulating the DC link voltage and multilevel inverter currents. The system was simulated using MATLAB Simulink and the results are verified with single phase and three phase non linear loads.

Minimizing the Frequency Deviations in the Interconnected Microgrids considering Renewable Energy Sources

Abstract: Nowadays, the use of Microgrids is increasing due to their ample applications and advantages. Microgrids have much smaller financial commitments, and they use renewable resources; hence are more environmentally friendly with lower carbon footprints. Also, microgrids require fewer technical skills to operate, rely more on automation, and are isolated from grid disturbance or outage. Traditionally, microgrids have been employed in remote locations that cannot be connected to the central power grid and serve critical infrastructure. Due to the recent advancements in technology, microgrids have become more accessible and economically feasible. Microgrids can be employed in organizations that intend to lower their energy cost. The paper explains a detailed literature review and the contributions of the authors in Interconnected Microgrids. Also, the data taken from the survey was used in the transfer function blocks in simulation. The simulation of the interconnected microgrids comprising Thermal, solar, and wind turbine systems is formulated on MATLAB. The frequency error and ACE are reduced to zero in a quick time by using a fuzzy PID controller. Also, the paper aims at achieving one of the most important United Nations Sustainability Development Goals (UNSDGs), Affordable and Clean Energy (UNSDG- 7).

Sustainable Smart Parking Solution in a Campus Environment

Abstract: INTRODUCTION: With the continuous growth of cities and its demography, the number of vehicles has also increased in the cities which contributes to a greater difficulty in finding parking spaces. The time it takes for a citizen to find a free space in a car park can be tiring and contributes negatively to the level of air pollution. Smart Parking solutions intend to address this issue by proposing systems that, in many cases, include sensors and/or cameras with the purpose of facilitating the search for available parking spots.OBJECTIVES: In this paper, a crowdsourcing-based approach that makes use of a mobile app for facilitating the search for a parking space in the Instituto Politécnico de Viana do Castelo is presented.METHODS: The solutions intend to lower the time to park and, therefore, the amount of CO2 produced by vehicles of the academic community. Some gamification techniques were used to motivate users to be engaged with the mobile app.RESULTS: A survey was used to evaluate the solution and the app usability. It showed that the use of the app can contribute to reduce the time spent to find a parking space in approximately 50.75%, and consequently reducing the CO2 by the same amount, and it was also verified that the users enjoyed using the mobile app.CONCLUSION: The developed solution shows the efficient use of mobile applications, crowdsourcing and gamification approaches and their role to contribute to a more sustainable mobility.

A Hybrid Framework for Visual Positioning: Combining Convolutional Neural Networks with Ontologies

Abstract: Visual positioning is a new generation positioning technique which has been developed rapidly during recent years for many applications such as robotics, self-driving vehicles and positioning for visually impaired people due to advent of powerful image processing methods, especially Convolutional Neural Networks. Nowadays, deep Convolutional Neural Networks are capable of classifying images with high accuracy rates; however, comparing visual perception by a human being, pure Neural Networks lack background knowledge which is essential for estimating the position through a reasoning process. In this paper we present a hybrid framework for employing ontologies over Convolutional Neural Networks to integrate a knowledge-based reasoning with Neural Networks for taking advantages of capabilities similar to human brain’s functions. The proposed framework is generic so it can be applied to a wide variety of scenarios in smart cities where visual positioning represents added value.

Performance Optimization of Solar PV System Utilized for Cooling System

Abstract: This work investigates the performance and energy effectiveness of a solar photovoltaic (PV) system used to provide a cooling system for a building in Iraq. To achieve the goal, simulations and optimization are utilized to find the economic feasibility of the building in Iraq. In addition, a comparative study is conducted to compare the economic feasibility of PV cooling based on two options. The first option depends on the conventional electrical grid to offer cooling for the Iraqi building. The second option relies on a solar PV system to provide the electrical power for cooling the same building. The major numerical analysis results revealed that using a PV system can save roughly 45% electrical power compared to the option when the electrical power is drawn from the conventional grid. For this reason, it is predicted that the PV system can save a higher level of greenhouse gas (GHG) emissions compared to the first option. The results of this research revealed that the cooling load of the building in Samawah, Iraq equalled 600 kW. The PV system required to operate the cooling of the Samawah building during summer equals 18 kW peak. Using a solar PV system would be more economically feasible than the electrical power drawn from the electrical grid. Utilizing PV cooling is considered beneficial for the environmentas it can save GHG emissions that cause significant air quality problems and global warming.

Design of a low-cost wireless emission monitoring system for solid-fuel heat sources

Abstract: INTRODUCTION: The study presents a conceptual and detailed design methodology overview of a wireless sensor network (WSN) aimed to evaluate the SmartCity air quality in real-time. The aim of the article is to provide low-cost, reliable, and accurate emission data at remote locations, assisting the 2050 Climate-Neutral target set by the European Commission. The sensor devices shall monitor emission parameters such as ozone, carbon dioxide concentration and particle concentrations, specifically concentrations PM2,5 and PM10.OBJECTIVES: The overall objective of the article is to demonstrate the use of a modern home-made air quality device within the market of boilers, fireplaces or other heating devices.METHODS: The methodology consists of reverse engineering of used professional portable emission analyzers, determining the detailed parts, building a model of how the device's internal systems operate. The paper later explains a series of future experiments including the setup, the necessary components and specific aim. Two numerical models shall be constructed in MATLAB Simscape and Simulink, specifically a telecommunication model, assisting the design of the telecommunication module, and thermal numerical model, that aids in verifying the system temperature and cooling.RESULTS: The study presents a large potential in increasing the accuracy and spectrum of modern air quality data and decreasing emission levels.CONCLUSION: In the conclusion of the paper, the functional requirements of the data processing are stated, along with schematic illustration of the user interface of measured emissions.

Adaptive FPA Algorithm based OPF with Unified Power Flow Controller

Abstract: In this work a novel modified flower pollination algorithm has been developed to solve the problem of single and multi-objective Optimal Power Flow operations for Unified power Flow Controller in Flexible Alternating Current Transmission Systems. In the proposed Adaptive Flower Pollination Algorithm the best initial solution can be chosen from the fittest and also the weights are adaptively adjusted to get better convergence characteristics. The nature of the objective functions is non-linear and difficult to get best possible solutions within the boundary conditions of total power demand. The weak nodes are determined in the system to locate the UPFC with Fuzzy approach considering input parameters as L-Index and voltage magnitudes. The projected method is validated using IEEE-30 and IEEE-57 bus systems for three objective functions, namely, system real power loss minimization, fuel cost minimization and the combination of total generating cost and system real power loss. Results of Fuzzy- Adaptive Flower Pollination Algorithm based OPF optimization for UPFC produced optimum results for the considered objectives of total fuel cost, real power loss and for the multiobjective.

An Analysis of Research Trends and Knowledge Structure in the Field of Affordable and Clean Energy

Abstract: INTRODUCTION: Energy is the foundation of all human endeavors and is intertwined with human progress. The access to sustainable energy services is a fundamental requirement for sustainable development, encompassing poverty eradication, food security, health, well-being, and education quality. Affordable and clean energy is explicitly recognized as one of the 17 sustainable development goals. OBJECTIVE: to analyse research trends and the knowledge structure in the field of affordable and clean energy. METHODS: This study was based on a descriptive bibliometric analysis of SDGs 7 "Affordable and Clean Energy". The Scopus database was used as a source of information, between 2012 and 2021. RESULTS: The trend of documents on Affordable and Clean Energy reveals a steady increase in the number of published papers related to this topic, indicating a growing interest and activity in researching and disseminating information about sustainable energy. It is observed that international collaboration accounts for 21.8% of the analyzed documents, indicating a significant involvement of researchers from different countries. Engineering emerges as the leading subject area with 591,146 scholarly outputs, indicating a strong focus on technological advancements and innovation. CONCLUSIONS: Scientific production in the field of affordable and clean energy has experienced steady growth, reflecting an increasing interest in research and development of sustainable energy solutions. However, it is important to recognize that this increase in the number of published papers has not translated into greater impact and recognition in the scientific community. Although more knowledge is being generated, its influence seems to be diminishing. Countries that participate in joint research obtain a higher number of citations, indicating the importance of establishing international linkages to maximize the visibility and impact of research.

Smart Technology Based Empirical Mode Decomposition (EMD) Approach for Autonomous Transmission Line Fault Detection Protection

Abstract: Many novel technologies of property energy and cell, solar power, batteries, and high-efficient combustion are widely investigated to conserve energy and reduce emissions. Transmission lines (TLs) play a serious role in transmitting generated electricity to different distribution units in facility engineering. The transmission lines function as a link between shoppers and a Power Station. Faults usually occur within the transmission when positioned in an open field. Quick identification and sick line faults square measures required for the conventional operation of the plant. A way like distinct moving ridge rework (DWT) and (EMD) is used to locate and identify faults to resolve this disruption. DWT is used to break down fault transients, as a result of which the info can be collected at the same time in each time and frequency domain. EMD decomposes the TLs voltage into Intrinsic Mode operation (IMFs). Four varieties of fault signals are square measurements produced by the grid-connected facility. Line faults square measure induced MATLAB/Simulink mistreatment.

Power Quality Improvement using Parallel Connected FACTS Device with Simplified d-q Control

Abstract: INTRODUCTION: Distribution network is mainly affected by the end user load nature. Ruinous influence on power system operation based on the type of load used by the end user and due to the presence of non-linear loads causes Harmonics in power system. The concept of reducing the harmful effect of harmonics on power system attracted the research attentiveness. OBJECTIVES: To reduce these harmonics and reactive power problems FACTS devices are found reliable. Out of various FACTS devices, Active Power Filter (APF) is one FACTS device which identifies and controls the harmonic contamination in power system with non-linear loads. This work mainly presents a parallel APF concept for the compensation of harmonics to improve the reliability of the system. METHODS: The main contribution of this work is proposal of single control strategy for compensation of Power quality. Corrective back currents (for parallel APF) to compensate the identified harmonics are generated using modified d-q reference-based control methodology. RESULTS: The models are developed, and analysis is presented using MATLAB/SIMULINK software CONCLUSION: d-q reference theory control strategy is explained in detail. Load current, Source Voltage and DC link voltage which are measured using various sensors and send to processor. modified d-q reference the signals to be measured are same

Static Voltage Stability Assessment of Ethiopian power System Using Normalized Active Power Margin Index

Abstract: Voltage stability assessments, made so far on the Ethiopian electric power system (EEP), are limited both in number and in methodology. Here, in this paper the static voltage stability of the Ethiopian power system is investigated using an index called normalized active power margin. The methodology starts from determining Thevenin equivalent of a system as viewed from the load buses. The Thevenin equivalent parameters help to determine the load bus maximum active power transfer limit and to draw the PV relation curves. The approach avoids the time-consuming method of PV curve based maximum active power transfer determination, which requires large number of power flow computations. The resulting maximum active power transfer and current operating active power load are used for the index calculation. The index is tested using IEEE 30 bus system and produced results matching with other previously established indices. The index is capable of ranking vulnerability of load buses to voltage instability. Then, scenarios of heavy load and light load EEP cases, with and without system reactive power compensation, are investigated. Results reveal weakest buses are supplied from 66kV transmission lines, load bus 232 being the weakest of all. On the other hand, the most stable buses are supplied from 132 kV transmission lines, bus 149 being the most stable bus. PV curves drawn, also, reveal the improvement that come with reactive power compensation and with operating in light load condition.

A Sustainability-focused Project-based Learning Experience for Engineering Undergraduates: Case Study of a Smart Greenhouse Project

Abstract: In this paper, a smart greenhouse project has been presented as an example of a sustainability-focused project-based learning experience for undergraduates. While project-based instruction and learning experience has already gained enough momentum in several fields of education, the inclusion of sustainability perspectives from the science and engineering fields of studies is yet to make its room in the current course curricula as well as in the mindset of new generations of engineering undergraduates. This smart greenhouse project is an example of how sustainability can be brought into a classroom setting of engineering and technology programs as a project-based learning experience. The objective of this smart greenhouse project is to create an automated system capable of growing vegetation with little human input by utilizing electricity, computer programming, and a microcontroller operation. While this project was implemented by a group of two students with electrical engineering technology (EET) major as parts of their Introduction to Programming (ET 142) and Supervisory Control and Data Acquisition (ET 342) courses requirements at the University of Wisconsin-Green Bay, Wisconsin, USA, a similar sustainability-focused project-based learning approach can also be applied successfully in other courses at different levels of engineering and technology programs at other academic institutions.

Sustainable Urban Mobility Boost Smart Toolbox Upgrade

Abstract: SUMBooST2 research develops universally applicable data science methodology which extracts key urban mobility parameters and origin/destination matrices from the anonymized big data set gathered from telecom operator. The methodology (toolbox) provides transport planners with a method for fast, efficient, and reliable provision of data on movements within the certain area. Origin/destination matrices with modal split will provide transport planners with valid input data for the planning of urban transport systems. The algorithms which separate relevant mobility data from the overall dataset are the unique part of the toolbox. The algorithms to identify passenger car trips are developed in 2020 project SUMBooST, and they are being upgraded in 2021 to detect trips made by active mobility modes and public transport. For the methodology to be valid, it must be implemented in representative number of cities. Previous SUMBooST project included implementation and validation in the City of Rijeka, and SUMBooST2 continues with two other cities, City of Zagreb, and City of Dubrovnik. The aim of the paper is to present innovative toolbox for the boost of sustainable urban planning based on big data science.