Improve Energy Sustainability Research Articles

Environmental, technological, and economic analysis of supercritical coal-fired power system.

Developing countries primarily rely on fossil-based energy sources to meet their energy demands. The use of fossil fuels has several adverse environmental repercussions that damage the biosphere both directly and indirectly. Among fossil fuels, coal brings about the heaviest environmental externalities, yet its abundance makes its use widespread, particular in countries having significant power generation deficits, such as Pakistan. This study presents an environmental, technological, and economic analysis of a supercritical coal-based power unit located in Pakistan and used for electricity generation. For environmental assessment, the CML-1A baseline method in OpenLCA software was used, and eight midpoint impact indicators were selected. The functional unit chosen was 1 MWh of generated electricity. The results indicated that the category of ozone layer depletion has the least impact, whereas global warming potential has the highest impact score. Except for photochemical oxidation and human toxicity, the plant operational stage dominated most of the selected impact categories. The current paper also reveals that the removal efficiency of CO2 and other pollutants is higher in supercritical compared to subcritical plants. Moreover, the economic feasibility of supercritical plant is compared with chemical looping combustion (CLC)-based supercritical coal-fired power plant, and results shows that CLC-based coal-fired power plant is a more competitive and environmentally friendly option. The utilization of a scientific cleaner energy-management system in real-time, as exemplified in this study, may facilitate the development of a optimalpolicy framework that encouragesfor the adoption of cleaner coal power generation in developing countries, ultimately resulting in improved energy sustainability. Furthermore, this paper also presents some policy implications which could be helpful for policymakers, researchers, and industrialists to improve the sustainability of energy in emerging economies.

Maximizing energy transfer of solar-battery charge controller using voltage balancing strategy

Off-grid and grid-connected photovoltaic (PV) systems with battery storage rely heavily on efficient energy transfer to maximize PV power utilization and battery lifespan. However, existing literature often overlooks the crucial role of energy transfer efficiency in these systems. This paper proposes a novel, fundamental-based PV power flow strategy that addresses this gap by employing a concept of source-load voltage matching. The proposed strategy ensures optimal voltage matching between the PV array and the battery bank. This is achieved by configuring the battery bank voltage range (between nominal and fully charged states) to closely align with the variation in PV voltage at its Maximum Power Point (MPP) across different operating temperatures. This systematic approach requires specifying the DC load voltage, configuring the battery bank, and selecting PV modules with compatible Vmp (voltage at maximum power) parameters. The system utilizes a high-current blocking diode and current limiter for safe connection between the PV array and battery bank. Additionally, the strategy protects against battery overcharge by controlling parallel fans used for PV panel cooling. Experimental results with a 1.62 kW PV system employing lead-acid batteries demonstrate improved efficiency compared to traditional methods. This innovative approach has the potential to significantly enhance energy transfer efficiency, contributing to improved energy sustainability in PV systems.

Grid Integration for Electric Vehicles: A Realistic Strategy for Environmentally Friendly Mobility and Renewable Power

The promotion of electric vehicles (EVs) as sustainable energy sources for transportation is advocated due to global considerations such as energy consumption and environmental challenges. The recent incorporation of renewable energy sources into virtual power plants has greatly enhanced the influence of electric vehicles in the transportation industry. Vehicle grid integration offers a practical and economical method to improve energy sustainability, addressing the requirements of consumers on the user side. The effective utilisation of electric vehicles in stationary applications is highlighted by technological breakthroughs in the energy sector. The continuous advancement in science and industry is confirming the growing efficiency of electric vehicles (EVs) as virtual power plants. Nonetheless, a thorough inquiry is imperative to elucidate the principles, integration, and advancement of virtual power plants in conjunction with electric automobiles, specifically targeting academics and researchers in this field. The examination specifically emphasises the energy generation and storage components used in electric vehicles. In addition, it explores several vehicle–grid integration (VGI) configurations, such as single-stage, two-stage, and hybrid-multi-stage systems. This study also considers the various types of grid connections and the factors related to them. This detailed investigation seeks to offer insights into the various facets of incorporating electric vehicles into virtual power plants. It takes into account technology improvements, energy sustainability, and the practical ramifications for users.

Empowering solar photovoltaic logistic operations through cloud-enabled blockchain technology: a sustainable approach

In a world where renewable energy solutions are in high demand, solar photovoltaic (PV) systems are at the forefront, emphasizing the need for efficient and eco-friendly logistics. This coincides with the rise of blockchain technology as a game-changer in PV system management. Additionally, cloud computing is playing a pivotal role in transforming the IT landscape, providing seamless access to shared computing resources via the Internet. This research introduces a novel framework that utilizes cloud computing to enhance blockchain-based PV logistics. It employs a sophisticated mathematical model to optimize logistics components such as transportation, storage, inventory management, and supply chain coordination, with the goal of minimizing costs and improving overall efficiency. At the heart of this transformative paradigm lies a visionary cloud-based system, endowing PV logistic planners with the power of real-time access to mission-critical data. This infusion of data-driven decision-making capabilities fosters a seamless symphony of communication and enriches collaboration among stakeholders, setting the stage for monumental shifts in efficiency and management, ushering in a new era of sustainability and scalability within the photovoltaic industry. This technological synergy is not just about immediate gains. It is a testament to our commitment to improved energy sustainability and a testament to our shared vision of a greener future. In lockstep with the global pursuit of renewable energy solutions, this research lights the way toward a brighter, more sustainable tomorrow.

Exergy, exergoeconomic and exergoenvironmental assessments of experimental hybrid energy systems for hot water production to improve energy sustainability

Hybrid energy systems have proven their efficacy in improving energy sustainability. This paper focuses on the design and evaluation of various hybrid energy systems for hot water production in the experimental plant of the Laboratory for Quality Control in Buildings. The experimental facility was created to test and control various systems for energy supplies in buildings. In this work, three thermal installations were investigated: (1) a combined boiler cogeneration system, (2) a combined boiler solar collector system, and (3) a combined boiler heat pump system. After configuring each system in the laboratory, defining the control, and running the experimental essay, the corresponding data were obtained and treated. The exergy concept matches very well with the goal of promoting new systems that efficiently integrate renewable and nonrenewable energy resources. The exergy analysis and its extended assessments, the exergoeconomic and the exergoenvironmental, were applied to the designed systems. The results show that DHW production by the combined boiler solar thermal collector system is the most expensive in terms of the exergy cost index (about 33.29 kWhex/kWhex). DHW production by the combined boiler cogeneration system offers the lowest exergy unit cost (about 21.15 kWhex/kWhex). Based on economic and environmental indexes, DHW production by the combined boiler solar thermal collector system is the most suitable option. Its unit exergoeconomic cost is around 2.15 €/kWhex, and its exergoenvironmental unit impact is equal to 9.35 kg CO2/kWhex.

Integration of Solar Energy Technology in Improving Energy Sustainability and Efficiency in the Fisheries Sector (Case Study of Rokan Hilir Regency, Riau Province)

Improving sustainability and energy efficiency in the fisheries sector has emerged as an essential objective in addressing current environmental and economic concerns. One promising solution is the integration of solar energy technology in the fisheries sector. The purpose of the study was to analyse the potential and benefits of incorporating solar energy technology in improving sustainability and energy efficiency in the fisheries sector. This research included quantitative and qualitative analysis of the usage of solar energy technology in numerous aspects of the fisheries sector, such as fishing vessels, aquaculture, processing facilities, and related infrastructure. Data was collected from different locations with various characteristics during field research. The study found that integrating solar energy technology can lessen reliance on fossil fuels while also saving long-term operational costs. One of the potentials that can be used to encourage the growth of Rokan Hilir Regency, particularly in the field of fisheries, is the incorporation of solar energy technology. The Rokan Hilir Regency has the potential for solar energy conversion into electrical energy that can be used for a variety of purposes. The average peak power hour (Sun Peak Hour) for a year in Bangko District is 6.84 hours, with a minimum value of 6.23 hours in December and a maximum of 7.34 hours in August. The usage of integrated solar energy technology is utilised to support the activities of the fisheries sector, including catching, cultivating, or hatching, as well as fishing product processing. Obviously, the components used in each field must be adjusted to the level of electrical energy required. Several components that are used on fishing boats to facilitate fishing activities include spotlights, LED lights, fish cool boxes, and electric starters. Lighting lamps and DC water pumps can be used in the aquaculture industry. Solar energy is also used in the Fisheries Processing sector for LED lights and electric motors in shredded fish processing machines.

The Fleet and Berth Selection Model to Improve Energy and Environment Sustainability

This research aims to improve energy sustainability in transportation management. The case was derived from port-to-port coal transportation problem commonly faced by third-party logistic (3PL) company. During planning, they must determine which shipsets to be used and assign them to the loading/unloading berths. Each berth varies in terms of its loading/unloading speed and each shipset varies in terms of its capacity, sail speed, and fuel consumption rate. The selection of shipset impacts the auxiliary and main engine fuel consumption while the selection of berth impacts only the auxiliary engine fuel consumption. The target is to minimize the total fuel consumed by both engines for the whole shipset. We modelled the case through Multiple Vehicle Allocation Problem (MVAP) framework and proposed a heuristic algorithm to find the solutions. The heuristic algorithm is proven to be able to reach an optimal solution for small cases and near-optimal for medium to large cases.

Emerging Energy Sources for Sustainable Power Generation: An Overview

Electricity plays a big part in our daily life. Energy supply is a key factor in the modernization, automation, and expansion of the economy. Traditionally used energy sources are primarily used to create it. While traditional energy sourcesare rapidly running out, energy demand is rapidly increasing. A global problem is poor energy management as a result of scarce land resources, tight energy budgets, and weather-dependent renewable energy sources. Researchers that study energy are primarily concerned withthe depletion of conventional energy and the parallel development of practical alternative energy sources. Only 20% of the country's energy is used by homes; the remaining 80% is split across different economic sectors. When it comes to achieving sustainability in power generationfor sustainable development, the topic of renewable energy sources for generation cannot be overemphasized.The two main issues in the fight against climate change are without a doubt energy security and sustainability. Clean energy and a healthy environment are necessary for a world where people, plants, and animals can live in peace and health. Therefore, finding ways to incorporate renewable energy into the mix of energy production is necessary to improve energy sustainability and combat climate change. Todemonstrate their current condition and potential in the future, the literature on new energy sources is explored in this article. This analysis explains policies for renewable energy, potential assessments, comparative studies, energy optimization, sustainability, and the adaptation of strategic policies to promote the development of emerging renewable energy as a source of power generation to accelerate economic growth and preserve the environment.

From Targets to Action: Analyzing the Viability of REPowerEU in Achieving Energy Sustainability

EU’s energy sector is facing turbulent times as it strives to strengthen energy independence without losing sight of providing affordable and sustainable energy to all. The European Commission’s REPowerEU plan to accelerate the EU’s energy transition places additional pressure on each member state’s path to energy sustainability. To reach this objective, policymakers must assess the present energy sustainability levels of each member state, identify areas for development, and monitor the county’s progress over time. The purpose of this article is to analyze and compare the energy sustainability levels of the EU member states using a variety of indicators and to identify key cornerstones for advancing their energy transition. This study develops an energy sustainability composite index (ESCI) in order to unravel and compare the multiple lawyers of energy sustainability, including energy security, primary energy intensity, share of renewable energy resources, energy efficiency, CO2 emission intensity, and energy poverty. Log-Mean Divisia Index (LMDI) decomposition analysis is utilized to track the progress of energy policy in achieving reductions in energy-related CO2 emissions from 2015 to 2019. Changes in CO2 emissions were decomposed using Kaya identity factors to determine which of the following factors contributed the most to the changes: changes in emission intensity, energy intensity, economic or population growth. The results indicate that all EU member states have untapped potential for improving energy sustainability.

Does natural resources matter for sustainable energy development in China: The role of technological progress

Sustainable development has become a development goal in more and more countries. As the world's largest energy consumer and producer, the challenge of reducing energy dependence and improving energy sustainability is becoming a challenge for China's economic development. This research validates the impact of natural resources, technological progress, and sustainable energy development and their mechanisms through theoretical and empirical analyses. The paper selects 30 interprovincial panel data in China from 2004 to 2019, taking each region of China as the research object. The results show that (1) Natural resources have a positive contribution to sustainable energy development. (2) Natural resources make a positive contribution to technological innovation and technological introduction. (3) Technological innovation has a positive contribution to sustainable energy development. The study proposes relevant policy recommendations to help provinces enhance their energy sustainability.

Building Energy Consumption Prediction Using Neural-Based Models

In the recent years digital transformation became one of the most used approaches in building energy consumption optimization. Increased interest in improving energy sustainability and comfort inside buildings has created an opportunity for digital transformation to build predictive tools for energy consumption. By retrofitting or implementing new construction technologies nowadays the quantity and quality of the operational data collected has reached unprecedented levels. This data must be consumed by implementing powerful predictive tools that will provide the needed level of certainty. Adopting Six Sigma's Define, Measure, Analyze, Improve, Control (DMAIC) cycle as predictive analytics framework will make this paper accessible for both professionals working in energy industry and researchers that are developing models, creating the premises for reducing the gap between research and real-world business, guiding the use of data. Moreover, the selected strategy for preprocessing and hyperparameter selection is presented, the final selected models showing scalability and flexibility. At the end the architectures, performance and training time are discussed and then coupled with the thought process providing a way to weigh up the options. Building energy consumption prediction, it is a relevant and actual topic. Firstly, on European level, meeting the targets set by the new European Green Deal for buildings sector is relying heavily on digitization and therefore on predictive analytics. Secondly, on Romania level, the liberalization of the Energy market created an unpreceded energy price increase. The negative social impact might be diminished not only by the price reduction, but also by understanding how the energy is consumed.

Average Peak Age of Information Analysis for Wireless Powered Cooperative Networks

Future of massive Internet-of-Things (IoT) and low latency applications hinges on delivering fresh information on time. Thus, to analyse data freshness for time critical use cases in future networks, the age of information (AoI) measure is introduced. Besides, energy harvesting is also essential to improve energy sustainability and lifetime of a power-constrained and cost-efficient network. Therefore, we investigate a new network architecture suitable for future massive IoT where connectivity, energy sustainability and freshness of information are emerged. We study a wireless powered cooperative network, wherein a source and a relay charge their finite-sized capacitors by harvesting energy from a power station. For decode-and-forward (DF) and amplify-and-forward relaying strategies, average AoI and peak AoI (PAoI) are investigated to indicate how the randomness of the data/power transfer and size of the capacitors affect the age metrics. It is shown that, although utilizing a power-limited relay imposes more delay, the age metrics could be improved. Specifically, for the DF scheme with more waiting time due to signal processing, we may achieve lower average PAoI due to improving the reliability. Furthermore, special cases of the proposed system are discussed, e.g., full-power nodes and one-shot successful data transmission. Finally, numerical results are provided to clarify when a relaying strategy can outperform the direct transmissions. It is shown that for all values of the size of the capacitors, position of the relay, the power station’s power, and etc, there is not a unique optimal transmission strategy to minimize AoI metrics.

A novel approach for multi-constraints knapsack problem using cluster particle swarm optimization

Cluster particle swarm optimization (CPSO) is distinct approach of PSO, in which each sub-swarm points an exact region with a particular diverse situation, to perform on-demand computing. Particularly, it is used for problems based on a cluster, which contains many locally optimal solutions to reduce wastage of energy and improve energy sustainability. Among the combinatorial optimization problems, the knapsack problem is widely studied. There are several variants and techniques devised over the times, to get the optimal solutions for solving multiple constrain problems by considering weight and capacity to minimize energy consumption. Still, the multi-constraint Knapsack problem (KP) remains the major challenge. The proposed cluster-based Particle swarm optimization (PSO) algorithm is used for solving problems having multiple energy preserving constraints. The proposed algorithm incorporates Boundary value analysis (BVA) techniques and is compared with the standard knapsack dataset for effective energy optimization. The proposed algorithm is evaluated based on performance criteria, thereby, achieving 100% accuracy for minimum dimension and approximately more than 85% for higher dimension of energy minimization problems. The proposed techniques are compared with Simulated annealing (SA) and Genetic algorithm (GA). It is evident that the proposed techniques out performed well to compare to other algorithms. Future research focuses on applying proposed techniques, to machine learning and deep convolutional neural network for quicker searching process. Furthermore, plan to utilize the proposed techniques for other combinatorial optimization problems.

Advanced Power Generation Using a Nitrogen Turbine Engine Instead of a Conventional Injection Steam Turbine Engine

An ever-increasing demand for electrical power and soaring levels of energy consumption around the world have led to an energy crisis. Thus, this paper aims to review the conventional technologies against those of newer developments in electrical power generation such as using nitrogen generators. The nitrogen generator method is most appealing as it is a seemingly free energy already existing in nature. A nitrogen generator with a 5000 (Nm3/h) capacity has the potential to be used to analyze gas composition and the results are compared with the gas composition of a conventional steam turbine, which is used to pressurize 6000 (kWh) injection steam turbines. The magnetic bearing must be installed in both systems to modify all centrifuged systems which reduces all energy consumption in all systems by more than 50%. Artificial intelligence is used with the machine to analyze and control nitrogen gas flow to provide a more precise evaluation resulting in a more efficient technology. It should further be noted that the nitrogen turbine is superior to the steam turbine because it does not require the burning of fossil fuel to generate power. Hence, it is crucial to modify conventional technologies to improve energy sustainability and begin the long task of tackling environmental issues.

Location Suitability Analysis for Wind Farm Exploitation Using Fuzzy Analytic Hierarchy Process

The development of renewable energy has been constantly conducted as an attempt to increase energy diversification, improve energy sustainability and reduce greenhouse gas emissions, including the wind power plant (WPP). Suitable location selection is urgently necessary to achieve optimized output and high economic values. There are multi-criteria to be considered during the selection process, namely wind velocity, climate condition, road access, environmental impact, land use, land tilt, plain condition, distance to residential areas, etc. This study aimed to develop a software supporting multi-criteria decision-making based on artificial intelligent technology, namely fuzzy analytic hierarchy process (fuzzy-AHP) which was implemented to evaluate the WPP location suitability. The method of fuzzy-AHP is believed to be able to generate prioritized criteria supporting the location of WPP with high accuracy. Based on those criteria, there were two locations identified at Tanah Laut Regency, South Kalimantan, Indonesia, as the most suitable research sites. It is expected that studies employing fuzzy-AHP are to be further developed to determine wider renewable WPP locations.

How Different Electricity Pricing Systems Affect the Energy Trilemma: Assessing Indonesia’s Electricity Market Transition

Many countries have a clear policy objective of increasing their share of renewable energy sources (RESs). However, a major impediment to higher RES penetration often lies in the historically grown structures of a country’s electricity sector. In Indonesia, policy makers have relied on cheap fossil fuels and state control to provide the population with access to both reliable and affordable electricity. However, this focus on only two of the three horns of the energy trilemma, namely energy security and energy equity (and not sustainability), may put Indonesia at risk of missing its ambitious RES targets. In this context, a number of small-scale reform attempts to promote RES integration in recent years have proved to be relatively unsuccessful. Like many other countries, Indonesia needs clear policy directions to avoid an unsustainable lock-in into a fossil fuel future. In the last decades, several other countries have successfully restructured their electricity sectors, for example by introducing a wholesale market for electricity under different electricity pricing systems, including nodal, zonal, or uniform pricing. These countries may hold valuable experiences of overcoming the historically grown barriers to successful RES integration through a greater role for market mechanisms. We develop three generic models that allow policy makers to analyze the impact of introducing either a nodal, a zonal, or a uniform pricing system on the three horns of the energy trilemma in their country. We evaluate our model using a simplified network representation of the Indonesian electricity sector. Our results indicate that each of the pricing systems is able to foster specific horns of the energy trilemma. Considering that any major reform intended to improve energy sustainability in Indonesia will only be a success if it also addresses energy security and energy equity, we also discuss our results from the perspective of energy justice and the need to balance the country’s energy trilemma. Ultimately, we illustrate a transformation pathway for a more sustainable and just transition to a low-carbon economy in Indonesia.

System and Design for Selective OFDM SWIPT Transmission

Simultaneous wireless information and power transfer (SWIPT) augments a wireless device's capability to transmit data by adding a harvesting component to the standard information processing receiver. With SWIPT, both information processing and energy scavenging are combined to allow a SWIPT device to become its own recurrent power source. This article proposes and analyzes the functionality of a novel selective orthogonal frequency-division multiplexing (OFDM) receiver architecture. The architecture leverages the OFDM signal structure to extract the cyclic prefix (CP) of the signal for energy harvesting and selectively harvest a fraction of the received signal for increase energy storage. This article also evaluates the rate-energy (R-E) tradeoff of the system as a means for analyzing the switching time's impact on rate and energy. Additionally, this article examines the feasibility of harvesting sufficient energy to power the OFDM processing portion of the receiver. To understand the feasibility, an optimization problem is developed to minimize the portion of the information signal used for harvesting while ensuring sufficient energy is harvested to perform the processing. To facilitate the evaluation, Monte Carlo simulations are run presenting system level R-E tradeoff and feasibility performance. Selective OFDM transmission is found to provide improved energy harvesting and sustainability.

An Integrated Approach to the Realization of Saudi Arabia’s Energy Sustainability

As system thinking is a recognized approach to the comprehension and realization of energy sustainability, this paper applies a holistic representation to the World Energy Trilemma Index (WETI) key indicators using Bayesian Belief Networks (BBN) to illuminate the probabilistic information of their influences in Saudi Arabia’s context. The reached realization is suggested to inform the policies to improve energy sustainability, and thus the country’s rank in the WETI. The analysis used two groups of learning cases, one used the energy statistics of the period from 1995 to 2019 to show the outlook of the Business as Usual path, and the other addressed the projected data for the period from 2018 to 2037 to investigate the expected impact of the new policies. For both BAU and new policies, the BBN calculated the improvement, stability, and declining beliefs. The most influential factors on energy sustainability performance were the electricity generation mix, CO2 emissions, energy intensity, and energy storage. Moreover, the interlinkage between the influential indicators and their causes was estimated in the new policies model. A back-casting analysis was carried out to show the changes required to drive the improvement belief to 100%. The compiled BBN can be used to support structuring policymaking and analyzing the projections’ outcomes by investigating different scenarios for improvement probabilities of energy sustainability.

Energy potential of biogas and sludge from UASB reactors in the State of Paraná, Brazil

Upflow Anaerobic Sludge Blanket (UASB) reactors are widely used for domestic sewage treatment in Brazil, and generate sludge and biogas as by-products. Typically, the sludge is sent to sanitary landfills, and the biogas is burned in flares. This study assessed the energy potential of these by-products in sewage treatment plants (STPs) located in the state of Paraná, Brazil. First, an overview of biogas energy recovery potential in a full-scale STP based on UASB reactors was carried out. Afterwards, a total of 239 STPs in the state of Paraná were assessed, and the energy potential of the by-products was estimated by a mathematical model. Data were spatially classified using ArcGIS®, taking into account the different effluent characteristics (worst, typical and best scenario), sludge dehydration systems (drying bed and centrifuge) and sizes (small, medium and large). Among the states in Brazil, Paraná presented the highest biogas potential, although nowadays it exploits only 0.4% of its capacity. Biogas was the main by-product generated by UASB reactors in Paraná, and if used in the entire state, it could supply the energy demands of a city with 111,000 inhabitants. Biogas corresponded to 65, 64 and 74% of the total potential (sludge and biogas) for small, medium and large STPs, respectively. The study of the energy potential of the by-products associated with GIS tools positively contributes to the decision-making process in sanitation management and to improve energy sustainability.

An economic evaluation on welfare distribution and carbon sequestration under competitive pyrolysis technologies

Pyrolysis and gasification are considered as a means of producing renewable energy and improving energy sustainability, which has become attractive renewable technologies to many countries. Unlike other studies that are conducted in small scale, this study aims to aggregate the economic and environmental effects such as agricultural benefits, energy sale, and carbon sequestration to provide more detailed information to decision-makers before these projects are widely employed. This study first employs a lifecycle assessment to investigate the feasibility, profitability, and emission reduction of four major pyrolysis and gasification technologies using crop residuals, and then conducts a sensitive analysis to examine the most influential factors. The results indicate that the intermediate pyrolysis with rice straw and slow pyrolysis from corn stover could offset the carbon dioxide the most. However, the pyrolysis value is also sensitive to production of the feedstock used. Value adding of stover-based biochar under fast pyrolysis improves profitability but other technologies do not have such patterns. Additionally, while gasification can generate considerable amount of renewable electricity, it yields almost zero percent of biochar that can be used as a soil amendment, and thus its contribution to agricultural sector is trivial.