The placement of wind turbines is a crucial design element in wind farms, given the energy losses resulting from the wake effect. Despite numerous studies addressing the Wind Farm Layout Optimization (WFLO) problem, considering multiple directions to determine wind turbine spacing and layout remains limited. However, relying solely on one predominant direction may lead to overestimating energy production, and loss of energy generation. This work introduces a novel mathematical programming optimization framework to solve the WFLO problem, emphasizing the wind energy's nonlinear characteristics and wake effect losses. Comparisons with traditional layout approaches demonstrate the importance of optimizing wind farm layouts during the design phase. By providing valuable insights into the renewable energy sector, this research aims to guide future wind farm projects towards layouts that balance economic considerations with maximizing energy production.

In view of achieving the decarbonization target, green hydrogen is commonly regarded as the alternative capable of reducing the share of fossil fuels. Despite its wide application as a chemical on industrial scale, hydrogen utilization as an energy vector still suffers from unfavorable economics, mainly due to its high cost of production, storage and transportation. To overcome the last two of these issues, different hydrogen carriers have been proposed. Hydrogen storage and transportation through these carriers involve: 1. the carrier hydrogenation, exploiting green hydrogen produced at the loading terminal, where renewable sources are easily accessible, 2. the storage and transportation of the hydrogenated species and 3. its subsequent dehydrogenation at the unloading terminal, to favour H2 release. Although there is a number of studies in literature on the economic feasibility of hydrogen transport through different H2 vectors, very few of them delve into the technical evaluation of... [more]

This study presents a comprehensive approach to optimizing hydrogen supply chain network (HSCN), focusing initially on Texas, with potential scalability to national and global regions. Utilizing mixed-integer nonlinear programming (MINLP), the research decomposes into two distinct modeling stages: broad supply chain modeling and detailed hub-specific analysis. The first stage identifies optimal hydrogen hub locations, considering county-level hydrogen demand, renewable energy availability, and grid capacity. It determines the number and placement of hubs, county participation within these hubs, and the optimal sites for hydrogen production plants. The second stage delves into each selected hub, analyzing energy mixes under variable solar, wind, and grid profiles, sizing specific production and storage facilities, and scheduling to match energy availability. Iterative refinement incorporates detailed insights back into the broader model, updating costs and configurations to converge upo... [more]

The decarbonization of the society has a very high effect on the power grids as especially the energy generation will be almost completely shifted to CO2-neutral sources such as wind and solar. This implies significant design changes to the power grids and power systems, which lie between the electricity producers and consumers. In this paper, we discuss both the generation and consumer side, including the grid changes and required data exchange to support the transition.

The chemical industry is actively pursuing energy transition and decarbonization through renewables and other decarbonization initiatives. However, navigating this transition is challenging due to uncertainties in capital investments, electricity costs, and carbon taxes. Adapting to decarbonization standards while preserving existing valuable infrastructure presents a dilemma. Early transitions may lead to inefficiencies, while delays increase the carbon footprint. This research proposes a framework to find an optimal retrofit decarbonization strategy for existing oil refineries. We start with a generic process flowsheet representing the refinery's current configuration and operations, and consider various decarbonization alternatives. Through superstructure optimization, we identify the most cost-effective retrofit strategy over the next three decades to achieve decarbonization goals. We develop a Mixed-Integer Linear Programming (MILP) model, integrating simplified process equations... [more]

This work presents an overview of the path towards the use of renewable and nonconventional resources for a sustainable chemical and process industry. The aim is not only to lead the way to meet the sustainable development goals but also to maintain the style and quality of life achieved by the technologies and products developed within this sector. Alternative raw materials are to be used and processed differently while a new paradigm for utilities is to be established. The development of technologies and their deployment faces several barriers that we as process engineers can help overcome by providing insight into the alternatives, the thresholds to achieve to become competitive, and strategic analyses.

The planetary boundaries (PBs) define ecological limits that are critical to preserve the stability of the Earth. Six of them have already been exceeded, which calls for urgent action to optimize industrial systems capable of operating within the safe operating space that they define for humanity. Here we discuss the challenges and opportunities of including PBs in a range of application domains in Process Systems Engineering, focusing on chemicals and fuels production and the use of mathematical programming coupled with life cycle assessment to support sustainable decision-making.

Northern European nations are at the forefront of renewable energy adoption but face challenges in optimizing energy conversion efficiency. There is a lack of detailed understanding of how behavioral factors affect the efficiency of renewable energy conversion in these countries. This study aims to evaluate and compare the renewable energy conversion efficiency of Northern European countries, intending to inform strategic policy making and identify best practices for technology deployment in the renewable energy sector. Employing a Data Envelopment Analysis (DEA) model, the study integrates behavioral economic parameters—specifically, the aversion loss and gain significance coefficients—to assess the efficiency of renewable energy conversion, accounting for psychological factors in decision making. A comprehensive sensitivity analysis was conducted, varying the gain significance coefficient while maintaining the aversion loss coefficient at constant levels. This experiment was designed... [more]

Sustainable energy presently represents the energy of the future, which should be based on the application respecting the importance of energy priorities, increasing regional self-sufficiency, regional control of energy, and regulation of resource use. In the area of energy supply, the use of RES has been increasingly popular, mainly due to the instability in the energy market and the political situation worldwide. Paper’s ambition is to evaluate the efficiency of the selected RES use in the specific conditions of Slovakia, with the aim to achieve the EU targets. This is important due to the increasing use of RES in Slovakia. The objective of this paper is achieved through an analysis of the energy profit of the RES system, comparing the costs of the proposed solutions. The evaluation is carried out by calculating the energy and economic efficiency of three possible buildings used in the research. Using the data obtained, the results show the most suitable alternative for each building... [more]

Despite renewable energy source integration being a well-established requirement in international policies, energy systems still face some unresolved issues, including the intermittence of production. To tackle this problem, a viable solution could comprise the off-peak storage of electricity production excess, to be consumed later during peak-load hours. The transition from the diffuse pattern of centralized generation to the distributed model, involving energy communities, suggests an additional aspect to manage: the spatial constraints of systems for domestic applications. Compressed-air energy storage represents a promising Power-to-Power technology for small-scale energy integration. This study proposes the application of a gas−liquid energy storage system (GLES) in a residential building, using renewable energy excess from a photovoltaic (PV) array. The performance of the proposed system, whose operation involves the compression of the gaseous mass through a piston operated by mi... [more]

Despite that previous research exists, there is a need for further research on the quantitative aspects of this Nexus. Existing Water-Energy-Environment Nexus management tools and frameworks are based on indicators aiming to model the whole system, analyze the involved resources, and test potential management strategies. The environmental, social, and economic consequences of actions already taken and ongoing projects require important focus because of the strong relationship between water and energy supply, and that both are key issues for society’s development and sustainability. The present research focuses on the indicators that the Water-Energy-Environment Nexus tools and frameworks use to analyze the whole problem. Existing tools often require large amounts of data, becoming a time-consuming process that lowers the capacity to evaluate the political problems of high pollutants. With the aim of accelerating time evaluation, this research builds an indicator to rapidly evaluate the... [more]

There is a growing interest in green hydrogen, with researchers, institutions, and countries focusing on its development, efficiency improvement, and cost reduction. This paper explores the concept of green hydrogen and its production process using renewable energy sources in several leading countries, including Australia, the European Union, India, Canada, China, Russia, the United States, South Korea, South Africa, Japan, and other nations in North Africa. These regions possess significant potential for “green” hydrogen production, supporting the transition from fossil fuels to clean energy and promoting environmental sustainability through the electrolysis process, a common method of production. The paper also examines the benefits of green hydrogen as a future alternative to fossil fuels, highlighting its superior environmental properties with zero net greenhouse gas emissions. Moreover, it explores the potential advantages of green hydrogen utilization across various industrial, c... [more]

Advance in renewable penetration has promoted the interaction between the AC and DC power system and multi-energy sources. However, the disparate nature of different energy utilization technologies presents strong challenges for the economic dispatch of such a complex system. This paper proposes a comprehensive characterization of the AC/DC power system considering multi-energy and renewable integration. Detailed models are elaborated for the AC/DC power grid, the district heating system (DHS), coupling units, and renewables to describe their inner interactions accurately. On this basis, an economic dispatch method is developed to minimize the operation cost and renewable’s abandonment. Simulations indicate that the interaction between the AC/DC power systems and multi-energy sources can enhance voltage levels and improve operational economy.

The escalating global concern for sustainable development necessitates an in-depth understanding of the role of renewable energy projects. Evaluating their impact on economic, environmental, and social sustainability is of significant importance. In this study, the impact of green energy projects on economic, environmental, and social sustainability across APEC countries from 2010 to 2021 is comprehensively assessed using machine learning models. The employed machine learning models revealed associations between key variables and sustainability implications of green energy projects. Renewable energy consumption emerged as a significant contributor to economic performance, scoring a compelling importance score of 0.34. Concurrently, fossil fuel energy consumption and urban population were identified as key influencers on environmental outcomes and social impacts, respectively, with importance scores of 0.36 and 0.42. The empirical evidence presented in this research underscores the pivo... [more]

The global energy demand is increasing day by day. Fossil fuels such as crude oil, coal and gas are the main source of energy worldwide. However, fossil fuels, which cause acid rain, the greenhouse effect and other such environmental problems, will eventually be depleted, and renewable energy seems to be the most reasonable solution in this regard. Renewable biofuels have significant potential and can meet the world’s current energy demand. One of the important biofuels is biodiesel, and in the future it can replace petroleum. Waste cooking oil was used as a raw material in biodiesel production in order to reduce the production cost of the offered additive. In this study, the aim was to optimize the process parameters for biodiesel production within the acceptable limit values in the literature. Therefore, the molar ratio of methanol to waste cooking oil (9:1−15:1), catalyst concentration (1−5% by weight) and reaction time (60−120 min) were studied for two catalyst types, potassium hyd... [more]

The green chemistry method for nanocatalyst synthesis along with environmentally feasible non-edible sources are promising alternatives to fossil fuels. The current study focuses on the synthesis of copper oxide phyto-nanocatalyst and the identification of a new renewable feedstock, Citrullus colocynthis, to reduce environmental pollution. The highest biodiesel yield (95%) was obtained under optimum conditions of a 1:8 oil-to-methanol ratio and reaction temperature of 85 °C for 120 min with a 0.365 wt% catalyst concentration. The phyto-nanocatalyst was synthesized using seed oil cake after extracting oil with the salt of copper (copper oxide). The catalyst was then subjected to various analyses, namely, EDX, FT-IR, SEM, and XRD. The catalyst was proved to be efficient and effective after being reused five times and still there was a very small difference in biodiesel yield. All the analyses also show sustainable and stable results. Thus, copper oxide phyto-nanocatalyst with non-edible... [more]

Oscillating-water-column wave energy converters (OWC-WECs) are gaining attention for their high energy potential and environmental friendliness. However, their irregular input energy characteristics pose challenges to achieving stable power generation, particularly due to high peak power compared to average power. This study focuses on stable rating control to enable continuous power generation in the presence of irregular wave energy. It is difficult to precisely configure the existing rated power controllers due to physical time delays; this impacts system stability and utilization. To address this, we propose a rated power controller that compensates for system time delays using a deep learning algorithm. By predicting the valve control angle in advance and analyzing the input data for angle estimation, we successfully compensate for the physical time delay. The performance of the proposed rated power controller, incorporating the deep learning algorithm, is evaluated by analyzing t... [more]

To cope with the energy crisis and environmental pollution, the future development of the power system has to change towards a clean, low-carbon, flexible, and diversified direction. This paper proposes a decentralized power dispatching model based on blockchain technology to address the problems of uncertainty, privacy, security, and reliability in power dispatching systems containing renewable energy and flexible loads. Considering the uncertainty of wind, photovoltaic, and flexible load integration into the power grid, the total generation costs of the system are established, and the smart contracts of the decentralized power dispatching are proposed. The proof of work (PoW) consensus mechanism is improved in this paper. The hash operation that must be repeated in the PoW algorithm is replaced by an optimized computation process using a blockchain-based genetic algorithm (BD-GA). The proof of work-load-genetic algorithm-based (PoW-GAD) consensus algorithm is proposed. The decentrali... [more]

Crude oil, Bitcoin, and carbon dioxide emissions are major issues that are significantly impacting the global economy and environment. These three issues are complexly interlinked, with profound economic and environmental implications. In this study, we explore the correlation among these three issues and attempt to understand the influence of crude oil and Bitcoin on carbon dioxide emissions. We created a novel approach, named quantile mediation analysis, which blends mediation regression with quantile regression, enabling us to explore the influence of Brent crude oil on carbon dioxide emissions by considering the mediating impact of Bitcoin. According to the findings from using our new approach, the impact of Brent crude oil on carbon dioxide emissions is partly mediated by Bitcoin, and the association between Brent crude oil and carbon dioxide emissions involves both direct and indirect effects. Since the carbon dioxide generated by the extraction of crude oil and Bitcoin has a gre... [more]

The transition to a green economy for any country is crucial for the sustainability development of the economy, environment, society, and governance (EESG). A green economy is a sustainable approach to combating climate change and promoting sustainable development through the adoption of sustainable energy. This research utilizes the Delphi and fuzzy analytical hierarchy process (AHP) methodologies to assess and rank the EESG criteria and policy options for transitions to a green economy. The factors and policy choices are identified using the Delphi approach for further analysis. These factors and policy alternatives for switching to a green economy for sustainable development are determined using the fuzzy AHP technique. According to the fuzzy AHP approach, environmental, social, and economic factors are best suited for green economy transitions. The findings also show that the most crucial policy options for the switch to a green economy are research and development, carbon pricing,... [more]

Intelligent manufacturing under Industry 4.0 assimilates sophisticated technologies and artificial intelligence for sustainable production and outcomes. Blockchain paradigms are coined with Industry 4.0 for concurrent and well-monitored flawless production. This article introduces Sustainable Production concerned with External Demands (SP-ED). This method is more specific about energy production and the distribution for flawless and outage-less supply. First, the energy demand is identified for internal and external users based on which sustainability is planned. Secondly, Ethereum blockchain monitoring for a similar production and demand satisfaction is coupled with the production system. From two perspectives, the monitoring and condition satisfaction processes are validated using federated learning (FL). The perspectives include demand distribution and production sustainability. In the demand distribution, the condition of meeting the actual requirement is validated. Contrarily, the... [more]

Solar is a significant renewable energy source. Solar energy can provide for the world’s energy needs while minimizing global warming from traditional sources. Forecasting the output of renewable energy has a considerable impact on decisions about the operation and management of power systems. It is crucial to accurately forecast the output of renewable energy sources in order to assure grid dependability and sustainability and to reduce the risk and expense of energy markets and systems. Recent advancements in long short-term memory (LSTM) have attracted researchers to the model, and its promising potential is reflected in the method’s richness and the growing number of papers about it. To facilitate further research and development in this area, this paper investigates LSTM models for forecasting solar energy by using time-series data. The paper is divided into two parts: (1) independent LSTM models and (2) hybrid models that incorporate LSTM as another type of technique. The Root me... [more]

This review investigates the effects of the Brazilian agriculture production and forestry sector on carbon dioxide (CO2) emissions. Residual biomasses produced mainly in the agro-industrial and forestry sector as well as fast-growing plants were studied. Possibilities to minimize source-related emissions by sequestering part of carbon in soil and by producing biomass as a substitute for fossil fuel were extensively investigated. The lack of consistency among literature reports on residual biomass makes it difficult to compare CO2 emission reductions between studies and sectors. Data on chemical composition, heating value, proximate and ultimate analysis of the biomasses were collected. Then, the carbon sequestration potential of the biomasses as well as their usability in renewable energy practices were studied. Over 779.6 million tons of agricultural residues were generated in Brazil between 2021 and 2022. This implies a 12.1 million PJ energy potential, while 4.95 million tons of for... [more]

Anaerobic digestion is a well-known and long-used biological method for stabilizing organic materials. Among the benefits of this process in waste management are the reduction of greenhouse gases, the production of alternative energy, and the acquisition of valuable digestate that can be used in the form of biogas, thereby closing the cycle of elements in nature. For some materials, such as manure, which is heterogeneous in terms of morphology and chemical composition, digestion of a single substrate may not be very efficient. Therefore, more and more studies on the co-digestion process are appearing in the literature. This solution allows higher biogas production and the possibility of processing several wastes simultaneously. The prospect of the future effective application of anaerobic co-digestion depends on regulations, work regime, and access to raw materials. Therefore, there is a need to systematize the available knowledge and results, as well as to identify the possibilities a... [more]

Direct air capture (DAC) is considered one of the mitigation strategies in most of the future scenarios trying to limit global temperature to 1.5 °C. Given the high expectations placed on DAC for future decarbonisation, this study presents an extensive review of DAC technologies, exploring a number of techno-economic aspects, including an updated collection of the current and planned DAC projects around the world. A dedicated analysis focused on the production of synthetic methane, methanol, and diesel from DAC and electrolytic hydrogen in the European Union (EU) is also performed, where the carbon footprint is analysed for different scenarios and energy sources. The results show that the maximum grid carbon intensity to obtain negative emissions with DAC is estimated at 468 gCO2e/kWh, which is compliant with most of the EU countries’ current grid mix. Using only photovoltaics (PV) and wind, negative emissions of at least −0.81 tCO2e/tCO2 captured can be achieved. The maximum grid inte... [more]