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Abstract In this paper, a reintegration-based multi-objective intentional controlled islanding (ICI) model is proposed to enhance resiliency of electrical power systems under catastrophic events. This remedial measure plan relies on a mixed-integer linear programming model with two objective functions including reintegration risk and total load shedding value. While ensuring that each island includes only coherent generators, the proposed multi-objective model solves the controlled islanding problem using lexicographic optimization approach. To ease the islands’ reintegration, charging reactive power, reliability, capacity, and power flow disruption of transmission lines are considered in the model. After implementation of controlled islanding, each resulted island may face temporary active/reactive load-generation imbalance, which may put the islands at the risk of frequency instability, transient voltage instability or a combination of both. The proposed model reduces these risks by modeling energy storage systems (ESSs) and static VAR compensators (SVCs) as fast corrective control actions. In addition to modeling voltage dependent loads in the controlled islanding problem, a linear island frequency response (IFR) model is proposed for frequency stability assessment. The test results of the proposed ICI model on the IEEE 39-bus and IEEE 118-bus test systems demonstrate its performance.

It has been known for a very long time that chemical energy may be converted into electrical energy by using biomass, considered a renewable energy source. In the study that is being presented here, an explanation and a presentation are offered on a one-of-a-kind hybrid system that generates dependable power and cooling by harnessing the chemical energy of biomass. An anaerobic digester takes in organic material and converts it into biomass by using the high-energy content of cow manure as fuel. The Rankin cycle is the primary engine that drives the system that produces energy, and its combustion-based byproducts are routed to an ammonia absorption refrigeration system in order to provide sufficient cooling for the process of pasteurizing and drying the milk. It is expected that solar panels might contribute to the production of sufficient amounts of power for necessary activities. The technical and financial facets of the system are both being investigated at the moment. In addition, the optimal working conditions are determined by employing a forward-thinking multi-objective optimization strategy. This method simultaneously raises the operational effectiveness to the greatest extent that is practically possible while simultaneously lowering both expenses and emissions. The findings indicate that under ideal conditions, the levelized cost of the product (LCOP), efficiency, and emission of the system are, respectively, 0.087 $/kWh, 38.2%, and 0.249 kg/kWh. The digester and the combustion chamber both have very high exergy destruction rates, with the digester having the highest rate and the combustion chamber having the second-highest rate among all of the system's components. This assertion is supported by every one of these components.

In this chapter, turbulent flow of water-based optimization (TFWO) inspired based on whirlpools created in turbulent flow of water is used to solve the maximum power point tracking (MPPT) of photovoltaic systems in partial shading conditions. The TFWO is used to determine the optimal duty cycle of the DC/DC converter with the objective of maximizing the extracted power of the photovoltaic system. The capability of proposed method is evaluated in different patterns of partial shading to achieve global optimal power. The simulation results showed that TFWO is able to track the global maximum power point (GMPP), successfully in PSC and also fast climate changing. The TFWO has a better tracking capability with faster tracking speed and accuracy than particle swarm optimization (PSO) in obtaining the GMPP. Moreover, the results indicate that the use of buck–boost converter led to faster and more accurate access to the global optimal point than the system equipped with boost converter. The results showed that photovoltaic system with boost converter cannot obtain global maximum power in climate changing condition and limited the efficiency of the MPPT algorithm, while the photovoltaic system with buck–boost converter could be tracked GMPP due to its wider operating area.

Abstract In this study, fluctuation with three frequencies is applied to the boundaries of the cyclone separator. Flow field including dominant frequency and amplitude of vortices at three regions (vortex finder, main cylinder, and cone) and performance parameters (collection efficiency and pressure drop) are studied. Lagrangian-Eulerian Frame is applied, and Large Eddy Simulation (LES) is used for turbulence modeling. Three inlet flows of 4, 6, and 8 [g/s] are considered. The Power Spectral Density (PSD) of fluctuations has been increased by increasing the inlet flow rate. The fluctuating flow will make vortices with higher amplitude than the uniform flow. Because the high amplitude vortex breaks into and transmits energy to the small vortex, pressure drop increases with frequency increment. The pressure drop equations in the non-uniform flow of the cyclone are derived based on the existing pressure drop relationships. The average separation efficiency in non-uniform flow is less than uniform flow.

The growing global awareness of social and environmental issues has led investors to prioritize sustainable investments. This study examines the relationship between ten Islamic and conventional sector indices, which include stocks screened for environmental, social, and governance (ESG) factors, across three energy-related fields: renewable energy, energy efficiency, and oil equipment and services. Using a quantile cross-spectral approach, this research finds a high level of long-term synchronization among all energy-related sectors and indices. However, as markets shift from bearish to bullish, the current relationship between energy-related sectors and Islamic and conventional indices weakens. To support the findings in this research and investigate potential financial implications, this investigation applies a causality-in-quantiles approach. The research in this study shows a bidirectional causal relationship between conventional and Islamic indices, particularly in the energy efficiency sector during bearish market conditions. At lower tails, ESG market indices are found to cause renewable energy products, suggesting a hedging mechanism. The findings of this study assert that investments that do not possess any ESG shortcomings are imperative for effectively bolstering renewable energy companies and fostering opportunities for energy efficiency. These conclusions hold considerable ramifications for energy policymakers as they strive to devise more robust financial mechanisms that can provide substantial support to the burgeoning green sector.

Abstract Sustainable production of biofuels has provided an attractive alternative to fossil fuels, which has relieved the concern regarding energy supply and global climate change. Currently, interest in metabolic engineering of yeasts as microbial cell factories for biofuel production, which varies from short-chain ethanol to long-chain fatty acid-derived molecules, is growing. The commercial production of new energy-dense biofuels using yeasts and new synthetic biology tools is now possible due to recent developments in metabolic engineering. Here, it is attempted to comprehensively and critically review the latest advances in metabolism-targeted strategies and the production of different types of biofuels using yeasts. Furthermore, the key challenges and perspectives have been discussed for improving yeast biorefineries for the production of biofuels, such as host compatibility of heterologous genes, substrate extension for alternative feedstocks, better tools for reprogramming cell metabolism, host robustness for tolerating or alleviating toxicity induced by end products, and new design principles with predictable behaviors for the constructed biological systems.

Abstract A method to analyze multi-area optimal power flow in novel energy management systems is proposed and studied in this paper. The studied power network consisted batteries, distributed generators and electric parking lots. A straightforward granular-based method is introduced to maintain the simplicity of the calculations while the independency of areas is preserved. In this case, a three-area power network as a multi-area power network problem is chosen to test and approve the applicability of the proposed method in terms of accuracy, simplicity, preserving independency, and not requiring any control or initial parameters. According to the results, maximum error is 0.0009 pu in the selected case study. Moreover, two valued variables namely operation cost and voltage deviation are selected as the two fundamental objective functions to be analyzed both multi-objectively and solely. Furthermore, in this paper, soon-to-be-indispensable electric vehicle parking lots and distributed generators are also utilized to optimize operation cost (up to 49.28%) as well as voltage deviation (up to 48.99%). Also, the influence of each area on one another in multi-area layout is studied. In one scenario, the third area is equipped with battery and fuel cell to improve voltage deviation of itself (40.42%) as well as first and second area 12% and 15.4%, respectively.