Partial shading (PS) is a prevalent phenomenon that often affects photovoltaic (PV) installations, leads to the appearance of numerous peaks in the power-voltage characteristics of PV cells, caused by the uneven distribution of solar irradiance on the PV module surface, known as global and local maximum power point (GMPP and LMPP). In this paper, a new technique for achieving GMPP based on the dandelion optimizer (DO) algorithm is proposed, inspired by the movement of dandelion seeds in the wind. The proposed technique aimed to enhance the efficiency of power generation in PV systems, particularly under PS conditions. However, the DO-based MPPT is compared with other advanced maximum power point tracker (MPPT) algorithms, such as Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Artificial Bee Colony (ABC), Cuckoo Search Algorithm (CSA), and Bat Algorithm (BA). Simulation results establish the superiority and effectiveness of the used MPPT in terms of tracking efficiency... [more]

The Habanero pepper (Capsicum chinense Jacq.) is recognized worldwide for its unique organoleptic characteristics, as well as for its capsaicin content; however, other bioactive compounds, such as phenolic compounds with bioactive properties (mainly antioxidant capacity), have been extracted (ultrasound) and identified in this fruit. Moreover, the extracts obtained by ultrasound present a high sensitivity to environmental conditions, making spray drying a viable option to avoid the degradation of bioactive compounds while maintaining their properties after microencapsulation. Response surface methodology (RSM) has been used to optimize spray-drying conditions such as the inlet temperature (IT) and maltodextrin:extract (M:E) ratio. Thus, the objective of this work was to establish the optimal spray-drying conditions (IT and M:E) of a Habanero pepper extract with a final characterization of the spray-dried product. Results showed that the optimal spray-drying conditions included an IT =... [more]

Chinalco’s Toromocho mine, located in the Morococha district of Peru, treated 117,200 mtpd ores during last 10 years. It is currently undergoing expansion, treating approximately 52,740 mtpd of chalcopyrite ore since 2021. As with the commissioning of most large plants, the metallurgical performance levels produced after stability was achieved were below the design criteria; more specifically, the Cu overall recoveries were 80−82% compared with the design value of 85%, and the final concentrate Cu grades were 20−23% compared with the design value of 24% over the past 2 years. It is clear that the copper losses in the fine size fraction (<10 µm) were due to unoptimized hydrodynamics. To overcome this obstacle and improve overall performance, an innovative approach for flotation circuit evaluation was designed and set up, to improve understanding of the nature of the mineral losses, benchmark the cell hydrodynamics as a platform to improve flotation cell operation, and link the circui... [more]

Curved bladelets on wind turbine blades play an important role in improving the performance and efficiency of wind turbines. Implementing such features on the tip of wind turbine blades can improve their overall aerodynamic characteristics by reducing turbulence and loading without hindering lift generation and overall efficiency, thus leading to increased energy capture and reduced costs over the life of the turbine. Subjecting the integrated blade tip to optimization procedures can maximize its beneficial contribution to the assembly in general. Within this context, a systemic workflow is proposed for the optimization of a curved bladelet implemented on a wind turbine blade. The approach receives input in the form of an initial tip geometry and performs improvements in two distinct stages. Firstly, shape optimization is performed directly on the outer shape to enhance its aerodynamic properties. Subsequently, the topology of its interior structure is refined to decrease its mass whil... [more]

Water-soluble polymers are becoming increasingly important in various applications, such as stabilizer fluids and drilling muds. These materials are used as viscosifiers and filtration control agents, flocculants, and deflocculants due to their superior properties in increasing viscosity and gelling ability in the presence of crosslinkers. In general, studying the rheological behavior of drilling fluids is of paramount importance to ensure successful well drilling operations. Partially hydrolyzed polyacrylamide is one of the polymers widely used in water-based muds. The main objective of this study is to optimize the rheological properties of drilling muds through a characterization study of various parameters, including rheological behavior, viscosity, temperature (23 °C, 40 °C, and 60 °C), salinity using KCl and NaCl contents, aging, pH, solubility, and structural analysis using infrared of partially hydrolyzed polyacrylamide. The study aims to demonstrate the importance of using pol... [more]

This paper is concerned with the design and structural optimization of a training device for operators of a hydraulic rescue tool employed during traffic accidents, in conjunction with the improvement of the technical procedures used in such situations. Changes in the design process and subsequent production in the motor industry frequently result in an increased impact resistance of the used structural components. This applies, also, to extrication works and frequently used technical equipment. This paper presents its findings on the design process for the prototype of a training device designed for the extrication cutting drill with the assistance of a hydraulic rescue tool. The primary part of the research was dedicated to structural optimization; therefore, parameter dimensioning of the training device’s prototype was implemented. The device’s mechanical resistance, sturdiness, and stability during the implementation of hydraulic tools were also taken into account. A secondary part... [more]

A new Group Contribution Method based on elements and chemical bonds was proposed to predict the enthalpy of evaporation of organic compounds at their normal boiling points. A prediction model was built using 1266 experimental data points, and the accuracy of the model estimations was evaluated using 16 experimental data points. The new method has only 42 groups, a simple way of group splitting, and a wide range of predictions with an average relative error of 5.84%. Furthermore, the inclusion of silicon elements and their chemical bonds in the group library enables the effective prediction of silicon-containing compounds with an average relative error of 2.71%. By analyzing and comparing the other three commonly used methods, it can be concluded that the new method provides accurate and reliable estimation results and has a more comprehensive application range.

Improving the separation efficiency of the layer melt crystallization process is a key but difficult task. Herein, a comprehensive model involving both crystallization and sweating was proposed and used to optimize the operating time of crystallization and sweating processes. The crystallization process was modeled based on the relationship between differential and integral distribution coefficients under a constant layer growth rate. For the sweating process, an empirical sweating equation was employed to govern the sweating model, the parameters of which were determined experimentally using P-xylene as the model substance. The separation efficiency was then optimized by minimizing the operating time at a given product purity and yield. A sensitivity analysis showed that the crystallization and sweating times nonlinearly increase with increasing yield. After the yield exceeds 0.65, an increasing crystallization time is the dominant factor in improving the separation efficiency, while... [more]

The increasing demand for electricity and the need for environmentally friendly transportation systems has resulted in the proliferation of solar photovoltaic (PV) generators and electric vehicle (EV) charging within the low voltage (LV) distribution network. This high penetration of PV and EV charging can cause power quality challenges, hence the need for hosting capacity (HC) studies to estimate the maximum allowable connections. Although studies and reviews are abundant on the HC of PV and EV charging available in the literature, there is a lack of reviews on HC studies that cover both PV and EVs together. This paper fills this research gap by providing a detailed review of five commonly used methods for quantifying HC including deterministic, time series, stochastic, optimization, and streamlined methods. This paper comprehensively reviews the HC concept, methods, and tools, covering both PV and EV charging based on a survey of state-of-the-art literature published within the last... [more]

Integrated solar combined cycle (ISCC) systems play a pivotal role in the utilization of non-fossil energy; however, the efficient application of solar energy has emerged as a primary issue in the study of ISCC systems. Therefore, it is extremely urgent to propose the best optimization scheme for ISCC under different operating conditions. In this paper, according to the idea of temperature matching and cascade utilization, the optimization of the ISCC system is carried out with the genetic algorithm for the whole working conditions, and the optimization schemes with the highest photoelectric efficiency and system efficiency under different working conditions are derived. In comparison with two optimization schemes with different objective functions, the conclusion can be drawn that: At 100% gas turbine load—30% DNI and 100% gas turbine load—100% DNI working conditions, respectively, the maximum system efficiency of 56.32% and the maximum solar photoelectric efficiency of 35.5% are atta... [more]

In the global trend towards decarbonization, peer-to-peer (P2P) energy trading is garnering increasing attention. Furthermore, energy management on the demand side plays a crucial role in decarbonization efforts. The authors have previously developed an automated bidding agent that considers user preferences for renewable energy (RE), assuming users own electric vehicles (EVs). In this study, we expand upon this work by considering users who own not only EVs but also heat pump water heaters, and we develop an automated bidding agent that takes into account their preferences for RE. We propose a method to control the start time and presence of daytime operation shifts for heat pump water heaters, leveraging their daytime operation shift function. Demonstration experiments were conducted to effectively control devices such as EVs and heat pumps using the agent. The results of the experiments revealed that by controlling the daytime operation of heat pumps with our method, the RE utilizat... [more]

Underground coal gasification (UCG) is a clean coal mining technology without significant environmental impacts. This technology can also be used in deep, hard-to-reach seams or deposits affected by tectonic disturbances, where conventional mining is impossible. Several techniques and methods have been investigated worldwide to support the process control of UCG. Global research focuses on the control of UCG operating parameters to stabilize or to optimize the performance of the underground reactor during energy conversion. This paper studies recent research in the field of UCG control and compares individual control techniques and possibilities for practical application. The paper focuses on advanced control methods that can be implemented in an in situ control system (e.g., adaptive control, extremum seeking control, and robust control). The study investigates control methods that ensure desired syngas calorific value or maximization. The review showed that robust control techniques... [more]

Microgrid technology has recently gained global attention over increasing demands for the inclusion of renewable energy resources in power grids, requiring constant research and development in aspects such as control, protection, reliability, and management. With an ever-increasing scope for maximizing renewable energy output, there is also a need to reduce the curtailment of power on both the generation and demand sides by increasing forecasting accuracies and using resources more effectively. This paper proposes a dual-stage dispatch employing a novel “split-horizon” strategy, in a bid to enhance energy management in a standalone microgrid. The split-horizon is essentially the considered time horizon split into equal operational periods of the dual-stage dispatch. The proposed strategy utilizes a custom-designed novel variant of the inertia-weight-based particle swarm optimization (PSO), termed customized PSO, to perform the optimal schedule and dispatch operation by benefitting from... [more]

Hydropower is the most prevalent source of renewable energy production worldwide. As the global demand for robust and ecologically sustainable energy production increases, developing and enhancing the current energy production processes is essential. In the past decade, machine learning has contributed significantly to various fields, and hydropower is no exception. All three horizons of hydropower models could benefit from machine learning: short-term, medium-term, and long-term. Currently, dynamic programming is used in the majority of hydropower scheduling models. In this paper, we review the present state of the hydropower scheduling problem as well as the development of machine learning as a type of optimization problem and prediction tool. To the best of our knowledge, this is the first survey article that provides a comprehensive overview of machine learning and artificial intelligence applications in the hydroelectric power industry for scheduling, optimization, and prediction.

The integration of distributed generation (DG) into the power grid has increased in recent years due to its techno-economic benefits for utilities and consumers. However, due to the fact that distribution systems were not originally designed to accommodate such DG units, many challenges are being faced by utilities to seamlessly integrate them into their systems. One of the critical challenges is their effect on protection system settings and coordination. The DG units will affect the pickup current settings of the protection relays, coordination between the primary and secondary relays, and even the direction of the fault current. Failing to consider DG’s effect on the protection system may lead to serious equipment damage or system failure, causing huge financial setbacks for utilities. To that end, this work proposes a new dynamic approach to optimally allocate different types of DG units over the planning horizon. The objective is to minimize the overall costs of the system while t... [more]

This study focuses on the determination of optimum layout configurations for a linear array of identical mutually interacting truncated cylinders. Optimum configurations correspond to those that maximize either the total heave exciting force acting on all cylinders of the array or the heave exciting force applied on pairs of cylinders within the array. For achieving this goal, we developed and applied an efficient optimization numerical process (ONP), where a robust hydrodynamic numerical model, capable of solving the diffraction problem of the examined multi-body arrangement in the frequency domain, was appropriately coupled with a genetic algorithm solver in an integrated computational environment. Initially, the efficiency of the ONP is demonstrated by comparing results with those of other investigations that resulted from the deployment of classical optimization methods. Then, ONP is applied for a linear array of nine cylinders for determining the optimum layout configurations unde... [more]

This paper investigates the influence of a stochastic variation of both energy and economic parameters in an optimization loop applied to a refurbished social housing building. Usually, energy and economic optimization procedures rely on the results of an underlying numerical deterministic model which influences both energy gains and economic figures. However, an analyst must always face the random variation of input and parameter data. The unknown data can represent poor initial information or data that can change in a long time; this is the case of fuel cost and economic indexes in particular. This paper deals with both problems for building refurbishment optimization, the former related to the initial state of a building, and the latter to the energy cost variability. Reliability analysis considers a stochastic variation of parameters looking for solutions that incorporate a risk level; in this case, it deals with optimization objectives related to different impacts on economic, env... [more]

This paper proposes a method to improve the performance of a distribution system by optimizing volt−var function of a smart inverter to alleviate the voltage deviation problem due to distributed generation connection. In order to minimize voltage deviation and line losses which represent the performance of a distribution system, this paper proposes an algorithm that optimally sets the parameters of the volt−var function. In the process of optimizing the parameters of the volt−var function, the algorithm proposed in this paper considers minimizing the contribution of the reactive power in order not to affect the output of the distributed generation. In order to apply to the field, the distribution system in South Korea considering the configuration and operation regulation was selected as a test model for algorithm verification. As a result, the system performance was successfully improved by optimally setting the volt−var function of the smart inverter which is an effective way to solv... [more]

The performance of a wind turbine is affected by wind conditions and blade shape. This study aimed to optimize the performance of a 20 kW horizontal-axis wind turbine (HAWT) under local wind conditions at Deniliquin, New South Wales, Australia. Ansys Fluent (version 18.2, Canonsburg, PA, USA) was used to investigate the aerodynamic performance of the HAWT. The effects of four Reynolds-averaged Navier−Stokes turbulence models on predicting the flows under separation condition were examined. The transition SST model had the best agreement with the NREL CER data. Then, the aerodynamic shape of the rotor was optimized to maximize the annual energy production (AEP) in the Deniliquin region. Statistical wind analysis was applied to define the Weibull function and scale parameters which were 2.096 and 5.042 m/s, respectively. The HARP_Opt (National Renewable Energy Laboratory, Golden, CO, USA) was enhanced with design variables concerning the shape of the blade, rated rotational speed, and pi... [more]

Pump-as-turbine (PAT) technology permits two operating states—as a pump or turbine, depending on the demand. Nevertheless, designing the geometrical components to suit these operating states has been an unending design issue, because of the multi-conditions for the PAT technology that must be attained to enhance the hydraulic performance. Also, PAT has been known to have a narrow operating range and operates poorly at off-design conditions, due to the lack of flow control device and poor geometrical designs. Therefore, for the PAT to have a wider operating range and operate effectively at off-design conditions, the geometric parameters need to be optimized. Since it is practically impossible to optimize more than one objective function at the same time, a suitable surrogate model is needed to mimic the objective functions for it to be solvable. In this study, the Latin hypercube sampling method was used to obtain the objective function values, the Adaptive Neuro-Fuzzy Inference System... [more]

The restructuring of power systems and the ever-increasing demand for electricity have given rise to congestion in power networks. The use of distributed generators (DGs) may play a significant role in tackling such issues. DGs may be integrated with electrical power networks to regulate the drift of power in the transmission lines, thereby increasing the power transfer capabilities of lines and improving the overall performance of electrical networks. In this article, an effective method based on the Harris hawks optimization (HHO) algorithm is used to select the optimum capacity, number, and site of solar-based DGs to reduce real power losses and voltage deviation. The proposed HHO has been tested with a complex benchmark function then applied to the IEEE 33 and IEEE 69 bus radial distribution systems. The single and multiple solar-based DGs are optimized for the optimum size and site with a unity power factor. It is observed that the overall performance of the systems is enhanced wh... [more]

A microgrid is a set of decentralized loads and electricity sources, mainly renewable. It can operate connected to and synchronized with a traditional wide-area synchronous grid, i.e., a macrogrid, but can also be disconnected to operate in “island mode” or “isolated mode”. When this microgrid is able to manage its own resources and loads through the use of smart meters, smart appliances, control systems, and the like, it is referred to as a smart grid. Therefore, the management and the distribution of the energy inside the microgrid is an important issue, especially when operating in isolated mode. This work presents an overview of the different solutions that have been tested during the last few years to manage microgrids. The review shows the variety of mature and tested solutions for managing microgrids with different configurations and under several approaches.

A successful transformation of the energy and transportation sector is one of the main targets for our society today. Battery electric vehicles can play a key role in future renewable-based energy supply systems because of their ability to store electrical power. Additionally, they provide significant charging flexibility due to the long parking durations. In this paper, we provide insights into the temporal and power-specific flexibility behavior of three different vehicle fleets. These fleets are pool vehicles of office employees, a public authority, and a logistics company. Several parameters, such as the average charging power per charging event or the average plug-in duration per charging event, are discussed. Additionally, we investigate different charging rates and their impact on the temporal flexibility of the charging events. The data analysis shows that the logistics site has the most homogeneous charging profile as well as high charging flexibility, in contrast to the offic... [more]

Solar energy is currently dispatched ahead of other renewable energy sources. For the first time, this study presents a concept of exploiting temporary−periodical runoff discharge in the Shire River. Pumped hydro storage−photovoltaic plant (PHS−PV) was optimized to satisfy the all-day peak electricity demand in Malawi. The effect of varying the net head on the PHS system in both the generation and pumping operation modes was investigated. The bi-objective optimization evaluated the system reliability for day-time and night-time operation together with implied costs of investment for the whole system. The optimized system generated above 53% of added power as contrasted to single-source power generation from the existing hydropower plants. The estimated optimal capacities were 182 MWp (solar PV) and 86 MW (PHS plant). These additional optimal capacities achieved a 99.8% maximum system reliability (Loss of Power Supply Probability—LPSP—of 0.2%) and Levelized Cost of Energy—LCOE—of 0.13 U... [more]

The optimal design of the thrust vector control system of solid rocket motors (SRMs) is discussed. The injection of a supersonic underexpanded gas jet into the diverging part of the rocket engine nozzle is considered, and multiparameter optimization of the geometric shape of the injection nozzle and the parameters of jet injection into a supersonic flow is developed. The turbulent flow of viscous compressible gas in the main nozzle and injection system is simulated with the Reynolds-averaged Navier−Stokes (RANS) equations and shear stress transport (SST) turbulence model. An optimization procedure with the automatic generation of a block-structured mesh and conjugate gradient method is applied to find the optimal parameters of the problem of interest. Optimization parameters include the pressure ratio of the injected jet, the angle of inclination of the injection nozzle to the axis of the main nozzle, the distance of the injection nozzle from the throat of the main nozzle and the shape... [more]