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]

The presented work employs the multiple random feature kernel mean p-power algorithm (MRFKMP) for the voltage source converter (VSC) control of a three-phase four-wire grid-tied dual-stage photovoltaic-hybrid energy storage system (HESS) to achieve multiple objectives during various induced dynamic conditions. The proposed control enables the VSC to accomplish manifold goals, i.e., reactive power compensation, power quality enhancement, load, power balancing at common coupling point and grid voltage balancing during unity power factor mode of operation. The proposed system is scrutinized under steady-state and numerous dynamic states such as irradiation variation, specified power mode, abnormal grid voltage, load, and grid voltage unbalancing. The seamless control facilitates the swift resynchronization of the grid as well as maintaining stability during islanding and re-synchronization operations while satisfying the necessary load requirements. The associated HESS consisting of batte... [more]

The underground coal gasification (UCG) represents an effective coal mining technology, where coal is transformed into syngas underground. Extracted syngas is cleaned and processed for energy production. Various gasification agents can be injected into an underground georeactor, e.g., air, technical oxygen, or water steam, to ensure necessary temperature and produce syngas with the highest possible calorific value. This paper presents an experimental study where dynamic optimization of operating variables maximizes syngas calorific value during gasification. Several experiments performed on an ex situ reactor show that the optimization algorithm increased syngas calorific value. Three operation variables, i.e., airflow, oxygen flow, and syngas exhaust, were continually optimized by an algorithm of gradient method. By optimizing the manipulation variables, the calorific value of the syngas was increased by 5 MJ/m3, both in gasification with air and additional oxygen. Furthermore, a high... [more]

The topic of microgrids (MGs) is a fast-growing and very promising field of research in terms of energy production quality, pollution reduction and sustainable development. Moreover, MGs are, above all, designed to considerably improve the autonomy, sustainability, and reliability of future electrical distribution grid. At the same time, aspects of MGs energy management, taking into consideration distribution generation systems, energy storage devices, electric vehicles, and consumption components have been widely investigated. Besides, grid architectures including DC, AC, or hybrid power generation systems, energy dispatching problems modelling, operating modes (islanded or grid connected), MGs sizing, simulations and problems solving optimization approaches, and other aspects, have been raised as topics of great interest for both electrical and computer sciences research communities. Furthermore, the United Nations Framework Convention on Climate Change and government policies and in... [more]

Battery electric vehicles offer many advantages in terms of performance and zero-emission pollutants, but their limited range for long-distance trips compromises their large-scale market penetration. The problem of range can be solved with a dense network of fast-charging stations and an increase in embedded battery capacity. Simultaneously, improvements in high-power charging point units offer range gains of hundreds of kilometers in a mere 20 min. One risk remains: The travel time depends on the availability of charging stations, which can drop during rush hours, due to long queues, or power grid constraints. These situations could significantly affect the user experience. In this paper, we presented an approach to coordinate EV charging station choices in the case of long-distance trips. This system relies on vehicle-to-infrastructure communications (V2X). The objective is to enhance the use of the infrastructure by improving the distribution of vehicles between the different chargi... [more]

Rotary heat exchangers have been widely used in paint shops, combustion power plants, and in heating, ventilation, and air conditioning systems in buildings. For these processes, many types of heat exchangers are available in the market: Tube-shell heat exchangers, plate heat exchangers, and rotary heat exchangers, among others. For the rotary heat exchangers, the problem is that there is no net present value method and lifecycle assessment method-based optimization found in the literature. In this work, we address this issue: An optimization is carried out with help of an empirically validated simulation model, a life-cycle assessment model, an economical assessment, and an optimization algorithm. The objective function of the optimization simultaneously considers economic and environmental aspects by using different CO2 pricing. Different CO2 pricing scenarios lead to different optimization results. The ambient air empty tube velocity va, 2.1 optimum was found at 1.2 m/s, which... [more]

This article discusses the optimization of railway transition curves, through the application of polynomials of 9th and 11th degrees. In this work, the authors use a 2-axle rail vehicle model combined with mathematically understood optimization methods. This model is used to simulate rail vehicle movement negotiating both a transition curve and circular arc. Passenger comfort is applied as the criterion to assess which transition is actually is the best one. The 4-axle vehicle was also used to verify the results obtained using the 2-axle vehicle. Our results show that the traditionally used in a railway engineering transition—3rd degree parabola—which is not always the optimum curve. This fact is especially valid for the longest curves, with lengths greater than 150 m. For such cases, the transition curves similar to standard curves of 9th and 11th degrees is the optimum ones. This result is confirmed by the use of the 4-axle vehicle.