With the gradual increase in load demand due to population and economic growth, integrating renewable energy sources (RES) into the grid represents a solution for meeting load demand. However, integrating RES might change the power system type from radial to non-radial, where the current can flow forward and backward. Consequently, power system analysis methods must be updated. The impact on power systems includes changes in the load flow affecting the voltage level, equipment sizing, operating modes, and power system protection. Conventional power system protection methods must be updated, as RES integration will change the power flow results and the short circuit levels in the power system. With an RES contribution to short circuit, existing settings might experience missed coordination which will result in unnecessary tripping. This paper considers the impact of integrating renewable energy sources into power system protection on overcurrent time delay settings. A new method to upgr... [more]

This paper proposes a smart system for managing the operations of grid-connected charging stations for electric vehicles (EV) that use photovoltaic (PV) sources. This system consists of a mobile application for EV drivers to make charging reservations, an algorithm to optimize the charging schedule, and a remote execution module of charging operations based on the open charge point protocol (OCPP). The optimal charging schedule was obtained by solving a binary integer programming problem. The merits of our solution are illustrated by simulating different charging demand scenarios.

Nowadays, the influences of the communication structure on the frequency regulation performance in a multi-area power system are barely studied. In this paper, a decentralized frequency regulation method for a multi-area power system considering optimization of communication structure is presented, and the influence of the communication structure on the frequency regulation performance is studied. Firstly, the communication network model is described and the multi-area power system model considering communication structure is presented. Then, the optimization model of communication structure during a decentralized frequency regulation process is constructed. This model aims to speed up the convergence speed of the control together with ensuring the high algebraic connectivity of the communication structure. Quantum binary particle swarm optimization (QB-PSO) algorithm is introduced to solve this model and, based on this, the communication structure optimization process and frequency re... [more]

This article is devoted to the development of technology for improving the efficiency of directional well drilling by predicting and adjusting the system of static and dynamic components of the actual weight on the bit, based on the real-time data interpretation from telemetry sensors of the bottom hole assembly (BHA). Studies of the petrophysical and geomechanical properties of rock samples were carried out. Based on fourth strength theory and the Palmgren−Miner fatigue stress theory, the mathematical model for prediction of effective distribution of mechanical specific energy, using machine learning methods while drilling, was developed. An algorithm was set for evaluation and estimation of effective destruction of rock by comparing petrophysical data in the well section and predicting the shock impulse of the bit. Based on the theory provided, it is assumed that the given shock impulse is an actual representation of an excessive energy, conveyed to BHA. This excessive energy was qua... [more]

The production of municipal waste is increasing all over the world. Although a significant part of the waste is collected as commingled waste, much of it is recyclable if disposed of properly. Thus, separate deposition and collection plays an extremely important role today, more than ever, not only in terms of preventing pollution but also from the point of view of recycling as a driver of circular economy and of efficient use of resources. This work is focused on the development of compaction equipment to be applied to containers, which allows a more efficient approach to the process of collecting waste for recycling. As a management option, recycling depends on collective behavior which is based on individual acts. Therefore, individual use of plastic/metal compaction systems can help meet recycling targets, even as a complement to conventional bins. Thus, herein a proposal is presented for a plastic/metal collection station with a built-in compaction element that allows for the comp... [more]

The compensating choke plays an important role in many high-power industrial applications with reactive power compensation. Due to the high number of devices installed every year and the EU’s efforts to reduce the energy demands of our society, it is advisable to maximize the efficiency of these devices. Due to the non-linearity of the magnetic core, the requirement of a linear operating characteristic, and the presence of a distributed air gap, this is a difficult task, with various technical challenges. This paper presents an analytical method for the electromagnetic design of a three-phase compensating choke with an air-gapped core and a flat load characteristic. The design method considers the fringing magnetic fields and the current-density dimensioning based on an advanced analytical thermal model. The proposed method is based on the use of existing analytical procedures; however, optimization was conducted to achieve a trade-off between the core and the I2R losses to manipulate... [more]

Wear debris in lubrication oil provides important information for marine engine condition monitoring and faults diagnosis. Inductive sensors have been widely used to detect wear debris in lubrication oil. To improve the sensitivity, the inductive coil is always connected with a capacitor in parallel to form parallel LC resonance-sensing circuit. A previous study optimized the parallel resonance circuit by adjusting the excitation frequency. However, multiple parameters (namely, excitation signal, signal detection circuits, and signal-processing program, etc.) need to be adjusted accordingly for a series of the testing frequencies. To simplify the optimization, we propose a method based on adjusting the parallel capacitance in this work. The impedance (inductance and internal resistance) of the sensing coil and its variation induced by particles are first measured, which are the necessary parameters for establishing the function relationship between the parallel capacitance and the rela... [more]

A brief review of the development of ideas on extremal principles in the theory of heat and mass transfer processes (including those in reacting media) is given. The extremal principles of non-equilibrium thermodynamics are critically examined. Examples are shown in which the mechanical use of entropy production-based principles turns out to be inefficient and even contradictory. The main problem of extremal principles in the theory of irreversible processes is the impossibility of their generalization, often even within the framework of a class of problems. Alternative extremal formulations are considered: variational principles for heat and mass transfer equations and other dissipative systems. Several extremal principles are singled out, which make it possible to simplify the numerical solution of the initial equations. Criteria are proposed that allow one to classify extremal principles according to their areas of applicability. Possible directions for further research in the searc... [more]

Solar air heater systems are equipment that uses energy captured directly from the sun to heat an existing airflow through the module. The technology to operate these systems is based on clean, renewable and free energy. Solar air heaters absorb thermal energy from the sun using an ab-sorption surface and achieve a transfer of heat from the absorption surface to the air flow supplied by one or two fans. This type of equipment can be used for space heating, drying, or ventilation processes. In addition, the equipment is capable of operating in cogeneration with other systems, e.g., preheating the air used for drying wood, preheating the air used to heat industrial premises, or preheating the water used in different heating systems. This scientific work is meant to reveal the current research context and the future opportunities in the case of cogeneration applications of solar air heaters, which are analyzed in light of their actual evolving dynamics. On this basis, we highlight expecta... [more]

In this paper, an optimal hybrid (wind and grid)-hydrogen energy system (H-HES) is proposed using multi-objective non-dominated sorting algorithm (NSGA-II) optimization. The H-HES consists of the main energy system; wind-energy system (W-ES), which supplies a proton exchange membrane (PEM) electrolyzer via an energy management system (EMS) and a rectifier. In addition, the grid-energy system (G-ES) is available to support the W-ES to meet the PEM electrolyzer’s energy demand, and the EMS facilitates control between the W-ES and G-ES. The W-ES is modelled using wind data from Wind Atlas South Africa (WASA) for six Renewable Energy Development Zones (REDZs) in South Africa and their appropriate wind turbine models. The selection of appropriate wind turbine models is guided by the optimal wind turbine variables obtained from NSGA-II corresponding to the optimal H-HES model. The optimal H-HES model is developed using two objective functions: cost of electricity and efficiency, which are mi... [more]

The main purpose of the work was examining various methods of decomposition of a network optimization problem of simultaneous routing and bandwidth allocation based on Lagrangian relaxation. The problem studied is an NP-hard mixed-integer nonlinear optimization problem. Multiple formulations of the optimization problem are proposed for the problem decomposition. The decomposition methods used several problem formulations and different choices of the dualized constraints. A simple gradient coordination algorithm, cutting-plane coordination algorithm, and their more sophisticated variants were used to solve dual problems. The performance of the proposed decomposition methods was compared to the commercial solver CPLEX and a heuristic algorithm.

In this research, the advantages of the e-scooter tool used in the mail or package delivery process were discussed by considering the Turkish Post Office (PTT) data in the districts of Istanbul (Kadıköy, Üsküdar, Kartal, and Maltepe) in Turkey. The optimization Poisson regression model was utilized to deliver the maximum number of packages or mails with minimum cost and the shortest time in terms of energy consumption, cost, and environmental contribution. Statistical and optimization results of dependent and independent variables were calculated using numerical and categorical features of 100 e-scooter drivers. The Poisson regression analysis determined that the e-scooter driver’s gender (p|0.05 < 0.199) and age (p|0.05 < 0.679) factors were not effective on the dependent variable. We analysed that the experience in the profession (tenure), the size of the area responsible, and environmental factors is effective in the e-scooter distribution activity. The number of packages deli... [more]

There is a strong trend in the development of control systems for multi-rotor unmanned aerial vehicles (UAVs), where minimization of a control signal effort is conducted to extend the flight time. The aim of this article is to shed light on the problem of shaping control signals in terms of energy-optimal flights. The synthesis of a UAV autonomous control system with a brain emotional learning based intelligent controller (BELBIC) is presented. The BELBIC, based on information from the feedback loop of the reference signal tracking system, shows a high learning ability to develop an appropriate control action with low computational complexity. This extends the capabilities of commonly used fixed-value proportional−integral−derivative controllers in a simple but efficient manner. The problem of controller tuning is treated here as a problem of optimization of the cost function expressing control signal effort and maximum precision flight. The article introduces several techniques (bio-i... [more]

Slotting effect in electric machines reduces flux per pole that effect magnetic flux density distribution in the air gap which induces harmonics in magnetic flux density causing flux pulsation, that in turn generates dominant torque pulsation in the form of cogging torque and torque ripples. To overcome the abovesaid demerits, a novel outer rotor field-excited flux-switching machine (OR-FSFSM) with a combined semi-closed and open slots stator is proposed in this study. The developed OR-FEFSM offers a high-power factor, due to the utilization of the semi-closed slot for armature coils. The open slot stator structure was chosen for the field excitation coil, which effectively suppresses leakage reluctance that causes flux pulsation. Thus, the influence of torque ripples is reduced, and the average torque is improved. In order to investigate the effectiveness of the proposed OR-FEFSM, a detailed study of stator slot and rotor pole combinations are performed. Based on simplified mathematic... [more]

A variety of variables influence the optimal tilt angle of a PV panel, including the characteristics of the panel, the local seasonal weather variations, the number of daylight hours the panel is exposed to and the ambient temperature of the surroundings. In this study, the optimal PV tilt angle and maximum energy output of PV arrays was calculated for every county in the United States and compared against the practice of setting the PV tilt angle to be equivalent to the latitude angle of the PV geographic location. A PVWatts API, implemented through Python, was used in conjunction with the SciPy optimization package to find the optimal tilt angle for each county using a direct line search algorithm. Most counties (95.8%) showed a difference between the location latitude and the optimal tilt of more than one degree. Many counties showed a deviation of 2−6° lower than the location latitude. The variation of daylight hours had the largest influence on tilt angle and seasonal cloud cover... [more]

Population and economic growth, industrial activities, development of technology, and depletion of fossil fuels have all led to increasing energy demand. As a result, there is an increasing ambition towards implementation of sustainable energy sources. In this study, first, a review of the literature is conducted to learn about various methods and objectives for optimization of photovoltaic and thermal (PV/T) systems. Then, a case study is considered, and the seasonal and hourly solar radiation are studied. Further, two methods of multiobjective evolutionary algorithm based on decomposition (MOEA/D) and multiobjective particle swarm optimization (MOPSO) are compared. On this basis, the energy and exergy efficiencies are analyzed for a proposed PV/T system. The outcomes are validated by taking into account the previous studies, and a sufficient agreement is found indicating the validity and accuracy of the results. It is also found that the efficiency rates for both energy and exergy so... [more]

The resources of the earth are being consumed day by day with the increasing population and necessities of humankind in many areas, such as industrial applications and basic needs in houses, workplaces and transportation. As a consequence, careful usage of the energy sources and the conversed energy is of great importance in order to obtain sustainable development. Machining operations have a large percentage of all manufacturing methods in terms of depleted energy which gives them a high potential for reducing the total energy consumption. The approaches handled in the literature for the minimization of the consumed energy in the machining industry were considered in this study. While several machinability characteristics under different machining processes were investigated broadly in the context of composites and superalloys, the comparison of these systems has been given cursory attention in the current literature, specifically for cutting energy saving. The overall performance of... [more]

Integrating renewable energy sources (RESs) into modern electric power systems offers various techno-economic benefits. However, the inconsistent power profile of RES influences the power flow of the entire distribution network, so it is crucial to optimize the power flow in order to achieve stable and reliable operation. Therefore, this paper proposes a newly developed circle search algorithm (CSA) for the optimal solution of the probabilistic optimal power flow (OPF). Our research began with the development and evaluation of the proposed CSA. Firstly, we solved the OPF problem to achieve minimum generation fuel costs; this used the classical OPF. Then, the newly developed CSA method was used to deal with the probabilistic power flow problem effectively. The impact of the intermittency of solar and wind energy sources on the total generation costs was investigated. Variations in the system’s demands are also considered in the probabilistic OPF problem scenarios. The proposed method wa... [more]

Heating networks are highly relevant for the achievement of climate protection goals of urban energy systems. This is due to their high renewable energy potential combined with high plant efficiency and utilization rates. For the optimal integration and sector coupling of heating networks in holistic urban energy systems, open source energy system modeling tools are highly recommended. In this contribution, two open source approaches (the “Spreadsheet Energy System Model Generator”-integrated DHNx-Python module (DHNx/SESMG) and Thermos) are theoretically compared, and practically applied to a real-world energy system. Deviations within the results can be explained by incorrectly pre-defined parameters within Thermos and cannot be adjusted by the modeler. The simultaneity is underestimated in the case study by Thermos by more than 20%. This results in undersized heating plant capacities and a 50% higher number of buildings connected to the network. However, Thermos offers a higher end-u... [more]

By coordinating the operation of regionally interconnected virtual power plants (VPPs), the growing penetration problem of renewable energy sources (RESs) into the power system can be addressed. This study presents an interactive trading cooperation model of regionally interconnected VPPs using bilateral contracts. The proposed model maximizes overall electricity market social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). The focus of the proposed approach is to design and develop a parallel energy exchange cooperation model of interconnected VPPs, ensuring the operational efficiency and reliability of interconnected power systems over the planning horizon. Given that adjacent VPPs may have differences in their energy generation and usage patterns, a scenario tree method is used to model the uncertainties associated with solar irradiation and load demand. A case study of two interconnected VPPs is used, the operational scenario is designed, and t... [more]

The importance of integrating distributed generation (DG) units into the distribution network (DN) recently developed. To decrease power losses (PL), this article presents a meta-heuristic population-based tangent golden flower pollination algorithm (TGFPA) as an optimization technique for selecting the ideal site for DG. Furthermore, the proposed algorithm also finds the optimal routing configuration for power flow. TGFPA requires very few tuning parameters and is comprised of a golden section and a tangent flight algorithm (TFA). Hence, it is easy to update these parameters to obtain the best values, which provide highly reliable results compared to other existing techniques. In different case studies, the TGFPA’s performance was assessed on four test bus systems: IEEE 33-bus, IEEE 69-bus, IEEE 119-bus, and Indian-52 bus. According to simulation results, TGFPA computes the optimal reconfigured DN embedded along with DG, achieving the goal of minimal power loss.

Cloud computing provides a ubiquitous data storage and access mechanism for organizations, industries, and smart grids to facilitate their operations. However, the concern in cloud storage systems is to secure data access control toward authentication for sensitive data, such as the electric vehicles (EVs) requesting information for attending a charging service. Consequently, denying an authentic user’s request will result in delaying the requested service, thereby leading to service inefficiency. The role-based access control (RBAC) plays a crucial role in securing and authenticating such time-sensitive data. The design mechanism of roles is based on skills, authority, and responsibilities for organizations. For EVs, the roles are based on the type of membership, such as permanent, occasional, or one-time. In this paper, we propose a new RBAC access control and privacy-preserving information access method toward the coarse-grained measure control and privacy protection in the cloud st... [more]

In this article, a dual-stage proportional integral−proportional derivative with filter (PI−PDF) controller has been proposed for a hybrid two-area power system model having thermal-, hydro-, gas-, wind-, and solar-based power generating sources. Superconductor magnetic energy storage (SMES) units to cope with the transient power deviations have been incorporated in both areas. Governor dead-band (GDB) is considered in the governor model of thermal, and a generation rate constraint (GRC) is considered in the thermal and hydro turbine models to analyze the impact of system nonlinearity. The parameters of the proposed control strategy are optimally tuned by deploying a newly developed bull−lion optimization (BLO) to maintain optimal frequency and power response during system load deviations. Variations in wind speed and PV solar irradiance data have been included to examine the effectiveness of the BLO-based PI−PDF controller with system uncertainties and variability of renewable energy... [more]

A novel combined power and refrigeration system is proposed based on organic Rankine and jet refrigeration cycles. The system has a wider application range and can be adjusted to different cooling and evaporation temperatures. To meet the needs of diverse populations, the cooling and evaporation temperature can be as low as −60 degrees Celsius. The genetic algorithm is used to optimize the system, and the proposed system’s energy, exergy, economy, and environment are analyzed under optimal conditions. The results desmonstrate that the exergy damage, environmental impact rate, and exergy economic coefficient of steam turbine are the largest. The system’s exergy damage and the turbine’s investment cost are reduced, and the system’s performance is improved. The condenser has the greatest potential for improvement and should be considered a priority component for system improvement. In addition, the system parameters are analyzed. Higher low-pressure steam generation temperature, dryness o... [more]

Energy has become the most expensive and critical resource for all kinds of human activities. At the same time, all areas of our lives strongly depend on Information and Communication Technologies (ICT). It is not surprising that energy efficiency has become an issue in developing and running ICT systems. This paper presents a survey of the optimization models developed in order to reduce energy consumption by ICT systems. Two main approaches are presented, showing the trade-off between energy consumption and quality of service (QoS).