With the participation of wind power in grid frequency modulation, the fatigue load of the wind turbine increases accordingly. A new control method that considers both fatigue load and output power of wind turbine (WT) is proposed in this paper. A linear active disturbance rejection control (LADRC) is designed and applied for the pitch angle in the wind turbine load reduction control. The particle swarm optimization (PSO) algorithm is used to optimize the parameters of the wind turbine controller, and the total variation of the wind turbine shaft torque and tower bending moment is added to construct a new objective function to further reduce the fatigue load of the wind turbine. The design-optimized controller is validated on a 5 MW wind turbine in SimWindFarm. The simulation results show that the LADRC controller can accurately track the reference power of the wind turbine, reduce the pitch angle fluctuation of the wind turbine, reduce the fatigue load of the wind turbine, and improve... [more]

There were many promising superconducting materials discovered in the last decades that can significantly increase the efficiency of large power transformers. However, these large machines are generally custom-made and tailored to the given application. During the design process the most economical design should be selected from thousands of applicable solutions in a short design period. Due to the nonlinearity of the task, the cost-optimal transformer design, which has the smallest costs during the transformers’ planned lifetime, is usually not the design with the highest efficiency. Due to the topic’s importance, many simplified transformer models were published in the literature to resolve this problem. However, only a few papers considered this preliminary design optimization problem in the case of superconducting transformers and none of them made a comparison with a validated conventional transformer optimization model. This paper proposes a novel FEM-based two-winding transforme... [more]

A power system’s nonlinearity and complexity increase from time to time due to increases of power demand. Therefore, properly designed power system controlsare required. Without these, system instability will cause equipment failures, and possibly even cascading events and blackouts. To cope with this, intelligent controllers using soft computing are necessary for real time operation. In this paper, the reheat type three-area thermal power system is considered, and the output scaling factors, gain parameters of fuzzy membership functions, and parameters of fuzzy-proportional integral derivative (FPID) controllers are optimized using a differential evolution (DE) optimization techniqueand integral time multiplied absolute error (ITAE) as objective functions. To improve the limitations of the controller and to enhance stability of the system, high voltage direct current (HVDC) technology is advantageous due to its quickresponse capabilities. In this paper, a HVDC is connected in parallel... [more]

Renewable energy transition creates unprecedented issues in power system control, operation and protection [...]

Harmonic pollution sources in microgrids have the characteristics of high penetration and decentralization, as well as forming a full network. Local harmonic mitigation is a traditional harmonic mitigation method, which has the disadvantages of complexity and costly operation. Based on the idea of the decentralized autonomy of power quality, this paper establishes a comprehensive optimization model of the active power and harmonic mitigation capacities of grid-connected inverters based on two-layer optimization and realizes harmonic mitigation. Firstly, based on the harmonic sensitivity analysis, the calculation method of harmonic mitigation capacity is given. Secondly, a two-layer model of harmonic mitigation optimization is established. The upper-layer optimization model takes the minimum operation cost of the microgrid as the objective and the active power reduction in the multi-functional grid-connected inverter (MFGCI) as the optimization variable. The lower-layer optimization mod... [more]

This study presents the optimization of a multilayer wire-on-tube condenser exposed to forced convection, using the Optimized Multi-objective Particle Swarm Optimization (OMOPSO) algorithm. The maximization of the heat transfer and the minimization of the heat exchange area were defined as objective functions. In the optimization process, the variations of eight geometric parameters of the condenser were analyzed, and the Multi-objective Evolutionary Algorithm based on Decomposition (MOEAD), Non-dominated Sorting Genetic Algorithm-II (NSGAII), and OMOPSO algorithms were statistically explored. Furthermore, the condenser optimization analysis was extended to the use of alternative refrigerants to R134a such as R600a and R513A. Among the relevant results, it can be commented that the OMOPSO algorithm presented the best option from the statistical point of view compared to the other two algorithms. Thus, optimal designs for the wire-on-tube condenser were defined for three proposed study... [more]

The operation of the photovoltaic (PV) system under partial shading conditions (PSC) is complicated since the output characteristic of the PV system is profoundly affected by the heterogeneous irradiance of PSC. This paper proposes a dynamic reconfiguration framework to tackle PSC in the PV array. Continuous operation of the dynamic PV array reconfiguration under cloud-induced partial shading is considered by developing an emulator of the moving cloud. In addition, the Particle Swarm Optimization and Rao algorithms are improved to obtain the optimal PV array configuration under PSC. The operation of switching is enhanced by simultaneously considering the total switching times and the operation of highly active switches. The simulation results on the 9×9 PV array demonstrate the effectiveness of the proposed framework in terms of reducing the number of local maximum power points on the power-voltage characteristic, enhancing power output, and relieving stress on the switching operation... [more]

Although the proportional integral derivative (PID) is a well-known control technique applied to many applications, it has performance limitations compared to nonlinear controllers. GAPID (Gaussian Adaptive PID) is a non-linear adaptive control technique that achieves considerably better performance by using optimization techniques to determine its nine parameters instead of deterministic methods. GAPID represents a multimodal problem, which opens up the possibility of having several distinct near-optimal solutions, which is a complex task to solve. The objective of this article is to examine the behavior of many optimization algorithms in solving this problem. Then, 10 variations of bio-inspired metaheuristic strategies based on Genetic Algorithms (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO) are selected to optimize the GAPID control of a Buck DC−DC converter. The computational results reveal that, in general, the variants implemented for PSO and DE present... [more]

Among the numerous renewable energy resources, the main advantage of water energy is that it utilizes the current of the streams and rivers regardless of the given time of the day or season. The main purpose of this study was to create a low capacity, floating hydropower plant that is suitable for shallow and even narrow water bodies. The device was designed to create electric energy while floating on the water’s surface; therefore, it can be used not only in natural streams but also in drainage channels and wastewater treatment plants. The prototype was tested under real circumstances to identify the impacts of various settings on the energy efficiency. Measurements were conducted in Veszprém, Hungary on the Brook Séd. The average depth of the riverbed was 36 cm. Based on the field measurements, optimal efficiency was achieved by using six paddles. On the other hand, much lower efficiency was achieved when low (two or three) or high numbers (12 or 15) of paddles were used. A design fr... [more]

Diesel engines are widely used in agricultural tractors. During field operations, the tractors operate at low speed and high load for a long time, the fuel efficiency is only about 15% to 35%, and the exhaust waste heat accounts for 38% to 45% of the energy released from the fuel. The use of tractor exhaust waste heat can effectively reduce fuel consumption and pollutant emissions, of which the organic Rankine cycle (ORC)-based waste heat recovery conversion efficiency is the highest. First, the diesel engine map is achieved through the test rig, a plate-fin evaporator is trial-produced based on the tractor size, and the thermodynamic and economic performance model of the ORC are established. Then, taking the thermal efficiency of ORC and the specific investment cost (SIC) as the objective function, the particle swarm optimization (PSO) algorithm and the technique for order of preference by similarity to ideal solution (TOPSIS) decision method were used to obtain the optimal operating... [more]

This paper presents the integrated optimal design of the powertrain of a hybrid regional aircraft using multidisciplinary design optimization (MDO). The sizing of the main components of the propulsion chain is performed over the flight mission under various scenarios regarding energy management strategies and technological assessments. For that purpose, a complete set of multidisciplinary surrogate models are integrated into the MDO process, taking account not only of the main electrical, thermal and mechanical aspects but also of environmental constraints such as partial discharges in electric motors regarding flight conditions. Several MDO formulations are investigated comparing local (i.e., motor mass minimization) and global optimizations (i.e., powertrain mass then fuel burn minimization at aircraft level). Results emphasize main systemic couplings showing that despite future technological progress, the series hybrid architecture is heavier than a conventional thermal aircraft. Ne... [more]

This paper proposes an effective approach to solve renewable distributed generators (RDGs) and electric vehicle charging station (EVCS) allocation problems in the distribution system (DS) to reduce power loss (PLoss) and enhance voltage profile. The RDGs considered for this work are solar, wind and fuel cell. The uncertainties related to RDGs are modelled using probability distribution functions (PDF). These sources’ best locations and sizes are identified by the voltage stability index (VSI) and political optimization algorithm (POA). Furthermore, EV charging strategies such as the conventional charging method (CCM) and optimized charging method (OCM) are considered to study the method’s efficacy. The developed approach is studied on Indian 28 bus DS. Different cases are considered, such as a single DG, multiple DGs and a combination of DGs and EVs. This placement of multiple DGs along with EVs, considering proper scheduling patterns, minimizes PLoss and considerably improves the volt... [more]

In this paper, a novel one-way single-wire power transfer structure is proposed. Different from the traditional single-wire power transfer system, power is one-way transmitted from the power source to the load, and no loop is constituted. The structure of one-way single-wire power transfer is studied in detail, and the influences of its length and shapes on the transmission efficiency are determined. Research shows that the length of the receiving structure plays a key role in improving the system’s efficiency, while the transmitting structure has a little effect. Based on ensuring transmission efficiency, the space volume optimization method is further applied. The expression of electromagnetic field distribution is derived theoretically, and the proposed structure is verified by simulation and experimental results.

This study selects five parameters as decision variables for the optimization design of an ocean thermal energy conversion system, including the evaporating temperature, the condensing temperature, the pinch-point temperature difference between the evaporator and condenser, and the working fluid flow rate. The optimization goal is to maximize the net output power per unit area and the exergy efficiency. The final scheme is comprehensively screened out from the Pareto solution set through some evaluation indexes. Finally, this study also analyzes the effects of four decision variables on the optimization objectives and the evaluation indexes. This study finds that evaporating temperature and condensing temperature have similar effects on the two objective functions. However, the pinch-point temperature difference has different effects on them. The back work ratio is obviously affected by the condensing temperature. A small pinch-point temperature difference is beneficial and improves th... [more]

The importance of energy harvesting is considered when harvesting the neglected ambient energy that graduated from different systems and dissipates around us, such as electromagnetic waves, heat, vibration, etc [...]

The optimal operation of District Heating Networks (DHNs) is a challenging task. Current or future optimal dispatch energy management systems attempt to optimize objectives, such as monetary cost minimization, emission reduction, or social welfare maximization. Typically, this requires highly nonlinear models and has a substantial computational cost, especially for large DHNs. Consequently, it is difficult to solve the resulting nonlinear programming problem in real time. In particular, as typical applications allow for no more than several minutes of computation time. However, a distributed optimization approach may provide real time performance. Thereby, the solution of the central optimization problem is obtained by solving a set of small-scale, coupled optimization problems in parallel. At runtime, information is exchanged between the small-scale problems during the iterative solution procedure. A well-known approach of this class of distributed optimization algorithms is Optimalit... [more]

In recent years, the microgrid system (MGS) has become an important method for the consumption of renewable energy sources (RES). In the actual operation process, the uncertainties of RES add to the complexity of the MGS operation. Furthermore, the MGS is often operated by multiple subsystem operators. The benefit distribution among subsystem operators is an important factor affecting the overall stable operation of the MGS. In order to resist the interference of the above factors, a two-stage optimization method is proposed in this paper, which includes a bi-level robust optimization (BRO) model in the overall scheduling stage of the MGS and a nucleolus-based cooperative game (NCG) model in the internal cost allocation stage among the subsystem operators. The simulations demonstrated the following outcomes: (1) the P2G device can reduce the operating cost of the MGS by converting electricity into natural gas when the electricity price is low; (2) the two-stage optimization method can... [more]

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]

The explosion-proof diesel engine trackless rubber-tyred vehicle (TRTV) has the disadvantages of high fuel consumption and serious exhaust emissions, while the problems of insufficient power and short endurance limit the development of the explosion-proof battery trackless rubber-tyred vehicle. Hybrid technology can effectively reduce fuel consumption and emissions on the basis of ensuring sufficient power. Exploring the application of hybrid electric trackless rubber-tyred vehicle (HETRTV) has practical significance for coal mine auxiliary transportation. The degree of hybridization (DOH) will directly affect the performance and cost of TRTV, which needs to be focused in the development process. The effects of DOH on dynamic performance, fuel economy, emission performance, and cost were studied based on a simulation by ADVISOR, and the results were verified and analyzed by experiment. Compared with the flameproof diesel engine trackless vehicles, HETRTV with the optimal DOH exhausts h... [more]

The continually increasing fossil fuel prices, the dwindling of these fuels, and the bad environmental effects which mainly contribute to global warming phenomena are the main motives to replace conventional transportation means to electric. Charging electric vehicles (EVs) from renewable energy systems (RES) substantially avoids the side effects of using fossil fuels. The higher the increase in the number of EVs the greater the challenge to the reliability of the conventional power system. Increasing charging connections for EVs to the power system may cause serious problems to the power system, such as voltage fluctuations, contingencies in transmission lines, and loss increases. This paper introduces a novel strategy to not only replace the drawbacks of the EV charging stations on the power system’s stability and reliability, but also to enhance the power system’s performance. This improvement can be achieved using a smart demand side management (DSM) strategy and vehicle to grid (V... [more]

This paper presents a modified Levy particle swarm optimization (MLPSO) to improve the capability of maximum power point tracking (MPPT) under various partial shading conditions. This method is aimed primarily at resolving the tendency to trap at the local optimum particularly during shading conditions. By applying a Levy search to the particle swarm optimization (PSO), the randomness of the step size is not limited to a specific value, allowing for full exploration throughout the power-voltage (P-V) curve. Therefore, the problem such as immature convergence or being trapped at a local maximum power point can be avoided. The proposed method comes with great advantages in terms of consistent solutions over various environmental changes with a small number of particles. To verify the effectiveness of the proposed idea, the algorithm was tested on a boost converter of a photovoltaic (PV) energy system. Both simulation and experimental results showed that the proposed algorithm has a high... [more]

Both storage and transport of medical products remains a challenging task because of many variables as well as infrastructures, territory, and so on. Among these variables, monitoring the medical products temperature is fundamental to guarantee their safety. On the other hand, for sectors like aerospace delivery, weight has a crucial role too. For such applications and especially for strongly variable external temperatures, Peltier cells might be employed for either cooling or heating medical products to be stored. Accordingly, this study addresses the optimization of a heat sink for the thermal management of a Peltier-cell-based biomedical refrigerator. In detail, a brute-force multi-objective optimization of an impinging-flow finned heat sink for the Peltier cell is carried out here. Thermal resistance, weight, and pressure drop are chosen as the three-objective functions to be minimized, with both geometrical and volumetric flow rate as design variables. The results present a very l... [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]

To improve the performance and stability of the permanent magnet synchronous motor (PMSM), a new type of built-in permanent magnet synchronous motor (IPMSMB) is proposed. Firstly, the performance indexes of IPMSM, IPMSMA, and IPMSMB are compared by finite element analysis. The results show that the effective harmonic of the air-gap magnetic density of the motor increases when the rotor outer diameter is piecewise eccentric. At the same time, torque ripple and cogging torque decrease. Then the permanent magnet structure of the motor is changed on the basis of IPMSMA to form IPMSMB, which improves the output torque of the motor. Secondly, the Taguchi method is used to optimize the structural parameters of IPMSMB. After optimization, the output torque of IPMSMB is increased by 4.6%. The cogging torque and torque ripple are decreased by 45.5% and 25.7%, respectively. The consumption of permanent magnets is reduced by 7.74%. Finally, the rationality of the motor design is verified by the pr... [more]

Dry iron core reactors are widely used in various power quality applications. Manufacturers want to optimize the cost and loss simultaneously, which is normally achieved by the designers’ experience. This approach is highly subjective and can lead to a non-ideal product. Thus, an objective dry iron core reactor design approach to balance the cost and loss with a scientific basis is desired. In this paper, a multi-objective optimal design method is proposed to optimize both the cost and loss of the reactor, which provides an automatic and scientific design method. Specifically, a three-dimensional finite element model of dry iron core reactor is established, based on which the dependency of cost and loss upon the wire size of the reactor’s winding is studied by using joint Matlab-finite element method (FEM) simulation. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to search for the Pareto optimal solution set, out of which the optimal wire size of the reactor is deter... [more]