This paper investigates the theoretical reasons behind the low torque ripple of a fractional-slot concentrated-winding (FSCW) spoke-type interior permanent-magnet (IPM) machine obtained via a genetic algorithm-based optimization. To better understand the torque performance of the IPMM, this paper uses the frozen permeability method to segregate the overall torque into four components—magnet torque, reluctance torque, cogging torque, and the torque caused by cross-magnetization. Equations and detailed procedures of the torque separation method are discussed in the paper. Analysis of the separated torque components reveals that the counteraction between ripples of different torques leads to the low torque ripple. At high-load conditions, the magnetic saturation alters the torque ripples caused by cross-magnetization to offset ripples of other components resulting in minimization of the overall torque ripple. A detailed parametric analysis of the geometric parameters was carried out to un... [more]

In recent years, a large and growing body of literature has addressed the energy-efficient resource management problem in data centers. Due to the fact that cooling costs still remain the major portion of the total data center energy cost, thermal-aware resource management techniques have been employed to make additional energy savings. In this paper, we formulate the problem of minimizing the total energy consumption of a heterogeneous data center (MITEC) as a non-linear integer optimization problem. We consider both computing and cooling energy consumption and provide a thermal-aware Virtual Machine (VM) allocation heuristic based on the genetic algorithm. Experimental results show that, using the proposed formulation, up to 30 % energy saving is achieved compared to thermal-aware greedy algorithms and power-aware VM allocation heuristics.

The reflectors of a linear solar concentrator investigated in this work consisted of two plane mirrors (2MCC), and they were designed in such a way that made all radiation within the acceptance angle (θa) arrive on flat-plate absorber, after less than two reflections. To investigate the performance of an east−west aligned 2MCC-based photovoltaic (PV) system (2MCPV), a mathematical procedure was suggested based on the three-dimensional radiation transfer and was validated by the ray-tracing analysis. Analysis indicated that the performance of 2MCPV was dependent on the geometry of 2MCC, the reflectivity of mirrors (ρ), and solar resources in a site, thus, given θa, an optimal geometry of 2MCC for maximizing the annual collectible radiation (ACR) and annual electricity generation (AEG) of 2MCPV in a site could be respectively found through iterative calculations. Calculation results showed that when the ρ was high, the optimal design of 2MCC for maximizing its geometric concentration (Cg... [more]

Well-structured reactive power policies and dispatch are major concerns of operation and control technicians of any power system. Obtaining a suitable reactive power dispatch for any given load condition of the system is a prime duty of the system operator. It reduces loss of active power occurring during transmission by regulating reactive power control variables, thus boosting the voltage profile, enhancing the system security and power transfer capability, thereby attaining an improvement in overall system operation. The reactive power dispatch (RPD) problem being a mixed-integer discrete continuous (MIDC) problem demands the solution to contain all these variable types. This paper proposes a methodology to achieve an optimal and practically feasible solution to the RPD problem through the diversity-enhanced particle swarm optimization (DEPSO) technique. The suggested method is characterized by the calculation of the diversity of each particle from its mean position after every iter... [more]

A Time-of-Use (TOU)-tariff scheme, helps residential customers to adjust their energy consumption voluntarily and reduce energy cost. The TOU tariff provides flexibility in demand, alleviate volatility caused by an increase in renewable energy in the power system. However, the uncertainty in the customer’s behavior, causes difficulty in predicting changes in residential demand patterns through the TOU tariff. In this study, the dissatisfaction model for each time slot is set as the energy consumption data of the customer. Based on the actual customer’s consumption pattern, the user sets up a model of dissatisfaction that enables aggressive energy cost reduction. In the proposed Home Energy Management System (HEMS) model, the efficient use of jointly invested offsite photovoltaic (PV) power generation is also considered. The optimal HEMS scheduling result considering the dissatisfaction, cost, and PV curtailment was obtained. The findings of this study indicate, that incentives are requ... [more]

The number and interdependency of vehicle CO2 reduction technologies, which can be employed to reduce greenhouse emissions for regulatory compliance in the European Union and other countries, has increasingly grown in the recent years. This paper proposes a method to optimally combine these technologies on cars or other road vehicles to improve their energy efficiency. The methodological difficulty is in the fact that these technologies have incompatibilities between them. Moreover, two conflicting objective functions are considered and have to be optimized to obtain Pareto optimal solutions: the CO2 reduction versus costs. For this NP-complete combinatorial problem, a method based on a metaheuristic with Ant Colony Optimization (ACO) combined with a Local Search (LS) algorithm is proposed and generalized as the Technology Packaging Problem (TPP). It consists in finding, from a given set of technologies (each with a specific cost and CO2 reduction potential), among all their possible c... [more]

Optimization design of an impeller is critical for the energy performance of a fan. This paper takes the promotion of fan efficiency and pressure rise as the optimization objectives to carry out multiparameter and multiobjective optimization research. Firstly, an experimental test bench is built to measure the energy performance of the original fan and verify the accuracy of the numerical method. Then, the hub outlet angle of impeller β1, the impeller outlet angle increment Δβ1, the wrap angle φ, the hub outlet angle of diffuser β2, and the diffuser outlet angle increment Δβ2 are set as the optimal parameters to conduct orthogonal optimal design. The results show that the efficiency of the optimal fan increases by 11.71%, and the pressure rise increases by 50.15%. The pressure and velocity distributions in an optimal fan are uniform, the internal flow separation is weakened, and the influence of tip leakage flow is reduced, which makes for the improvement of energy performance for the... [more]

This paper proposes a mathematical model based on mixed integer linear programming (MILP). This model aids the decision-making process in local generation use and demand response application to power demand contract adequacy by Brazilian consumers/prosumers. Electric energy billing in Brazil has some specificities which make it difficult to consider the choice of the tariff modality, the determination of the optimal contracted demand value, and demand response actions. In order to bridge this gap, the model considers local generation connected to the grid (distributed generation) and establishes an optimized solution indicating power energy contract aspects and the potential reduction in expenses for the next billing period (12 months). Different alternative sources already available or of interest to the consumer can be considered. The proposed mathematical model configures an optimization tool for the feasibility analysis of local generation use and, concomitantly, (i) checking the t... [more]

With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environment, this paper provides an opportunity constraint programming model for the random variables contained in the constraint conditions. Considering the probability distribution of the random variables, a home energy management method for DR based on chance-constrained programming is proposed. Different confidence levels are set to reflect the influence mechanism of random variables on constraint conditions. An improved particle swarm optimization algorithm is used to solve the problem. Finally, the demand response characteristics in daily and emergency situations are analyzed by simulation examples, and the effectiveness of the method is verified.

The economic impact associated with power quality (PQ) problems in electrical systems is increasing, so PQ improvement research becomes a key task. In this paper, a Stockwell transform (ST)-based hybrid machine learning approach was used for the recognition and classification of power quality disturbances (PQDs). The ST of the PQDs was used to extract significant waveform features which constitute the input vectors for different machine learning approaches, including the K-nearest neighbors’ algorithm (K-NN), decision tree (DT), and support vector machine (SVM) used for classifying the PQDs. The procedure was optimized by using the genetic algorithm (GA) and the competitive swarm optimization algorithm (CSO). To test the proposed methodology, synthetic PQD waveforms were generated. Typical single disturbances for the voltage signal, as well as complex disturbances resulting from possible combinations of them, were considered. Furthermore, different levels of white Gaussian noise were a... [more]

With the advancing trend towards lighter and faster rail transport, there is an increasing interest in integrating composite and advanced multifunctional materials in order to infuse smart sensing and monitoring, energy harvesting and wireless capabilities within the otherwise purely mechanical rail structures and the infrastructure. This paper presents a holistic multiphysics numerical study, across both mechanical and electrical domains, that describes an innovative technique of harvesting energy from a piezoelectric micro fiber composites (MFC) built-in composite rail chassis structure. Representative environmental vibration data measured from a rail cabin have been critically leveraged here to help predict the actual vibratory and power output behaviour under service. Time domain mean stress distribution data from the Finite Element simulation were used to predict the raw AC voltage output of the MFCs. Conditioned power output was then calculated using circuit simulation of several... [more]

With the growing concern about decreasing CO 2 emissions, renewable energy sources are being vastly integrated in the energy systems worldwide. This will bring new challenges to the network operators, which will need to find sources of flexibility to cope with the variable-output nature of these technologies. Demand response and multi-energy systems are being widely studied and considered as a promising solution to mitigate possible problems that may occur in the energy systems due to the large-scale integration of renewables. In this work, an optimal model to manage the resources and loads within residential and commercial buildings was developed, considering consumers preferences, electrical network restrictions and CO 2 emissions. The flexibility that these buildings can provide was analyzed and quantified. Additionally, it was shown how this model can be used to solve technical problems in electrical networks, comparing the performance of two scenarios of flexibilit... [more]

The paper presents a method developed for the energy retrofit of specific Heat Exchanger Networks not containing Utility Paths. This useful and highly practically oriented method involves a systematic approach to obtaining the most efficient minimal modification topology of a Heat Exchanger Network, which brings the greatest benefits in terms of energy savings of the modified process. In principle, it is focused on finding the most suitable location for a new heat exchanger insertion to create the most efficient Utility Path. The next step of the developed retrofit method is the detailed design of the newly integrated heat exchanger using commercial software in combination with several heuristic rules regarding the cost-free investment and maintenance cost minimization of a new heat exchanger and considering heat transfer enhancement within the available exchanger type, space, and fluids pressure drop constraints. The detail design stage of the method also includes observation and reas... [more]

The importance of efficient utilization of biomass as renewable energy in terms of global warming and resource shortages are well known and documented. Biomass gasification is a promising power technology especially for decentralized energy systems. Decisive progress has been made in the gasification technologies development during the last decade. This paper deals with the control and optimization problems for an isolated microgrid combining the renewable energy sources (solar energy and biomass gasification) with a diesel power plant. The control problem of an isolated microgrid is formulated as a Markov decision process and we studied how reinforcement learning can be employed to address this problem to minimize the total system cost. The most economic microgrid configuration was found, and it uses biomass gasification units with an internal combustion engine operating both in single-fuel mode (producer gas) and in dual-fuel mode (diesel fuel and producer gas).

Facing energy shortage and severe environmental pollution, manufacturing companies need to urgently energy consumption, make rational use of resources and improve economic benefits. This paper formulates a multi-objective optimization model for lathe turning operations which aims to simultaneously minimize energy consumption, machining cost and cutting time. A dynamic multi-swarm particle swarm optimizer (DMS-PSO) is proposed to solve the formulation. A case study is provided to illustrate the effectiveness of the proposed algorithm. The results show that the DMS-PSO approach can ensure good convergence and diversity of the solution set. Additionally, the optimal machining parameters are identified by fuzzy comprehensive evaluation (FCE) and compared with empirical parameters. It is discovered that the optimal parameters obtained from the proposed algorithm outperform the empirical parameters in all three objectives. The research findings shed new light on energy conservation of machin... [more]

As the demand for high-speed elevators grows, the requirements of elevator performance have also increased. Most of these are single variables that do not consider the comprehensive impact of multiple variables on performance, especially comfort. To overcome this problem, a stepped segmentation method for a theoretical high-speed elevator car air pressure curve (THEC-APC) adjustment is proposed that could actively help to select a suitable theoretical elevator car air pressure adjustment curve. By utilizing the proposed Particle Swarm Optimization (PSO) algorithm, the theoretical elevator car air pressure curve is optimized for multiple performances (including passenger comfort, energy consumption, and aerodynamic characteristics). In addition, the THEC-APC is smoothed by the Bezier curve for the variable destination floor. To verify the proposed method, the KLK2 (Canny Elevator Co., Ltd., 2015, Suzhou) high-speed elevator design process is applied. The numerical experiment results sho... [more]

The performance of lithium-ion batteries will inevitably degrade during the high frequently charging/discharging load applied in electric vehicles. For hybrid electric vehicles, battery aging not only declines the performance and reliability of the battery itself, but it also affects the whole energy efficiency of the vehicle since the engine has to participate more. Therefore, the energy management strategy is required to be adjusted during the entire lifespan of lithium-ion batteries to maintain the optimality of energy economy. In this study, tests of the battery performances under thirteen different aging stages are involved and a parameters-varying battery model that represents the battery degradation is established. The influences of battery aging on energy consumption of a given plug-in hybrid electric vehicle (PHEV) are analyzed quantitatively. The results indicate that the variations of capacity and internal resistance are the main factors while the polarization and open circu... [more]

This paper proposes a novel layered permanent magnet motor (N-LPM), which is based on a three-degree-of-freedom (3-DOF) permanent magnet motor. Compared with the former, the improved N-LPM air gap magnetic density, torque and structure stability have been significantly improved. The proposed N-LPM has three layers of stator along the axis direction, and each layer of stator has three-phase winding. In order to calculate the magnetic field and torque distribution of the N-LPM, an analytical method (AM) is proposed. For performance verification and accurate calculation, finite-element analysis (FEA) is adopted. The two kinds of motors before and after the improvement are compared, and their magnetic field, torque and stability are analyzed. The optimization rate is defined to evaluate the performance of the motor before and after improvement. The results show that the radial flux density, rotation torque, deflection torque and the volume optimization rate of the permanent magnet of the i... [more]

To analyze the effect of carbon emission quota allocation on the locational marginal price (LMP) of day-ahead electricity markets, this paper proposes a two-stage algorithm. For the first stage of the algorithm, a multi-objective optimization model is established to simultaneously minimize the total costs and carbon emission costs of power systems. Hence, an evenly distributed Pareto optimal solution can be solved effectively by means of the normalized normal constraint method. For the second stage, a tracing model is built with the goal of minimizing the total costs of power systems and satisfying the constraints generated based on the Pareto optimal solution obtained from the first stage. Furthermore, the influence of carbon emission quota allocation on the LMP of electricity markets is analyzed, and different schemes to allocate carbon emission quotas are evaluated on a real 1560-bus and 52-unit system.

Increased concerns over global warming and air pollution has pushed governments to consider renewable energy as an alternative to meet the required energy demands of countries. Many government policies are deployed in Taiwan to promote solar and wind energy to cope with air pollution and self-dependency for energy generation. However, the residential sector contribution is not significant despite higher feed-in tariff rates set by government. This study analyzes wind and solar power availability of four different locations of southern Taiwan, based on the Köppen−Geiger climate classification system. The solar−wind hybrid system (SWHS) considered in this study consists of multi-crystalline photovoltaic (PV) modules, vertical wind turbines, inverters and batteries. Global reanalysis weather data and a climate-based electricity load profile at a 1-h resolution was used for the simulation. A general framework for multi-objective optimization using this simulation technique is proposed for... [more]

In this paper, opportunities and challenges of concrete portfolio options of an Austrian district heating (DH) supplier are assessed against the background of current challenges of the DH sector. The following steps are performed: (1) analysis of status quo; (2) analysis of current and possible future economic framework conditions; (3) definition of four concrete future portfolio options for investment planning until the year 2030; (4) modeling of status quo and future portfolios together with the respective framework conditions in a linear dispatch optimization model; and (5) perform techno-economic analysis for each portfolio under the different possible future framework conditions. The expected increase in renewable power generation capacity is likely to increase volatility in future electricity prices with hours of both very low and very high prices. This higher volatility results in higher technical flexibility requirements for the heat generation plants and a need for heat genera... [more]

Powertrain system design optimization is an unexplored territory for battery electric trucks, which only recently have been seen as a feasible solution for sustainable road transport. To investigate the potential of these vehicles, in this paper, a variety of new battery electric powertrain topologies for heavy-duty trucks is studied. Thereby, topological design considerations are analyzed related to having: (a) a central or distributed drive system (individually-driven wheels); (b) a single or a multi-speed gearbox; and finally, (c) a single or multiple electric machines. For reasons of comparison, each concurrent powertrain topology is optimized using a bilevel optimization framework, incorporating both powertrain components and control design. The results show that the combined choice of powertrain topology and number of gears in the gearbox can result in a 5.6% total-cost-of-ownership variation of the vehicle and can, significantly, influence the optimal sizing of the electric mach... [more]

In this study, a novel injector driving circuit was developed to achieve the regulation of fuel injection quantity and to work with the engine control system in a vehicle. The main purpose of the proposed injector driving circuit is to control the quantity and timing of fuel injection within the gasoline direct injection (GDI) fuel injector system. In this paper, a mathematical state model of a high-pressure (H.P.) fuel injector system is derived and the improved Taguchi method is proposed to define the optimal operating parameter settings of a fuel injector system. The experiments on fuel injection quantity were performed to achieve the requirements of the injector driving circuit. The fuel quantity sprayed from a fuel injector system under these control parameters was analyzed by leading the design of experiments. The S/N and β slopes were analyzed to determine their optimal control settings. The H.P. injector driving circuit developed was designed to drive the fuel injector and spra... [more]

Growing ecological standards force the implementation of solutions that will contribute to reducing greenhouse gas (GHG) emissions to the atmosphere. This is particularly important in Poland, whose energy system is almost 80% based on coal. In the interest of low carbon development it is worth considering the optimization of existing old coal-based power plants. The main goal of the research was to present the benefits of modernization of existing boiler equipment and to analyze the combustion process of various types of coal sorts that have a significant impact on the optimization of the production processes of energy media. An analysis of the processes occurring in boiler devices during the combustion of fuel was carried out, which had a significant impact on the quality of generated heat and electricity. The conducted research defined technological solutions for boiler structures that have a significant impact on improving the efficiency of the technological process in heating plant... [more]

With high penetrations of renewable energy sources (RES), distributed battery systems (DBS) are widely adopted in standalone DC microgrids to stabilize the bus voltages by balancing the active power. This paper presents an Adaptive Differential Evolution (ADE)-based hierarchical control for DBS to achieve online distribution power loss mitigation as well as bus voltage regulations in standalone DC microgrids. The hierarchical control comprises two layers, i.e., ADE for the secondary layer and local proportional-integral (PI) control for the primary layer. The secondary layer control provides the bus voltage references for the primary control by optimizing the fitness function, which contains the parameters of the bus voltage deviations and the power loss on the distribution lines. Simultaneously, the state-of-charge (SoC) of the battery packs are controlled by local controllers to prevent over-charge and deep-discharge. Case studies using a Real-Time Digital Simulator (RTDS) validate t... [more]