Well-designed energy management strategies are essential for the good operation of Hybrid Electric Vehicles (HEVs) in terms of fuel economy and pollutant emissions reduction, regardless of the specific powertrain architecture. The goal of this paper is to propose two innovative supervisory control strategies for HEVs derived from different optimization algorithms and to assess HEVs’ fuel consumption reduction (compared to conventional vehicles). These approaches are derived from the literature and modified by the authors to present novel algorithms for the optimization problem. One is based on Dynamic Programming (DP), here referred to as the Forward Approach to Dynamic Programming (FADP) and introduces a different implementation of the DP to achieve computational and accuracy benefits. The other is based on the Equivalent Consumption Minimization Strategy (ECMS) approach, and it adapts to the latest driving conditions using information gathered in a finite-length backward-looking hori... [more]

Power outage prediction is important for planning electric power system response, restoration, and maintenance efforts. It is important for utility managers to understand the impact of outages on the local distribution infrastructure in order to develop appropriate maintenance and resilience measures. Power outage prediction models in literature are often limited in scope, typically tailored to model extreme weather related outage events. While these models are sufficient in predicting widespread outages from adverse weather events, they may fail to capture more frequent, non-weather related outages (NWO). In this study, we explore time series models of NWO by incorporating state-of-the-art techniques that leverage the Prophet model in Bayesian optimization and hierarchical forecasting. After defining a robust metric for NWO (non-weather outage count index, NWOCI), time series forecasting models that leverage advanced preprocessing and forecasting techniques in Kats and Prophet, respec... [more]

With the increasing need for cooling and the concerns for pollution due to fossil fuel-based energy use, renewable energy is considered an add-on to cooling technologies. The climatic condition in the Middle East, analyzed in this paper, provides the potential to integrate solar energy with the cooling system. Due to the availability of various solar energy and cooling technologies, multiple configurations of solar-cooling systems can be considered to satisfy the cooling demand. The research presented in this paper aims to assess and compare these configurations by considering the energy prices and the installation area. The proposed model is formulated in Mixed-Integer Linear Programming and optimizes the holistic system design and operation. The economic, renewable energy use, and environmental performances of the optimal solution for each configuration are analyzed and compared to the base grid-DCS configuration. Results show that the electricity tariff and the available installatio... [more]

A method is proposed for optimizing circuits of sequential devices which are used in cyber-physical systems (CPSs) implemented using field programmable gate arrays (FPGAs). The optimizing hardware is a very important problem connected with implementing digital parts of CPSs. In this article, we discuss a case when Mealy finite state machines (FSMs) represent behaviour of sequential devices. The proposed method is aimed at optimization of FSM circuits implemented with look-up table (LUT) elements of FPGA chip. The method aims to reduce the LUT count of Mealy FSMs with extended state codes. The method is based on finding a partition of the set of internal states by classes of compatible states. To reduce LUT count, we propose a special kind of state codes named composite state codes. The composite codes include two parts. The first part includes the binary codes of states as elements of some partition class. The second part consists of the code of corresponding partition class. Using com... [more]

Energy has become an integral part of our society and global economic development in the twenty-first century. Despite tremendous technological advancements, fossil fuels (coal, natural gas, and oil) continue to be the world’s primary source of energy. Global energy scenarios indicate a change in coal consumption trends in the future, which in turn will have commercial, geopolitical, and environmental consequences. We investigated coal consumption up to 2030 using a new hybrid method of WOANFIS (whale optimization algorithm and adaptive neuro-fuzzy inference system). The WOANFIS method’s performance was assessed by the MSE (Mean Squared Error), MAE (Mean Absolute Error), STD (error standard deviation), RMSE (Root Mean Squared Error), and coefficient of correlation (R2) among the real dataset and the WOANFIS result. For the prediction of global coal consumption, the proposed WOANFIS had the best MAE, RMSE, and correlation coefficient (R2) values, which were 0.00113, 0.0047, and 0.98, re... [more]

Several socioeconomic factors such as industrialization, population growth, evolution of modern technologies, urbanization and other social activities do heavily influence the increase in energy demand. A thorough understanding of the effects of energy demand to power grid is highly essential for effective planning and operation of a power system network in terms of the available generation and transmission line capacities. This paper presents an optimal power flow (OPF) with the aim to determine the exact nodes through which the network capacities can be increased. The problem is formulated as a Direct Current (DC) OPF model, which is a linearized version of an Alternating Current (AC) OPF model. The DC-OPF model was solved as a single period OPF problem. The model was tested in several case studies using the topology of the IEEE test systems, and the computation speeds of the different cases were compared. The results suggested dual variables of the problem’s constraints as an extra... [more]

As the world is keen on cleaner and sustainable energy, hydrogen energy has the potential to be part of the green energy transition to replace fossil fuels and mitigate climate change. However, hydrogen energy storage is a difficult task since physical storage in the form of compressed gas under high pressure is associated with safety issues. Another form of hydrogen storage is material-based storage, which is the safest way to store hydrogen energy in a particulate matter, known as metal hydrides. Metal hydrides can store hydrogen at room temperature and use less volume to store the same amount of hydrogen compared to classical gas tanks. The challenges with the metal hydrides reactor are their slow charging process and the requirement of proper thermal management during the charging process. In this study, a metal hydride reactor model is developed in COMSOL Multiphysics, and the associated heat transfer simulations are performed. The main objective of this research is to optimize th... [more]

A guide vane was installed on a heat sink to enhance the cooling effect of light-emitting diode (LED) lights. The validity of the numerical analysis was verified against the experimental results and the result of the previous studies. The effect of the guide vane on the heat dissipation performance of the heat sink was identified. The effect of the guide vane on the heat sink was qualitatively studied using the streamline and temperature contour. The cooling effect of the heat sink was enhanced by increased air supplement to the center-bottom part. A parametric study was conducted to determine the thermal resistance according to the guide vane angle, installation height, and vane length. Optimization was performed to minimize the thermal resistance using the Kriging model and micro-genetic algorithm (MGA). The cooling performance of the heat sink was enhanced by a maximum of 17.2% when the guide vane was installed.

In buildings with the solar heat collection/insulation energy-saving window (SHC/IESW), when the insulation device is placed at night in winter, a double-wall structure façade (DSF) is formed between the glass and the insulation curtain, and the existence of air inlet and outlet leads to cold air penetration. In this paper, the Nusselt number (Nu) correlation and convective heat transfer coefficient (CHTC) of the cavity in SHC/IESW were calculated through an experiment combined with a theoretical analysis. Then, numerical simulation was performed on the fluid dynamics and thermal characteristics caused by air convection in an asymmetrically heated cavity under uniform heat flow conditions, to optimize the SHC/IESW structure and analyze its heat transfer mechanism to solve the problem of convection heat transfer between plates under cold air infiltration. Using the calculation formulas obtained from the experiment, the heat transfer coefficient of SHC/IESW is 1.71 W·m−2·K−1. The numeric... [more]

This paper presents the integration of shunt capacitors in the radial distribution grids (RDG) with constant and time-varying load consideration for the reduction of power losses and total annual cost, which turns to enhance the voltage profile and annual net savings. To gather the stated goals, three objective functions are formulated with system constraints. To solve this identified problem, a novel optimization technique based on the modification of particle swarm optimization is proposed. The solution methodology is divided into two phases. In phase one, potential candidate buses are nominated using the loss sensitivity factor method and in phase two the proposed technique first selects the optimal buses for the capacitor placement among the potential buses then it decides the optimal sizing of the capacitors as well. To demonstrate the performance in terms of efficiency and strength, the proposed technique is tested on IEEE 15, 33, and 69 bus system for the optimal placement and s... [more]

Even though many studies have been deployed to determine the optimal planning and operation of microgrids, limited research was discussed to determine the optimal microgrids’ geographical boundaries. This paper proposes a zonal-based optimal microgrid identification model aiming at identifying the optimal microgrids topology in the current distribution systems through zoning the network into several clusters. In addition, the proposed model was developed as a mixed-integer linear programming (MILP) problem that identifies the optimal capacity and location of installing distributed energy resources (DERs), including but not limited to renewable energy resources and Battery Energy Storage Systems (BESS), within the determined microgrid’s boundaries. Moreover, it investigates the impact of incorporating the BESS in boosting the DERs’ penetration on the optimal centralized microgrid. Numerical simulations on the IEEE-33 bus test system demonstrate the features and effectiveness of the prop... [more]

According to different mission scenarios, the UAV swarm needs to form specific topology shapes to achieve more robust system capability. The topology shaping, which will guide the UAVs autonomously to form the desired topology shape, is considered one of the most basic procedures in the UAV swarm field operations. The traditional optimization model of UAV swarm topology shaping proposed in most studies roughly represents the energy consumption by the squared Euclidean distances from initial positions to target positions of nodes. However, in practice, UAVs flying in different directions (vertical or horizontal) usually exhibits different energy consumption even though under the same moving distance. This paper proposes a more precise energy consumption model for UAV swarm topology shaping while taking the energy consumption for a UAV flying vertically upward, vertically downward, and horizontally into account. Simulation results show that the global energy consumption of the topology s... [more]

Adequate recognition of the offshore wind energy potential may help coastal states frame proper energy policies for replacing nuclear and fossil fuel energy. In this study, we examined the application potential of the offshore wind energy generated by 31 offshore wind farms designated by the Taiwanese government for future exploitation. Our findings indicate that offshore wind energy (through its substantial power generation volume and capacity factor) can play the most pivotal role in future power generation for Taiwan. A total of 59.3 TWh of electricity produced from offshore wind energy and solar photovoltaics (PVs) each year could replace the power generated from nuclear energy by 2025. Coal-fired power generation could be replaced by offshore wind energy and other renewables by 2032. The full exploitation of offshore wind farms as detailed in this study (103.4 TWh/year), together with other renewables, could reduce the share of liquefied natural gas-fired power generation to 5.6%... [more]

Transportation has been incorporating electric vehicles (EVs) progressively. EVs do not produce air or noise pollution, and they have high energy efficiency and low maintenance costs. In this context, the development of efficient techniques to overcome the vehicle routing problem becomes crucial with the proliferation of EVs. The vehicle routing problem concerns the freight capacity and battery autonomy limitations in different delivery-service scenarios, and the challenge of best locating recharging stations. This work proposes a mixed-integer linear programming model to solve the electric location routing problem with time windows (E-LRPTW) considering the state of charge, freight and battery capacities, and customer time windows in the decision model. A clustering strategy based on the k-means algorithm is proposed to divide the set of vertices (EVs) into small areas and define potential sites for recharging stations, while reducing the number of binary variables. The proposed model... [more]

As an important energy base in China, Shanxi Province, in its economic development, has depended heavily on coal resources. However, enormous coal consumption produces a large amount of carbon dioxide and an aggravated ecological problem. In this paper, the super efficiency slack-based measure and data envelopment analysis (SBM-DEA) model and Malmquist index were used to calculate the energy consumption and carbon emission efficiency of 11 prefecture-level cities in Shanxi in the period from 2000 to 2020. The results were as follows: (1) The primary form of energy consumption in Shanxi Province is the burning of coal, and the carbon emission efficiencies of the 11 prefecture-level cities are quite different. The technical efficiency, technological progress, and total factor productivity of Taiyuan and Shuozhou were found to be greater than 1 compared to other cities in Shanxi. (2) On the whole, although the carbon emission rate of Shanxi Province has slowed down, it still faces the pro... [more]

La3Te4-based rare-earth telluride is a kind of n-type high-temperature thermoelectric (TE) material with an operational temperature of up to 1273 K, which is a promising candidate for thermoelectric generators. In this work, the Sm substitution in La3−xSmTe4/Ni composites is reported. The electrical transport property of La3−xSmTe4 is modified by reducing carrier concentration due to the substitution of Sm2+ for La3+. The electric thermal conductivity decreases by 90% due to carrier concentration reduction, which mainly contributes to a reduction in total thermal conductivity. Lattice thermal conductivity also decreases by point-defect scattering by Sm doping. Meanwhile, based on our previous study, compositing nickel improves the thermal stability of the La3 − xSmTe4 matrix. Finally, combined with carrier concentration optimization and the decreased thermal conductivity, a maximum zT of 1.1 at 1273 K and an average zTave value of 0.8 over 600 K−1273 K were achieved in La2.315Sm0.685Te... [more]

Operation optimization for large-scale offshore wind farms can cause the fatigue loads of single wind turbines to exceed their limits. This study aims to improve the economic profit of offshore wind farms by conducting multi-objective optimization via decoupled group operations of turbines. To do this, a large-scale wind farm is firstly divided into several decoupled subsets through the parallel depth-first search (PDFS) and hyperlink-induced topic search (HITS) algorithms based on the wake-based direction graph. Next, three optimization objectives are considered, including total output power, total fatigue load, and fatigue load dispatch on a single wind turbine (WT) in a wind farm. And then, the combined Monte Carlo and beetle swarm optimization (CMC-BSO) algorithms are applied to solve the multi-objective non-convex optimization problem based on the decentralized communication network topology. Finally, the simulation results demonstrate that the proposed method balances the total p... [more]

This paper deals with the method of shaping the magnetic field distribution in the air gap of a synchronous machine. The main goal is to obtain a specific distribution of the magnetic field in the machine’s air gap to enable easier powering, to increase the torque and power density, or to limit the content of higher harmonics in the induced voltage and torque. This method can be applied for both the electrically excited machines and permanent magnets excited machines. The problem has been reduced to solving a modified system of algebraic equations obtained by the finite element method. The presented examples show the effectiveness of the proposed method both in shaping the contours of the air gap and the magnetization of permanent magnets placed on the rotor. The method can particularly be used in the design of the high-speed synchronous machines.

Aggregated electric vehicles (EVs) integrated to the grid and intermittent wind and solar energy increased the complexity of the economic dispatch of the power grid. Aggregated EVs have a great potential to reduce system operating costs because of their dual attributes of load and energy storage. In this paper, plugged-in EV is refined into three categories: rated power charging, adjustable charging, and flexible charging−discharging, and then control models are established separately; the concept of temporal flexibility for EV clusters is proposed for the adjustable charging and flexible charging−discharging of EV sets; then, the schedule boundary of EV clusters is determined under the flexibility constraints. The interval is used to describe the intermittent nature of renewable energy, and the minimum operating cost of the system is taken as the goal to construct a distributed energy robust optimization model. By decoupling the model, a two-stage efficient solution is achieved. An ex... [more]

A space solar power station (SSPS) has become a huge potential candidate to provide abundant and clean electrical energy for terrestrial users by collecting and converting solar power in space. In this paper, an innovative two-layer ring truss-based SSPS is proposed. It consists of the top layer concentrator-based spherical one-time reflection region, the bottom layer space radiator using symmetric or asymmetric cable networks, a ring truss for a supporting structure, a photoelectric conversion system, and transmitting antennas. The construction strategies including the triangular facets modularity of top layer concentrator, area requirement of bottom layer space radiator, two-segment optimization design of generatrix of photoelectric conversion system, and aperture derivation of transmitting antenna are carried out. Then, the performance analysis mainly including the modularization theory error calculation, energy collection and distribution, and thermal characteristics in orbit of th... [more]

Coal-fired power plants are widely used to achieve a power balance in grids with renewable energy, which leads to new requirements for speediness in load dispatch. This paper presents a nondominated-sorting grey wolf optimizer algorithm (NSGWO) for the multiobjective load dispatch of coal-fired power plants that employed efficient nondominated sorting, a reference-point selection strategy, and a simulated binary crossover operator. The optimization results of the benchmark functions indicated that the NSGWO algorithm had a better accuracy and a better distribution than the traditional multiobjective grey wolf optimizer algorithm. Regarding the load dispatch of economy, environmental protection, and speediness strategies, the NSGWO had the best performance of all the simulated algorithms. The optimal-compromise solutions of the economy and speediness strategies of the NSGWO algorithm had a good distribution, which elucidated that this novel algorithm was favorable to allowing coal-fired... [more]

We invert gravity and magnetic anomalies for basement relief at the Harrat Rahat Volcanic Field (HRVF) for the purpose of evaluating its geothermal energy prospects. HRVF is dominated by basaltic scoria cones and other volcanic rocks overlying the Proterozoic basement. The area considered for this study is located within the northern HRVF and consists mainly of alkali basalts with lesser amounts of benmoreite, mugearite, hawaiite, and trachyte. Our approach adopts a global optimization technique using Particle Swarm Optimization with automated parameter selection, and a two-dimensional gravity-magnetic (GM) forward modeling procedure. The results of the PSO-based approach indicate a depth to the basement at 0.10−624 m, with greater depths within the central region of a solitary anomalous density body in the HRVF. The obtained basement geometry is corroborated by the depth estimates obtained from other potential field inversion methods. The regions with higher prospects are mapped for a... [more]

With increasing concerns on transportation decarbonization, fuel cell hybrid trains (FCHTs) attract many attentions due to their zero carbon emissions during operation. Since fuel cells alone cannot recover the regenerative braking energy (RBE), energy storage devices (ESDs) are commonly deployed for the recovery of RBE and provide extra traction power to improve the energy efficiency. This paper aims to minimize the net hydrogen consumption (NHC) by co-optimizing both train speed trajectory and onboard energy management using a time-based mixed integer linear programming (MILP) model. In the case with the constraints of speed limits and gradients, the NHC of co-optimization reduces by 6.4% compared to the result obtained by the sequential optimization, which optimizes train control strategies first and then the energy management. Additionally, the relationship between NHC and employed ESD capacity is studied and it is found that with the increase of ESD capacity, the NHC can be reduce... [more]

The use of a cobalt-iron (VaCoFe) core is investigated as an alternative to silicon-iron (FeSi) in the design of interior permanent magnet synchronous motors (IPMSM). Considering VaCoFe and FeSi cores, a spoke-type IPMSM geometry is optimized for a torque range up to 40 N·m, providing a general comparative analysis between materials. This is done considering the application of a four-motor competition vehicle’s powertrain. A genetic optimization algorithm is coupled to the motor’s electromagnetic and thermal hybrid analytical/finite-element model to provide sufficiently accurate results within a feasible time. VaCoFe allows an estimated increase of up to 64% in torque for the same efficiency level, or up to 5% in efficiency for the same torque. After optimization and using a detailed time-dependent model, a potential 3.2% increase in efficiency, a core weight reduction of 4.1%, and a decrease of 9.6% in the motor’s core volume were found for the VaCoFe at 20 N·m. In addition, for the s... [more]

The optimization of injection−production parameters is an important step in the design of gas injection development schemes, but there are many influencing factors and they are difficult to determine. To solve this problem, this paper optimizes injection-production parameters by combining an improved particle swarm optimization algorithm to study the relationship between injection-production parameters and the net present value. In the process of injection-production parameter optimization, the particle swarm optimization algorithm has shortcomings, such as being prone to fall into local extreme points and slow in convergence speed. Curve adaptive and simulated annealing particle swarm optimization algorithms are proposed to further improve the optimization ability of the particle swarm optimization algorithm. Taking the Tarim oil field as an example, in different stages, the production time, injection volume and flowing bottom hole pressure were used as input variables, and the optima... [more]