Electric vehicles represent a necessary alternative for wheeled transportation to meet the global and national targets specified in the Paris Agreement of 2016. However, the high concentration of electric vehicles exposes their harmful effects on the power grid. This reflects negatively on electricity market prices, making the charging of electric vehicles less cost-effective. This study investigates the economic potential of different charging strategies for an existing office site in Austria with multiple charging infrastructures. For this purpose, a proper mathematical representation of the investigated case study is needed in order to define multiple optimization problems that are able to determine the financial potential of different charging strategies. This paper presents a method to implement electric vehicles and stationary battery storage in optimization problems with the exclusive use of linear relationships and applies it to a real-life use case with measured data to prove... [more]

Gun firing is a process that converts propellant chemical energy to projectile kinetic energy and other kinds of energies. In order to explore the energy conversion process, firstly, the interior ballistics mathematical model and the barrel-projectile finite element model are built and solved. Then, the related variable values and energy values are obtained and discussed. Finally, for improving energy efficiency, the interval uncertainty optimization problem is modeled, and then solved using the two-layer nested optimization strategy and back-propagation (BP) neural network surrogate model. Calculation results show that, after optimization, the heat efficiency raises from 31.13% to 33.05% and the max rifling stress decreases from 893.68 to 859.76 Mpa, which would improve the firing performance and prolong the lifetime of the gun barrel.

Replacing traditional internal combustion engine vehicles with electric vehicles (EVs) proves to be challenging for the transport sector, particularly due to the higher initial investment. As EVs could be more profitable by participating in the electricity markets, the aim of this paper is to investigate revenue potentials when marketing bidirectionally chargeable electric vehicles in the spot market. To simulate a realistic marketing behavior of electric vehicles, a mixed integer linear, rolling horizon optimization model is formulated considering real trading times in the day-ahead and intraday market. Results suggest that revenue potentials are strongly dependent on the EV pool, the user behavior and the regulatory framework. Modeled potential revenues of EVs of current average size marketed with 2019 German day-ahead prices are found to be at around 200 €/EV/a, which is comparable to other findings in literature, and go up to 500 €/EV/a for consecutive trading in German day-ahead a... [more]

This paper presents an improved inverse-time over-current protection method based on the compound fault acceleration factor and the beetle antennae search (BAS) optimization method for a microgrid. The proposed method can not only significantly increase the operation speed of the inverse-time over-current protection but also improve the protection coordination by considering the possible influential factors in terms of microgrid operation modes, distributed generation (DG) integration status, fault types, and positions, which are marked as the most challenging problems for over-current protection of a microgrid. In this paper, a new Time Dial Setting (TDS) of inverse-time protection is developed by applying a compound fault acceleration factor, which can notably accelerate the speed of protection by using low-voltage and short-circuit impedance during the fault. In order to improve the protection coordination, the BAS algorithm is then used to optimize the protection parameters of the... [more]

The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power network... [more]

Photovoltaic system is utilized to generate energy that relies upon the ecological conditions, for example, temperature, irradiance, and the load associated with it. Considering the non-linear component of photovoltaic (PV) array and the issue of low effectiveness because of the variable natural conditions, the Maximum Power Point Tracking (MPPT) method is required to extract the maximum power from the PV system. The adopted control is executed utilizing an Adaptive Sliding Mode Controller (ASMC) and the enhancement is actualized utilizing an Improved Pattern Search Method (IPSM). This work employs IPSM based optimization approach in order to command the underlying ASMC controller. The upper level decision determines the sliding surface for the adaptive controller. As a non-linear strategy, the stability of the adaptive controller is guaranteed by conducting a Liapunov analysis. On the practical side, MATLAB/Simulink is used as simulator for the controller implementation and coupling w... [more]

Waste solid residue from the hydrothermal extraction of pectin derived from sugar beet pulp was used as feedstock in the production of 5-hydroxymethylfurfural (5-HMF). The depolymerization of pectin-free sugar beet pulp (PF-SBP) to monosaccharides and their dehydration to 5-HMF were conducted in subcritical water using a batch reactor. The experimental design methodology was used in order to model the hydrothermal process and to optimize the operational parameters of the reaction, namely temperature and holding time. These parameters are required to achieve the highest yield of 5-HMF. The model predicts, in good agreement with experimental results (R2 = 0.935), an optimal yield of 5-HMF (of approximately 38% in relation to the cellulosic fraction content in the PF-SBP) at a temperature of 192.5 °C and a holding time of about 51.2 min. 5-HMF was successfully isolated from the reaction mixture using the liquid−liquid extraction method. The results are suitable for industrial upscaling an... [more]

The use of fossil resources for electricity production is one of the primary reasons for increasing greenhouse emissions and is a non-renewable resource. Therefore, the electricity generation by wind and solar resources have had greater applicability in recent years. Hybrid Renewable Energy Systems (HRES) integrates renewable sources and storage systems, increasing the reliability of generators. For the sizing of HRES, Artificial Intelligence (AI) methods such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) stand out. This article presents the sizing of an HRES for the Colombian context, taking into account the energy consumption by three typical demands, four types of wind turbines, three types of solar panels, and a storage system for the system configuration. Two optimization approaches were set-up with both optimization strategies (i.e., GA and PSO). The first one implies the minimization of the Loss Power Supply Probability (LPSP). In contrast, the second one conc... [more]

Cryogen spray cooling (CSC) could be applied clinically for the laser therapy of Ota’s nevus, a dermal hyperplastic pigmented disease with a morbidity rate of 0.1−0.6% in the Asian population. An accurate, efficient, complete simulation system that considers the entire spray cooling process, including cryogen flow in the tube nozzle, spray dynamics and internal phase change heat transfer (cold injury) in skin tissue, was established to determine suitable cryogen and cooling parameters. The optimum spray distances for R134a, R404A and R32 were determined to be 66.0, 43.1 and 22.5 mm, respectively. The corresponding maximum surface heat fluxes were 363.5, 459.9, and 603.6 kW∙m−2, respectively. The maximum surface heat flux of R32 with small spray distance was 1.66 times as large as that of R134a, indicating the potentially good cooling performance and precise targeted cooling of R32 during the laser therapy of Ota’s nevus. The cooling durations that caused cold injury of skin tissue were... [more]

This article presents the Reliability Assessment (RA) of renewable energy interfaced Electrical Distribution System (EDS) considering the electrical loss minimization (ELM). ELM aims at minimizing the detrimental effect of real power and reactive power losses in the EDS. Some techniques, including integration of Renewable Energy Source (RES), network reconfiguration, and expansion planning, have been suggested in the literature for achieving ELM. The optimal RES integration (also referred to as Distributed Generation (DG)) is one of the globally accepted techniques to achieve minimization of electrical losses. Therefore, first, the locations to accommodate these DGs are obtained by implementing two indexes, namely Index-1 for single DG and Index-2 for multiple DGs. Second, a Constriction Factor-based Particle Swarm Optimization (CF-PSO) technique is applied to obtain an optimal sizing(s) of the DGs for achieving the ELM. Third, the RA of the EDS is performed using the optimal location(... [more]

The adoption of electric vehicles is incentivized by governments around the world to decarbonize the mobility sector. Simultaneously, the continuously increasing amount of renewable energy sources and electric devices such as heat pumps and electric vehicles leads to congested grids. To meet this challenge, several forms of flexibility markets are currently being researched. So far, no analysis has calculated the actual flexibility potential of electric vehicles with different operating strategies, electricity tariffs and charging power levels while taking into account realistic user behavior. Therefore, this paper presents a detailed case study of the flexibility potential of electric vehicles for fixed and dynamic prices, for three charging power levels in consideration of Californian and German user behavior. The model developed uses vehicle and mobility data that is publicly available from field trials in the USA and Germany, cost-optimizes the charging process of the vehicles, and... [more]

As renewable energy installation costs decrease and environmentally-friendly policies are progressively applied in many countries, distributed generation has emerged as the new archetype of energy generation and distribution. The design and economic feasibility of distributed generation systems is constrained by the operation of the microgrid, which has to consider the uncertainty of renewable energy sources, consumption habits and electricity market prices. In this paper, a mathematical model intended to optimize the design and economic feasibility of a microgrid is proposed. After a search in the state-of-the-art, weaknesses and strengths of existing models have been identified and taken into account for building the present model. The present model should be seen as a basis on which other models can be built upon, hence a complete definition of the different sub-models is stated: uncertainty modelling, optimization technique, physical constraints and regulatory framework. One of the... [more]

Hot water supply is one of the leading consumers of energy in the building sector in cold climate areas. The use of woody biomass is effective in reducing CO2 emissions in hot-water supply systems. This report deals with a system that combines a wood pellet boiler (PB) and a heat pump system with CO2 (CO2HP) that is used in a facility for disabled people. The following research was conducted. The operation of a hybrid system combining a PB and CO2HPs was investigated. While operating the system, four specific operations were developed as countermeasures to save on costs and reduce system troubles while reducing CO2 emissions. The processes and results are introduced. Numerical simulations were carried out to optimize the operation. The hot water temperature, water volume, and hot water loads were simulated. The influence of the water volume ratio on the cost and primary energy consumption under the requirements for safe system operation was studied. The regional economic ripple effects... [more]

In this paper, we propose using particle swarm optimization (PSO) which can improve weighted k-nearest neighbors (PWKNN) to diagnose the failure of a wind power system. PWKNN adjusts weight to correctly reflect the importance of features and uses the distance judgment strategy to figure out the identical probability of multi-label classification. The PSO optimizes the weight and parameter k of PWKNN. This testing is based on four classified conditions of the 300 W wind generator which include healthy, loss of lubrication in the gearbox, angular misaligned rotor, and bearing fault. Current signals are used to measure the conditions. This testing tends to establish a feature database that makes up or trains classifiers through feature extraction. Not lowering the classification accuracy, the correlation coefficient of feature selection is applied to eliminate irrelevant features and to diminish the runtime of classifiers. A comparison with other traditional classifiers, i.e., backpropaga... [more]

This work focused on the application of a microchannel contactor for CO2 capture using water as absorbent, especially for the application of CO2-rich gas. The influence of operating conditions (temperature, volumetric flow rate of gas and liquid, and CO2 concentration) on the absorption efficiency and the overall liquid-side volumetric mass transfer coefficient was presented in terms of the main effects and interactions based on the factorial design of experiments. It was found that 70.9% of CO2 capture was achieved under the operating conditions as follows; temperature of 50 °C, CO2 inlet fraction of 53.7%, total gas volumetric flow rate of 150 mL min−1, and adsorbent volumetric flow rate of 1 mL min−1. Outstanding performance of CO2 capture was demonstrated with the overall liquid-side volumetric mass transfer coefficient of 0.26 s−1. Further enhancing the system by using 2.2 M of monoethanolamine in water (1:1 molar ratio of MEA-to-CO2) boosted the absorption efficiency up to 88%.

The accurate determination and dynamic adjustment of key control parameters are challenges for equivalent consumption minimization strategy (ECMS) to be implemented in real-time control of hybrid electric vehicles. An adaptive real-time ECMS is proposed for hybrid heavy-duty truck in this paper. Three efforts have been made in this study. First, six kinds of typical driving cycle for hybrid heavy-duty truck are obtained by hierarchical clustering algorithm, and a driving condition recognition (DCR) algorithm based on a neural network is put forward. Second, particle swarm optimization (PSO) is applied to optimize three key parameters of ECMS under a specified driving cycle, including equivalent factor, scale factor of penalty function, and vehicle speed threshold for engine start-up. Finally, combining all the above two efforts, a novel adaptive ECMS based on DCR and key parameter optimization of ECMS by PSO is presented and validated through numerical simulation. The simulation result... [more]

Ecological concerns on the climatic effects of the emissions from electricity production stipulate the remuneration of electricity grids to accept growing amounts of intermittent regenerative electricity feed-in from wind and solar power. Germany’s eager political target to double regenerative electricity production by 2030 puts pressure on grid operators to adapt and restructure their transmission and distribution grids. The ability of local distribution grids to operate autonomous of transmission grid supply is essential to stabilize electricity supply at the level of German federal states. Although congestion management and collaboration at the distribution system operator (DSO) level are promising approaches, relatively few studies address this issue. This study presents a methodology to assess the electric energy balance for the low-voltage grids in the German federal state of Baden-Württemberg, assuming the typical load curves and the interchange potential among local distributio... [more]

The optimal allocation and sizing of distributed generation (DG) resources are important in installing these resources, to improve the technical parameters of the network, including the power losses, voltage profile, and short-circuit level, as well as to increase economic factors. In this paper, a new multi-criteria algorithm and objective function are proposed for the optimal sizing and allocation of renewable and non-renewable DG resources simultaneously. The proposed algorithm is implemented on 63/20 kV substations at 20 kV levels. In the proposed objective function, all important technical and economic factors as well as important constraints, such as penetration level of DGs and budget constraint, are considered in a way that all factors are assigned to monetary values. Moreover, a new mathematical formulation is introduced for the allocation of renewable DG resources to reduce run-time optimization. The genetic algorithm (GA) is employed in the proposed algorithm to minimize the... [more]

In order to analyze the year-end water level of multi-year regulating reservoir of the cascade hydropower system, this paper studied the joint operation optimization model of cascade reservoirs and its solving method based on multi-dimensional dynamic programming, and analyzed the power generation impact factors of cascade system that contains multi-year regulating reservoir. In particular, taking the seven reservoirs in the middle and lower reaches of Yalong River as an example, the optimal year-end water levels of multi-year regulating reservoir under the multi-year average situation and different inflow frequencies situation were studied. Based on the optimal calculation results of multi-dimensional dynamic programming, the inflow frequency difference considered operation rule of year-end water level of Lianghekou reservoir was extracted using the least square principle. The simulation results showed that, compared with the fixed year-end water level in multi-year, the extracted rul... [more]

This paper proposes a predictive driver coaching (PDC) system for fuel economy driving for hybrid electric trucks using upcoming static map and dynamic traffic data. Unlike traditional methods that optimize over engine torque and brake to obtain a speed profile, we propose to optimize over driving modes of trucks to achieve a trade-off between fuel consumption and trip time. The optimal driving mode is provided to the driver as a coaching recommendation. To obtain the optimal solution, the truck dynamics are firstly modeled as a hybrid controlled switching dynamical system with autonomous subsystems and then a hybrid optimal control problem (HOCP) is formulated. The problem is solved using an algorithm based on discrete hybrid minimum principle. A warm-start strategy to reduce algorithmic iterations is used by employing a shrinking horizon strategy. In addition, an extensive analysis of the proposed algorithm is provided. We prove that the the coasting mode is never optimal given the t... [more]

Power plants based on organic Rankine cycle (ORC) are known for their capacity in converting low and medium-temperature energy sources to electricity. To find the optimal operating conditions, a designer must evaluate the ORC from different perspectives including thermodynamic performance, technological limits, economic viability, and environmental impact. A popular approach to include different criteria simultaneously is to formulate a bi-objective optimization problem. This type of multi-objective optimization (MOO) allows for finding a set of optimal design points by defining two different objectives. Once the optimization is completed, the decision-making analysis shall be carried out to identify the final design solution. This study aims to develop a decision-making tool for facilitating the choice of the optimal design point. The proposed procedure is coded in MATLAB based on the commonly used Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By providing t... [more]

Growth in application fields of unmanned aerial vehicles (UAVs) and an increase in their total number are followed by higher and higher expectations imposed on improvements in UAV propulsion and energy management systems. Most commercial vertical takeoff and landing (VTOL) UAVs employ a constant pitch propeller that forces a mission execution tradeoff in the majority of cases. An alternative solution, presented here, consists of the use of a variable pitch propeller. The paper summarizes experimental measurements of the propulsion system equipped with an innovative variable pitch rotor. The investigations incorporated characteristics of the rotor for no wind conditions and a new approach to optimize pitch settings in hover flight as a function of UAV weight and energy consumption. As UAV battery capacity is always limited, efficient energy management is the only way to increase UAV mission performance. The study shows that use of a variable pitch propeller can increase the maximal take... [more]

This article addresses the problem of hard switching caused by the change of equivalent load in a wireless power transfer (WPT) system based on a class E inverter. Based on the load-sensitive characteristics of the class E inverter, the coil structure is improved, and the self/mutual inductance compensation method of the transmitting coil is proposed to realize a wide range of soft switching. On the basis of fully considering the coupling relationship between the source and load coils, a coil structure with multiple coils in series on the primary side is proposed, and the cross-coupling relationship between the coils is analyzed in detail and simplified. The inverter parameters and coupling mechanism were adjusted by means of coil series reverse connection. Combined with the parameter influence law and the load equivalent principle of the class E inverter, the margin of soft switching at the inverter side was increased and the load offset correction was carried out. The soft-switching... [more]

The objective of this study is to investigate the performance characteristics of a small-sized R600a household refrigeration system that adopts a condenser outlet split (COS) ejector cycle under various operating and ejector geometry conditions. The coefficient of performance and pressure lifting ratio of the COS ejector cycle were analyzed and measured by varying the entrainment ratio, compressor speed, and nozzle exit position. The optimum nozzle exit position in the COS ejector cycle adopted to achieve the maximum cycle performance was proposed as a function of the compressor speed and entrainment ratio. The optimum nozzle exit position was 0 mm when the entrainment ratio and compressor speed were low, and it increased as the entrainment ratio and compressor speed increased owing to the associated internal pressure drop in the suction section.

The main goal of this paper is to prove that bi-objective optimization of high-pressure gas networks ensures grater system efficiency than scalar optimization. The proposed algorithm searches for a trade-off between minimization of the running costs of compressors and maximization of gas networks capacity (security of gas supply to customers). The bi-criteria algorithm was developed using a gradient projection method to solve the nonlinear constrained optimization problem, and a hierarchical vector optimization method. To prove the correctness of the algorithm, three existing networks have been solved. A comparison between the scalar optimization and bi-criteria optimization results confirmed the advantages of the bi-criteria optimization approach.