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This article proposes a framework as a remedial action scheme (RAS) for close to real-time system operation when system operator becomes aware of possibility of decentralized outages due to simultaneous attacks on several market retailers. The upper level of the framework is an offline RAS where system operator immediately implements a customized reconfiguration preventing the decentralized outages. Due to immediate implementation of upper-level reaction, it is possible to face decentralized congestions in the new topology having minimum reliance on the attacked market retailers. Since severity of congestions is less than that of outages, the lower level of the framework is implemented as an online RAS. In this level, eligible nonattacked market retailers are invited into a secondary market to compete for generation/consumption redispatch and contribute into alleviation of congestions with the purpose of increasing their income. The effectiveness of the proposed framework is validated on a well-known 136-bus distribution system.

Distinct characteristics of transmission and distribution power grids typically necessitate different control algorithms, especially at the primary control level where quick responses are required. Accordingly, various droop control schemes have been developed due to specific types of power grid impedances. Therefore, controllers at higher levels often have to be redesigned whenever a different power grid is considered, hence, incurring higher cost and effort. As a way to overcome that problem, in this work, a unified secondary controller using distributed control theory is designed for different droop schemes associated with distributed battery storage in different grid conditions. The control design follows the consensus theory, originally designed for multi-agent systems, to control the frequency and voltage at the point of common coupling (PCC), synchronize energy levels, and proportionally share active and reactive powers of battery storage systems. A sufficient condition for the upper bound of communication delays between storage systems is derived to ensure system stability. Several scenarios are studied using a modified IEEE 118-bus benchmark to support the theoretical results of the proposed approach.

Energy, building, and water networks are three interlinked critical infrastructures that need to be operated cooperatively to maximize the smart grid’s economic benefits. In this paper, a mixed-integer linear programming (MILP) formulation is proposed to approach the economic dispatch (ED) problem for smart grids embedded with interdependent water and energy networks. Energy management of various building applications is considered by intelligently controlling the indoor temperature during occupied and unoccupied hours. To optimize the demand of water distribution system, pump’s nonlinear scheduling and hydraulic factors and daily water usage of buildings are added to the proposed model. Piecewise linear approximation of univariate and bivariate nonlinear functions is used to convert the nonlinear problem to an MILP formulation. Several case studies were conducted to examine the impact of indoor temperature settings of the buildings, speed of pumps, battery efficiency, and end of day (EoD) battery and tank constraints on economic dispatch of the microgrid system.

Hybrid storage system composed of battery energy storage systems (BESSs) and supercapacitors is a promising solution to mitigate the high frequency power fluctuations of pulsed power loads (PPLs) in medium voltage DC (MVDC) shipboard power systems. Due to the presence of multiple storage units, a power sharing algorithm needs to be considered within the energy management system (EMS) in the shipboard power system. In this paper, an optimal power flow problem is formulated for MVDC shipboard power systems with hybrid energy storage systems. Battery energy storage systems (BESSs) and conventional generation units are enhanced with virtual resistive droop controllers to share the steady-state power fluctuations. Supercapacitors are enhanced with virtual capacitive droop controllers to share the high frequency fluctuations in the load. The optimal flow accounts for minimizing the operational cost of the generation units in the shipboard power system considering the constraints of network, load balance, voltage profile, and power/energy limits. Second-order cone programming (SOCP) relaxation is used to approximate the nonconvexity of the optimal flow formulation and necessary conditions for global optimality of the solution are discussed. Results confirm the effectiveness of the proposed formulation in load support and managing the energy between storage units.

This paper investigates the design and analysis of a robust nonlinear controller for voltage source converters (VSCs) connected to weak AC grids. Feedback linearization method is used to develop the control inputs that regulate the active power and output voltage of the grid-connected converter. The frequency-domain model of an LCL filter in $dq$ -frame is used to develop the nonlinear control blocks for small-signal stability analysis. Impact of phase-locked loop (PLL) is added to the control block through feedforward loops. It is shown that unlike vector controlled converters, the proposed controller is not negatively affected by the PLL gains and a broader range of operation is achieved. In addition, the designed controller is robust against sudden active power commands from 0 to 1 p.u., and is capable of fault ride through when AC grid is very weak. The robustness of the proposed controller is evaluated using eigenvalue analysis of the linearized closed-loop model and time-domain simulations of a grid-connected VSC in various cases.

Developing attack models is the first step to understand cyberattacks in smart grids and develop countermeasures. In this article, a three-level nonlinear programming formulation is proposed for false data injection (FDI) cyberattacks that could result in multiple transmission line congestions without being detected by conventional bad data detection (BDD) algorithms. The model is then converted to a mixed integer linear programming (MILP) formulation to guarantee a global optimum exists. A detection framework based on recursive least-square estimation (RLSE) is developed that can successfully detect the stealthy FDIs. The developed model with the detection framework is validated through various case studies in IEEE 118-bus benchmark.

Modern distribution power systems face more complex challenges compared to the conventional systems. A powerful technique to react to such challenges is network reconfiguration, which needs to be adapted with “recent” concerns of modern power systems. Hence, it is essential to determine optimal configurations “rapidly” for better time management of hour-ahead system's decision making. This paper proposes an optimization algorithm, named parallel frog migrating algorithm (PFMA), to rapidly identify the optimal system topology for hour-ahead systems operation. The significance of the proposed technique is the development of a fuzzy-based decision making unit to realistically evaluate the necessity of implementing the identified topologies. This will noticeably decrease the computational burden of system operator in analyzing the identified optimal configurations. The effectiveness of the proposed PFMA is validated on an unbalanced 136-bus distribution network containing wind turbine and photovoltaic (PV) distributed generation units (DGs). It is demonstrated that the presented PFMA is able to identify close to optimal solutions faster than the nonlinear solver of General Algebraic Modeling System (GAMS) software. More importantly, it is verified that the developed decision making mechanism effectively takes advantage of renewable DGs and reduces the necessity of network reconfiguration.

This article proposes a distributed consensus-based demand response control for permanent magnet synchronous generator (PMSG)-based wind turbines using standalone distributed battery energy storage systems (BESSs). The proposed controller cooperatively regulates the output power of individual wind turbines and BESSs in a wind farm to deliver active and reactive powers to the load in varying wind speed conditions. Capability curves of the wind turbines and BESSs are considered in the design. In addition, a virtual leader is designed to regulate the voltage and frequency of the combined PMSG-BESS units at the point of common coupling. Simulations on modified IEEE 14-bus power system are performed to validate the proposed design.

In this paper, a small-signal model of a single cell Polymer Electrolyte Membrane Fuel Cell (PEMFC) was developed based on state-space approach to study the effect of various operating conditions on the dynamic responses of the fuel cell. Dynamics of hydrogen, oxygen, and water partial pressure were considered in the modeling procedure. The transient responses of a single- and multiple cell PEMFC were also investigated as the operating parameters of air flow rate, fuel flow rate, temperature, anode/cathode relative humidity level, and electrical current were varied. Next, the studied PEMFC was integrated to the main grid using a boost DC/DC converter and a DC/AC converter. The stability of the overall system was tested through eigenvalue analysis in MATLAB, and several case studies were designed to examine the sensitivity of boost converter parameters and phase-locked loop (PLL) on the stability of the overall system. The analysis results were then validated on a 100 Watt simulated PEMFC in MATLAB Simscape Power System toolbox, and a set of optimum operating conditions were proposed.

Renewable energy sources normally provide low inertia, which allows a little time for controlling the system. The inertia emulation has recently been introduced for photovoltaic (PV) generation to fight against the small inertia and improve the energy efficiency. The main purpose of this article is to analyze the stability of a virtual inertia-based three-phase two-stage PV system for smart grid applications. Dynamics of DC/DC converter, DC/AC converter, AC side filter, virtual inertia controller, and controllers of the DC/DC and DC/AC converters are considered in the modeling procedure. Eigenvalue analysis is performed to evaluate the sensitivity of the design parameters on stability of a grid-connected virtual inertia PV system. Time-domain simulations using MATLAB/Simscape Power System toolbox are used to validate the eigenvalue analysis results.

This paper proposes a day-ahead market framework for congestion management in smart distribution networks. The presented scheme provides a platform for collaboration between distribution-level market operator (DMO) and data traffic operator (DTO) to alleviate congested feeders such that data transmission traffic between market participants is effectively managed in a smart grid. In addition, a decentralized mechanism is developed for collaboration of electric vehicle (EV) aggregators with common clients to take advantage of EVs not only as flexible loads but also as mobile distributed storage (MDS) for congestion management. Moreover, the proposed framework outlines an administrative action for distribution system operator (DSO) to support the market when the decentralized competitions among distributed generation (DG) aggregators and EV aggregators do not fully relieve a serious congestion. The proposed day-ahead congestion management scheme is validated on an unbalanced 136-bus distribution system massively integrated with wind turbine DGs (WTDGs), photovoltaic DGs (PVDGs), diesel-engine DGs (DEDGs), and EVs.

PurposeThis study aims to provide a better understanding of how information technology (IT) competency and knowledge management (KM) contribute to service supply chain (SSC) (coordination, collaboration and efficiency) practices in the hospitality industry.Design/methodology/approachDrawing on tourism businesses, this study tests the structural relationships of IT competency, KM and SSC. Structural equation modeling is performed to test the hypotheses. A survey of 494 hotels in Iran provided empirical evidence for the existence of interrelationships between multiple constructs.FindingsThe analysis demonstrated that IT competency is significantly associated with KM. Furthermore, SSC practices are found to be directly impacted by KM and IT competency.Originality/valueThis study unpacks the mechanism that operates between IT competency, KM and SSC and contributes to the academic research on SSC in the context of the hospitality industry.

Voltage source converter (VSC) based high-voltage direct current (HVDC) system is an emerging technology in high-power applications. Previous research has shown that VSCs, with commonly used vector current control (VCC) technique, cannot transmit more than 0.4 p.u. of active power when connected to a very weak ac grid. This paper presents a virtual synchronous generator (VSG) control strategy integrated with VCC to allow stable power transfer for very weak ac grid integration. Impedance analysis is used to analyze the designed controller in various scenarios. In addition, sensitivity analysis is performed to study the effect of virtual inertia gains on system stability. Time-domain simulation results using MATLAB/Simscape Power System toolbox show the effectiveness of the developed controller in very weak ac grid integration of VSC-HVDC systems.

This paper proposes a novel distributed control architecture for output power regulation of doubly fed induction generator (DFIG)-based wind turbines (WTs) with on-site battery energy storage systems (BESSs). The proposed distributed control architecture receives information from adjacent WTs+BESSs to control the DFIG's grid side converter (GSC) and the storage unit for output active/reactive power regulation and energy management purposes. The proposed method guarantees the equal active power sharing and energy management of WTs+BESSs in various wind speed conditions. A distributed controller is also designed to respond to the reactive power demand and share the reactive load demand between the GSC and BESS controllers based on their capacities. Furthermore, a controller is designed to account for the communication delays caused by the communication systems based on the IEEE standards. The proposed method is tested on the modified IEEE 14- bus power system with 10 WTs+BESSs

The adoption of renewable energy technologies (RETs) as a sustainable practice in the residential construction sector depends on promotional efforts. With a modeling-based contribution, this research aims to analyze advertising effectiveness in the context of RETs adoption regarding solar water heaters. The study is based on a survey of 398 Iranian citizens. A neural network analysis was employed to identify advertising effectiveness in terms of the AIDA framework. The results indicated that the neural network is able to predict the relationships among advertising effectiveness indices; namely attention, interest, desire in the RETs setting, and action. According to the neural network analysis, attention was found to be the most significant predictor of action, followed by interest and desire.

In this research, effects of magnetic field strength (400, 500 and 600 mT) and type of water (distilled and saline water) was studied on germination and growth characteristic of wheat seeds. Result...

Purpose Developing strategic relationships with third-party logistics (3PL) providers has long been one of the key challenges in automotive supply chains. The purpose of this paper is to propose a new approach for evaluation and indexing 3PL providers using the Kano model. Design/methodology/approach The statistical population used in this research comprises managers from the Iranian automotive industry. The Kano evaluation approach is used to analyze the data collected and to classify the criteria used in selection of the preferred 3PL providers. Findings The results suggest that the proposed framework, based on the Kano classification, can be a powerful tool for the automotive industry in evaluating 3PL providers. Moreover, the analyses indicate that 3PL providers need to improve their service offering in aspects that are to be found in the Kano model’s requirements, namely, must-be, one-dimensional and attractive. Originality/value This study contributes to the supply chain management literature by being the first to classify selection indices of 3PL providers in the automotive industry using the Kano model.

Flyback converters are widely used for photovoltaic (PV) application. However, the majority of research has been focusing on the control aspect of the converter where as stability, especially sensitivity of design parameters, has not been well studied. This paper presents the small-signal modeling of flyback converters in continuous conduction mode (CCM) using a moving average technique. MATLAB/Simulink is used to find the eigenvalues of the closed-loop system. The system stability is analyzed through the movement of eigenvalues due to changes in parameters of different components. The developed model demonstrates stability issues when certain parameters such as controller gains and passive components' values.

This paper presents a small-signal modeling of cascaded H-bridge converter connected to a solar photovoltaic (PV) system. By analyzing eigenvalues of state-space equations of the system, the closed-loop controller has been designed to control the DC-link voltage in each cell as well as the grid current. The sensitivity and stability margins of the system have been examined by changing the grid impedance, capacitors of DC-link, and parameters of the controller. Also, the dynamic response of the system was analyzed by applying a step change in the DC-link setpoints. To verify the performance and effectiveness of the controllers, simulation has been conducted in MATLAB/SIMULINK for a three-phase cascaded H-bridge with three cells in each phase.

This paper presents sub-synchronous resonance (SSR) mitigation of double-fed induction generator (DFIG)-based wind generation system. The system is series compensated by a capacitor in transmission model. A virtual generator control (VSG) is developed and supplemented to the grid side converter (GSC) of the DFIG to not only enhance the inertial response, but also to alleviate SSR. Two cases are designed to: 1) analyze the system stability under different compensation levels, and 2) test the sensitivity of parameters of VSG loop on system stability. The linearized small-signal model was developed on MATLAB/Simulink to validate the effectiveness of the proposed method. Sensitivity analysis is conducted to examine the impact of VSG gains on stability of series compensated DFIG-based system.

An impingement jet method was employed for extracting of sunflower seeds from sunflower heads (SHs). The method was based on holding SHs with a rotating plate and extracting the sunflower seeds with the help of pressurized air-jets. Artificial neural networks (ANNs) and response surface methodology (RSM) were used to model the effects of operational parameters of impingement air-jet on performance of preliminary model of the remover machine. The operational parameters were diameter of nozzle (ND), angle of impingement (AI), distance between nozzle outlet and sunflower head (DBNS), air pressure (AP) and rotational velocity of sunflower head (RV). The final ANN model, 3-5-1, successfully modeled the relationship between three operational parameters, ND, AI and RV with removing performance of machine (RPAJSSR) with R2of 0.98 and T value of 0.96. The RSM method was applied for three different locations of SHs at the optimum AP of 7 bar. The maximum value of RPAJSSR, (57%) was obtained for ND of 8 mm, AI of 30°, DBNS of 20 mm and RV of 10 rpm at side region of SH (SRSH). Also, the minimum value (4.49%) belonged to ND of 4 mm, AI of 30°, DBNS of 20 mm and RV of 15 rpm for central region of SH (CRSH).

In order to eliminate some problems of traditional and mechanical methods of separating sunflower seeds from the receptacles, a new method based on impingement jets was innovated. The effect of the seeds' location, reservoir pressure, nozzle diameter, and the distance between the two nozzles on the separating area of sunflower receptacle, in three different states including, static, linear movement of sunflower receptacle, and rotational movement of nozzles were examined. Also theoretical areas of covered region by the two nozzles in the three different states were calculated. The regions separated by impingement of the air-jet were photographed and the area of the separated regions was calculated based on image processing technique. Also, for the three states, power consumption of compressor was calculated. Moreover, in each state, response surface methodology was used to find the five best optimized points. In the static state, maximum and minimum values of area of separated regions in the central, middle, and side region of sunflower receptacle were equal to 2.63 and 1.39, 3.83 and 1.96, and 4.02 and 2.12 cm2, respectively. In the linear movement state, maximum and minimum values of area of separated regions in the central, middle, and side region of sunflower receptacle were equal to 9.78 and 5.72, 16.19 and 10.02, and 17.43 and 11.15 cm2, respectively. The corresponding values for rotational movement state were 9.33 and 5.14, 128.98 and 86.12, and 241.89 and 157.65 cm2, respectively. Obtained results by variance analyzing showed that in all three states and in each region, effects of independent input factors were significant at probability level of 1%. Also in all tests, no seed was observed to be damaged due to air-jet impinging.

Massive integration of converter-based renewable energy sources into power systems through weak AC grid has become a dilemma in recent years. This paper investigates the design of a robust nonlinear multi-input-multi-output (MIMO) controller for voltage source converters (VSCs) connected to weak AC grids. Feedback linearization method is used to find the controller equations and design the inputs to regulate the active power and output voltage of the converter. With this approach, the controller is designed in a way that the grid impedance impact on the stability of the converter system is significantly reduced. The robustness of the proposed controller is evaluated using time-domain simulations of a grid-connected VSC enhanced with the nonlinear controller in various case studies. The results illustrate a significant improvement compared to existing approaches.

Pulse width modulation (PWM) is the most commonly used technology for switching power electronics-based power converters in smart grids. However, implementing PWM in actual hardware is not as straightforward as it sounds. This paper develops a step-by-step procedure to implement PWM for single-phase and three-phase silicon carbide (SiC) converters using popular digital signal processing (DSP) boards from Texas Instruments (TI). The proposed model classifies the PWM implementation into multiple cascaded loops so that it can be understood easily from the electrical engineering point of view. The proposed step-by-step solution is then implemented on a C2000 F28069M LaunchPad development kit for single-phase and three-phase applications. An experimental setup on a 3.5 kW three-phase Silicon-Carbide (Sic) inverter was developed to validate the three-phase PWM implementation.

Improving the reliability and efficiency of microgrids to handle diverse load types will lead to more dependable electrical grids in small communities, reduce costs for both consumers and suppliers, and reduce carbon emissions. Better demand side management (DSM) has been proposed as a solution for creating more efficient m icrogrids a swell as limiting the need for increases in power generation capacity and transmission. This paper proposes a hardware implementation of DSM in an actual microgrid system to support grid needs. An algorithm for achieving DSM through load-leveling at the micro-level is presented and implemented on a physical microgrid and evaluated in order to create a Load-Leveling Trainer. A simulated case study, based on the electrical load needs of small communities in Bangladesh, is reviewed to prove that the Load-Leveling Trainer can be used to better balance electrical load demands.

In smart distribution networks, an essential responsibility of system operators is to effectively respond to the detected cyberattacks in order to prevent any possible blackout. This paper proposes a reaction framework for the distribution system operator (DSO) to respond to decentralized cyberattacks implemented on several distributed generation (DG) retailers, electric vehicle (EV) retailers, and demand response (DR) retailers. Due to the false data injections on the clients of DG / EV / DR retailers, wrong aggregated data will be submitted to the DSO. If a proper response is not provided, system has to rely on the targeted market participants which can result in congestion / blackout. As a result, we propose a real-time smart distribution network reconfiguration (RSDNR) framework for DSO to result in a system topology such that 1) minimum reliance on attacked retailers is required for system operation and 2) convenience of market participants is minimally affected by the administrative reaction of DSO. The effectiveness of the proposed scheme is validated on a well-known 136-bus distribution system modified with DGs and flexible loads which can provide DR.

Transmission system is one of the most important assets in secure power delivery. Recent advancements toward automation of smart grids and application of supervisory control and data acquisition (SCADA) systems have increased vulnerability of power grids to cyberattacks. Cyberattacks on transmission network, specifically the power transmission lines, are among crucial emerging challenges for the operators. If not identified properly and in a timely fashion, they can cause cascading failures leading to blackouts. This chapter tackles false data injection modeling from the attacker’s perspective. It further develops an algorithm for detection of false data injections in transmission lines. To this end, first, a bi-level mixed integer programming problem is introduced to model the attack scenario, where the attacker can target a transmission line in the system and inject false data in load measurements on targeted buses in the system to overflow the targeted line. Second, the problem is analyzed from the operator’s viewpoint and a detection algorithm is proposed using l1 norm minimization approach to identify the bad measurement vector in data readings. In order to evaluate the effectiveness of the proposed attack model, case studies have been conducted on IEEE 57-bus test system.

Purpose The application of automated systems is rapidly increasing in different industries and organizations. In this regard, computerized maintenance management systems (CMMS) using information technology play an important role in the automating production systems. The purpose of this paper is to investigate the impacts of CMMSs and relevant supportive organizational factors on the effectiveness of total productive maintenance. Design/methodology/approach This study is classified as a quantitative survey-based research using structural equation modeling. The scope of the study includes manufacturing companies in Iran. A total of 125 questionnaires from 60 companies were collected from January to March 2014 to help validate the conceptual model and test the hypotheses. Findings The results support the concept CMMSs positively relates to relevant supportive organizational factors (resource allocation, decision-making structure, senior management support, employees’ involvement and effective instruction) on the effectiveness of total productive maintenance. The relevant supportive organizational factors can also be seen as the predictors of CMMSs. Originality/value This study integrates the CMMSs and relevant supportive organizational factors in a robust model to examine the effectiveness of total productive maintenance. This study also examines the impacts of CMMSs and relevant supportive organizational factors on total productive maintenance which seems to not be done previously.

Interconnection of High Voltage Direct Current (HVDC) transmission systems to a weak AC grid has been a challenge in recent years. The main target of this paper is to provide a comprehensive review of the “converter control” approaches for: (1) the Line Commutated Converter (LCC)-based HVDC and (2) the forced commutated converter-based HVDC systems in weak AC grids. The control architecture for each HVDC technology (forced commutated and line commutated) is included. The stability limitations associated with HVDC systems, including LCC-HVDC, Voltage Source Converter (VSC)-based HVDC, and the Current Source Converter (CSC)-based HVDC, are elaborated. Moreover, the most recent control approaches for possible integration of LCC-HVDC and VSC-HVDC to very weak AC grids are introduced. Finally, the reliability modeling for each HVDC technology in weak AC grid integration is included for corrective and preventive reliability analysis.

This paper proposes a novel distributed control architecture for synchronization of the active/reactive power sharing, energy levels, frequency/voltage of distributed battery energy storage systems (BESSs) using inter-BESS communications. The local information of each BESS is exchanged with a few other neighboring BESSs to achieve a consensus. The consensus speed is significantly improved by introducing an inner control loop for energy levels. The droop frequency/voltage control is also added to regulate the active/reactive power sharing and the frequency/voltage of BESSs. Furthermore, self delays and communication delays are explicitly considered in the design. As a result, the derived consensus algorithms are fully distributed with fast consensus speed in both contexts of nonexistence and existence of time delays, which have not been addressed in the existing research for BESSs. To validate the design, several simulation case studies are carried out.

In this paper, consensus integral control is applied for energy storage in microgrids to synchronize the state-of-charge (SoC) and power levels of batteries with limited information exchange. Both local information (SoC and power level) and neighbors’ information (SoC and power level) will be fed into an integral control installed at every battery converter. The design is based on consensus control and takes into consideration of real-world battery coordination requirements, e.g., all batteries should work in the same charging or discharging mode. Compared with the consensus control in the existing literature for voltage consensus or battery SoC/power consensus, this paper offers a simple design. The major assumption of this paper is that each converter should possess an integral control. This assumption is valid since indeed integral controls exist if converters are equipped with secondary frequency control. The designed consensus control is validated by simulations on 14-bus microgrid and IEEE 57-bus power system. Simulation results demonstrate the effectiveness of the consensus integral control for variety modes of operation: 1) charging; 2) discharging; and 3) load variation.

This paper investigates the stability of a modular multi-level converter (MMC) based HVDC system connected to a weak ac grid. Impedance analysis is used to study the interactions between the weak ac grid and the converter. For this, the impedance of the MMC is first derived considering various outer- and inner-loop controllers. The Nyquist-stability criterion is then used to analyze the stability of the MMC connected to the weak ac grid for various case studies. The impact of circulating current controller on the stability of the MMC connected to the weak ac grid is also validated for two different types of outer-loop controllers. Finally, time-domain simulations are carried out using MATLAB/Simscape Power System toolbox to validate the analytical results.

Sunflower petal is one of the parts of the sunflower which has drawn attention and has several applications these days. These applications justify getting information about physical properties, mechanical properties, drying trends, etc. in order to design new machines and use new methods to harvest or dry the sunflower petals. For three varieties of sunflower, picking force of petals was measured; number of petals of each head was counted; unit mass and 1000-unit mass of fresh petals were measured and length, width, and projected area of fresh petals were calculated based on image processing technique; frequency distributions of these parameters were modeled using statistical distribution models namely Gamma, Generalized Extreme Value (G. E. V), Lognormal, and Weibull. Results of picking force showed that with increasing number of days after appearing the first petal on each head from 5 to 14 and decreasing loading rate from 150 g min−1 to 50 g min−1 values of picking force were decreased for three varieties, but diameter of sunflower head had different effects on picking force for each variety. Length, width, and number of petals of Dorsefid variety ranged from 38.52 to 95.44 mm, 3.80 to 9.28 mm and 29 to 89, respectively. The corresponding values ranged from 34.19 to 88.18 mm, 4.28 to 10.60 mm and 21 to 89, respectively for Shamshiri variety and ranged from 44.47 to 114.63 mm, 7.03 to 20.31 mm and 29 to 89 for Sirena variety. Results of frequency distribution modeling indicated that in most cases, G. E. V and Weibull distributions had better performance than other distributions. Keywords: Sunflower (Helianthus annus L.) petal, Picking force, Image processing, Fibonacci sequence, Lucas sequence

Purpose The purpose of this research is to explore the relationship between corporate social responsibility (CSR), brand image (BI) and brand equity (BE) in the banking industry of the Islamic Republic of Iran. Design/methodology/approach Using the deductive approach as the methodology and 213 valid questionnaires returned by customers of Iranian banks in four big cities of Iran, this study tests the relationship between CSR, BI and BE in eight hypotheses. The data were analyzed by the partial least squares method. Findings The results of this research show that CSR has a significant direct effect on BI. Also, BI has a significant direct effect on BE. Originality/value This research provides valuable insight for studying the relationship between CSR, BI and BE. The results of this study provide a better understanding of the role of CSR in customers’ attitudes and behaviors in the banking industry.

Purpose This paper aims to provide a quantitative basis to analytically determine the ranking of the brand personality of Adidas, Asics, Nike, Puma and Saucony brands among Iranian customers via a conventional multi-criteria decision-making (MCDM) method. Design/methodology/approach Data for determining the importance of evaluation criteria and ranking of brands are gathered by means of distributing questionnaires among a group of Iranian customers of sport shoes, as well as some industrial experts. The fuzzy analytic network process (FANP) was used to rank the brands with regard to dependencies between criteria and alternatives. Findings The results indicate that FANP is a capable method which provides invaluable insights for strategic marketing decisions in the sport product industry. Results show Adidas has the best performance in the sports shoe market compared to the other four brands. In this study, it was found that expertise sophistication was the most important criterion among Aaker’s five main criteria. Originality/value The value of this paper is applying FANP decision-making method for ranking sport shoe brands. This method has not been commonly used in the area of marketing, hence it is added to the pool of techniques used in ranking brands. In addition, evaluation and ranking of brands can be very useful for both academic research and practice. Researchers can benchmark the competences of each brand through evaluating them, and industrialists can extract the competitive advantages of the selected brands.

This paper presents impedance-model-based stability analyses of power synchronization control (PSC) and two types of vector controls used in voltage source converter-based high voltage direct current (VSC-HVDC) systems. The impedance model of a VSC with PSC is first derived. Stability analysis is then carried out using multi-input multi-output (MIMO) system analysis. As a comparison, power and angle transfer function-based analysis is also conducted. The impedance model-based stability analysis results are validated by the time-domain simulations. Impedance models of two types of vector controls are also derived for comparison. Effects of short circuit ratio (SCR), power transfer level, high-pass filters, and the PSC gain are demonstrated through analysis and real-time digital simulations in RT-LAB.

As digital interconnections of smart cities greatly enhance the quality of life for residents, they also introduce challenges related to cybersecurity that may adversely impact critical infrastructure. Smart cities must secure their critical infrastructures against cyberattacks. Water distribution is one of these infrastructures. In this paper, a bi-level optimization model is developed for cyberattacks that can result in physical consequence of multiple node failures in water networks. Unlike the existing research that considered random cyberattacks, the proposed cyber–physical attack model injects targeted false data into pumps’ measurements causing pressure head buildup in targeted nodes. In addition, the injected false data will ensure bypassing the existing water system’s state-estimation and bad data detection methods, a condition that was not considered in previously developed attacks. The findings indicate the minimum number of targeted pumps required to create the most severe cascading failures across the water network. The model will identify strategic pumps that are likely to be targeted by cyberattacks, and therefore should be given extra layers of protection by water authorities.