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The linkage between research and extension has always been considered as one of the most important and challenging issues in agricultural innovation systems. After the implementation of the agricultural extension new system, the linkage between these two sectors was considered as an important component. The primary objective of this survey research, conducted between 2021 and 2022, was to analyze the efficacy of linkage mechanisms facilitating the integration of research and extension within Iran's agricultural extension system. The statistical population of the study consisted of extension agents (N= 1113) in Alborz, Fars, Sistan & Baluchestan and Lorestan Provinces, out of whom 291 extension agents determined as sample using Krejcie and Morgan sampling table and proportionate stratified sampling technique. Data were collected through a questionnaire, validity of which was approved by a panel of experts and construct validity (AVE Index). Reliability of the questionnaire was approved by calculating the Cronbach's alpha and composite reliability (CR). The collected data were analyzed by SPSS22 and Smart PLS3 software. Results of prioritizing effective linkage mechanisms between research and extension indicated that "motivation" and "monitoring and evaluation" mechanisms, respectively, with the average of 3.85 and 3.80 were in the highest ranks and "structural-functional" and "participatory" mechanisms, respectively, with the average of 3.66 and 3.67 were in the lowest ranks. In addition, the results of confirmatory factor analysis confirmed that these mechanisms had eight components (i.e. motivation, participation, infrastructure-support, legal-policy, structural-functional, monitoring - evaluation, communication and training-empowerment), that "motivation" and "communication" components had the highest and lowest values of standard coefficient (0.964 and 0.786). Accordingly, it is advisable to enhance the connection between research and extension by focusing on: fostering motivation, fostering participation in the multilevel planning process, leveraging the capacities of the non-governmental sector, implementing training and empowerment initiatives, enacting structural reforms, ensuring provision of necessary facilities and infrastructure, and leveraging information and communication technology. [ABSTRACT FROM AUTHOR]

To overcome low output voltage of renewable energy sources such as photovoltaic arrays and fuel cells, a high step up SEPIC-based multi-input converter with dual coupled inductor is proposed. A new structure is presented in this paper, as an improved structure. This converter is based on combination of modified quadratic buck-boost converter, Dickson switched capacitor (DSC), and voltage multiplier modules (VMM). The high voltage gain can be achieved by adjusting the duty cycle and turn ratio of coupled inductor of VMM. This structure inherits all the advantages of the SEPIC converter such as step-up/down capability without inverting the polarity of regulated output voltage and using a bidirectional input port (in which an energy storage system (ESS) can be connected), and several unidirectional input ports. The load power can be flexibly divided among various power sources. Due to the buck-boost characteristics of the presented converter, it is suitable to charge-discharge the ESS. A coupled inductor (CI) is used to couple energy from input to the output equipped with the VMM. The usage of the DSC technique also enables the converter to obtain an additional double voltage gain while reducing the voltage stress on switches. Simulation results verify the performance of the proposed converter and feasibility of the control strategy. [ABSTRACT FROM AUTHOR]

In this paper, a new controller is proposed for lateral stabilization of four wheel independent drive electric vehicles without mechanical differential. The proposed controller has three levels including high, medium and low control levels. Desired vehicle dynamics such as reference longitudinal speed and reference yaw rate are determined by higher level of controller. Moreover, using a neural network observer and a fuzzy logic controller, a novel reference longitudinal speed generator system is presented. This system guarantees the vehicle’s stable motion on the slippery roads. In this paper, a new sliding mode controller is proposed and its stability is proved by Lyapunov stability theorem. This sliding mode control structure is faster, more accurate, more robust, and with smaller chattering than classic sliding mode controller. Based on the proposed sliding mode controller, the medium control level is designed to determine the desired traction force and yaw moment. Therefore, suitable wheel forces are calculated. Finally, the effectiveness of the introduced controller is investigated through conducted simulations in CARSIM and MATLAB software environments. [ABSTRACT FROM AUTHOR]

This paper presents a novel sliding mode controller (SMC) and its application in the lateral stability control of a 4-wheel independent drive electric vehicle. The structure of the SMC is modified and online-tuned to ensure vehicle system stability, and to track the desired vehicle motion references when an in-wheel motor fault happens. The proposed controller is faster, more accurate, more robust, and with smaller chattering than common SMCs chatter. The effectiveness of the introduced approach is investigated through conducted simulations in the CARSIM and MATLAB software environments. [ABSTRACT FROM AUTHOR]

The economic and resilient operation of power systems has always been one of the main priorities of energy systems. In spite of improvements in various fields of energy systems, especially power systems, the issue of resilience has become more important. For this purpose, this paper proposes a multiobjective optimization model to improve the economic performance of energy hub systems and improve the resilience of electrical consumers. Also, consumer welfare, which is a function of the energy not supplied index, is maximized over a 24-hour period by considering extreme weather conditions. The ε-constraint method is applied to solve the proposed model by transforming the multiobjective optimization problem into several single-objective optimization problems. The max-min fuzzy method is also used to select the optimal solution among the Pareto solutions. A sample hub system is made up of electrical, thermal, and gas loads, electrical and thermal energy sources, and storage systems employed as a test system. A group of actions is applied to improve the resilience of the system, which may be affected by outages caused by storms under the resilience response program (RRP). The results proved the efficiency of the proposed RRP in improving economics and resilience. [ABSTRACT FROM AUTHOR]

Highlights • Robust electricity procurement for renewable-based large consumers is studied. • Interval optimization method is proposed to model pool market price uncertainty. • Average and deviation costs are considered as conflict multi-objective functions. • The proposed multi-objective model is solved using weighted sum and fuzzy techniques. • Operation cost of large consumer is reduced based on peak load management. Abstract In this paper, a new optimization framework has been developed for optimal operation of large industrial consumer under time-of-use rate (TOU) of demand response program (DRP) considering pool market price uncertainty. In order to model mentioned uncertainty, interval optimization method has been implemented. Based on this approach, a bi-objective optimization problem with average and deviation costs as objective functions is generated to be minimized instead of a single objective function. So, the bi-objective problem is solved using weighted sum and fuzzy satisfying algorithms. In addition to mentioned algorithms, large consumer able to use TOU of DRP to be capable of shifting its demand from expensive intervals to off-peak intervals which can lead to reduce operating cost of large consumer. A sample model is simulated under GAMS optimization software within uncertainty of pool market price through mentioned algorithms and the results obtained from simulations revealed that in the case DRP is ignored by increasing average cost up to 4.32%, large consumer deviation cost representing uncertain of pool price has been reduced down to 87.22%. Moreover, in the case TOU is employed large consumer has paid 4.21% more to reduce uncertainty effect up to 85.43%. [ABSTRACT FROM AUTHOR]

• Presenting a MILP framework to reduce computation time and achieve the optimal solution. • Using advanced technologies (EVs, BDGs, BESSs, and DRP) simultaneously to enhance SDN resilience. • Utilizing a hybrid stochastic-IGDT method to model uncertainties of RESs, electricity price, EVs, and load. • Providing RA and RT strategies to face the uncertainty of load. Due to climate changes, the occurrence of low-probability but high-impact disasters such as hurricanes, earthquakes, thunders and etc are increasing. So in the occurrence of these disasters, the resilient operation of smart distribution networks (SDNs) needs to be more investigated by researchers. To address this challenge, in this paper, the optimal resilient operation of the SDN in the presence of renewable energy resources (RERs) and intelligent parking lots (IPLs) is investigated. A hybrid stochastic-IGDT approach is developed to handle the uncertainties of the proposed model. So to do this, the stochastic method is used to modeling of RERs generation, electricity price, and EVs (arrival time, departure time, and initial energy) uncertainties. Also, due to the high impact of load uncertainties on the resilient operation of SDN, the information gap decision theory (IGDT) approach is applied to mitigate the uncertainties of load. In this paper, backup diesel generators (BDGs), battery energy storage systems (BESSs), and demand response programs (DRPs) are suggested to improve the resilient operation of SDN. In order to show the efficacy of the proposed model, four case studies are evaluated on a modified IEEE-33 bus test system. The numerical results indicate, in the risk-averse strategy, the SDN is robust against 7.2% increasing active load by having 10% more operation cost, and the resiliency of the system decrease 3.05% for the worst scenario. On the other side, in the risk-taker strategy, with decreasing 7.4% in active load, the operation cost decrease 10%, and the resiliency of the system increase 4.93%. [ABSTRACT FROM AUTHOR]

In this paper, a new cascade multilevel inverter based on series connection of several basic units is proposed. The basic topology consists of 5 dc voltage sources and 12 switches. The required mathematical analysis consisting of voltage on switches, power losses and the values of dc voltage sources is provided. To verify the advantages of proposed topology, the suggested structure is compared with other multilevel inverter topologies in terms of used dc voltage sources, switches, voltage on switches and the number of on-state switches. The proposed structure uses the least numbers of dc voltage sources and switches compared to other multilevel inverters for the same number of levels. Also, voltage rating on the switches in the proposed topology is less than other topologies. These characteristics cause the weight, size and cost of proposed topology to be reduced. The proposed inverter is implemented using experimental setup. The experimental results verify the performance of proposed structure. [ABSTRACT FROM AUTHOR]