Renewable energy adoption is a complicated process that is influenced by a multitude of different factors. Previous studies seldom examine the social acceptance of renewable energy from the Chinese perspective in Shandong province. To bridge this gap, comprehensive research is crucial to find the public attitude towards renewable energy. We extended the theory of planned behavior by incorporating three additional factors, i.e., risk perception, environmental concern, and belief about renewable energy costs. A questionnaire survey was conducted in the four major cities of Shandong province. The Logit model was used to determine possible factors affecting public acceptance. Research findings reveal that residents significantly support renewable energy regarding its positive environmental impact. Individuals’ education, personal income, awareness and belief of renewable energy consumption cost positively affect their intention to utilize renewable energy, as the willingness to pay increases with an increase in these factors while decreasing with individuals’ age. Young people with higher education and income are willing to pay extra for green energy. Research results emphasized the importance of enhancing public awareness and highlighting renewable energy benefits to win public acceptance of renewable energy deployment.

With the rising load demand and power losses, the equipment in the utility network often operates close to its marginal limits, creating a dire need for the installation of new Distributed Generators (DGs). Their proper placement is one of the prerequisites for fully achieving the benefits; otherwise, this may result in the worsening of their performance. This could even lead to further deterioration if an effective Energy Management System (EMS) is not installed. Firstly, addressing these issues, this research exploits a Genetic Algorithm (GA) for the proper placement of new DGs in a distribution system. This approach is based on the system losses, voltage profiles, and phase angle jump variations. Secondly, the energy management models are designed using a fuzzy inference system. The models are then analyzed under heavy loading and fault conditions. This research is conducted on a six bus radial test system in a simulated environment together with a real-time Power Hardware-In-the-Loop (PHIL) setup. It is concluded that the optimal placement of a 3.33 MVA synchronous DG is near the load center, and the robustness of the proposed EMS is proven by mitigating the distinct contingencies within the approximately 2.5 cycles of the operating period.

Accurate, ubiquitous and reliable navigation can make transportation systems (road, rail, air and marine) more efficient, safer and more sustainable by enabling path planning, route optimization and fuel economy optimization. However, accurate navigation in urban contexts has always been a challenging task due to significant chances of signal blockage and multipath and non-line-of-sight (NLOS) signal reception. This paper presents a detailed study on environmental context detection using GNSS signals and its utilization in mitigating multipath effects by devising a context-aware navigation (CAN) algorithm that detects and characterizes the working environment of a GNSS receiver and applies the desired mitigation strategy accordingly. The CAN algorithm utilizes GNSS measurement variables to categorize the environment into standard, degraded and highly degraded classes and then updates the receiver’s tracking-loop parameters based on the inferred environment. This allows the receiver to adaptively mitigate the effects of multipath/NLOS, which inherently depend upon the type of environment. To validate the functionality and potential of the proposed CAN algorithm, a detailed study on the performance of a multi-GNSS receiver in the quad-constellation mode, i.e., GPS, BeiDou, Galileo and GLONASS, is conducted in this research by traversing an instrumented vehicle around an urban city and acquiring respective GNSS signals in different environments. The performance of a CAN-enabled GNSS receiver is compared with a standard receiver using fundamental quality indicators of GNSS. The experimental results show that the proposed CAN algorithm is a good contributor for improving GNSS performance by anticipating the potential degradation and initiating an adaptive mitigation strategy. The CAN-enabled GNSS receiver achieved a lane-level accuracy of less than 2 m for 53% of the total experimental time-slot in a highly degraded environment, which was previously only 32% when not using the proposed CAN.

This paper presents a subharmonic-based brushless wound rotor synchronous machine (BL-WRSM) topology with permanent magnet-assisted (PMA) and consequent-pole (CP) rotor structures to achieve better torque characteristics as compared to the conventional subharmonic-based brushless WRSM. The proposed topologies use the conventional high-efficient subharmonic field excitation technique to achieve a brushless operation and a lower volume of permanent magnet (PM) to achieve better average, starting, maximum, and minimum torques and lower torque ripple. A four-pole, twenty-four-slot (4-pole/24-slot) machine with conventional, PM-assisted (PMA), and consequent-pole (CP) rotor structures are developed in a JMAG-Designer 20.1 environment to carry out two-dimensional finite element analysis (2D-FEA). The developed machines are used to validate the operation and achieve electromagnetic and electromechanical performances of the proposed subharmonic-based BL-WRSM topologies with better torque attributes.