Meeting the rising energy demand and limiting its environmental impact are the two intertwined issues faced in the 21st century. Governments in different countries have been engaged in developing ...regulations and related policies to encourage environment friendly renewable energy generation along with conservation strategies and technological innovations. It is important to develop sustainable energy policies and provide relevant and suitable policy recommendations for end-users. This study presents a review on sustainable energy policy for promotion of renewable energy by introducing the development history of energy policy in five countries, i.e., the United States, Germany, the United Kingdom, Denmark and China. A survey of the articles aimed at promoting the development of sustainable energy policies and their modelling is carried out. It is observed that energy-efficiency standard is one of the most popular strategy for building energy saving, which is dynamic and renewed based on the current available technologies. Feed-in-tariff has been widely applied to encourage the application of renewable energy, which is demonstrated successfully in different countries. Building energy performance certification schemes should be enhanced in terms of reliable database system and information transparency to pave the way for future net-zero energy building and smart cities.
This study presents a novel mathematical formulation to describe repairable components reliability model based on their bathtub curve and repair rate behaviour. The model is derived from the concept ...of Markov chain, which allows defining component's lifetime process. In addition, the formulation brings components’ degradation quantification. The proposed approach presents a pathway to develop an accurate reliability model for reliability assessments as shown in the presented case study.
In order to provide a reliable service and supply the demand most of the time, all generators in a power grid should be subjected to an effective maintenance plan. The smarter the maintenance ...performed could result in a better performance of the system. However, a challenge is to minimise maintenance costs that do not compromise the benefits. Considering these facts, this study presents a reliability-based smart-maintenance approach of generators to compute the net-maximum economic benefit. The approach is derived from Kijima model type I to characterise the impact of maintenance over the component's virtual age, and Markov chains to model the component's lifetime. To achieve a more realistic model, generators' failure and repair rates are considered time-dependent variables. Then, the optimum preventive maintenance schedule is obtained by using an advanced algorithm named accelerated quantum particle swarm optimisation in combination with sequential Monte Carlo simulation. The effectiveness of the approach is investigated through a case study with four different scenarios: (i) no preventive maintenance plan, (ii) yearly periodic preventive maintenance, (iii) reliability-centred maintenance and (iv) smart maintenance. The results suggest that the approach is convenient for power system generators and delivers a significant knowledge contribution in the area of maintenance.
With the advancements in information and communications technologies, new teaching approaches arise. In this context, project-based learning (PBL) and science, technology, engineering, the arts, and ...mathematics model (STEAM) emerge as the most popular in the education field, attributed to their efficacy on students' learning capacity. This article contributes with a new teaching-learning approach that combines the STEAM model and PBL (called STEAM-PBL) to address the student's difficulties that may present in the topic of Pascal's principle. The proposed approach is validated following an experimental design considering control and experimental groups. The metrics used to measure academic performance are the Dellwo index, while the Rasch model is used to quantify the effectiveness of the evaluation instrument. In addition, the proposed approach's acceptance is quantified through Cronbach's Alpha factor. The results reveal that STEAM-PBL has the potential to enhance the teaching-learning process while keeping the student motivated during the lectures.
Electric vehicle growth is creating a larger share of mobile load in power systems. This can affect system stress in potentially constrained areas of the grid, during a period that may already be an ...emergency. This paper proposes a novel model to reflect the behavior and spatiotemporal charging demand of electric vehicles during a natural disaster evacuation. The paper integrates the model in an algorithmic approach enabling operators to anticipate grid impacts from the charging of electric vehicles during a wildfire and subsequent evacuation. Geospatial visualization of evacuation charging demand provides a means to enhance operator awareness of spatiotemporal impacts and indicate critical areas of the grid for proactive mitigation. Results for a case study using the RTS-GMLC test system suggest that electric vehicle evacuation can result in dynamic changes to load patterns, adding stress to network components with the most significant load changes occurring during the initial evacuation period.
Based on orbital angular momentum (OAM) properties of Laguerre-Gaussian beams LG(p,ℓ), a robust optical encoding model for efficient data transmission applications is designed. This paper presents an ...optical encoding model based on an intensity profile generated by a coherent superposition of two OAM-carrying Laguerre-Gaussian modes and a machine learning detection method. In the encoding process, the intensity profile for data encoding is generated based on the selection of
and
indices, while the decoding process is performed using a support vector machine (SVM) algorithm. Two different decoding models based on an SVM algorithm are tested to verify the robustness of the optical encoding model, finding a BER =10-9 for 10.2 dB of signal-to-noise ratio in one of the SVM models.
•A design-framework approach for the Monte-Carlo based PSO optimal reliability planning of a wind-PV-tidal RE DGs which are deployed throughout a distribution network based on size and location that ...maximizes reliability at low cost, i.e. EENS minimization.•Utilization of an integrated reliability assessment based on the system's state within the optimization method. The system's state calculation considers the events’ stochastic nature and includes the evaluation of the states of RE DG and components via probabilistic models, as well as time-dependent models for RE, grid supply, and load demands.
Distributed generation is essential for smart distribution systems. This prospect mainly depends on the efficient use of renewable resources. Therefore, it is compelling to provide an optimum design framework that allows a thorough modeling to select the most convenient size, location, and renewable energy combination that maximize system reliability on a distribution network. This paper presents an optimization-based framework to design a distributed generation system by incorporating an optimal reliability assessment with wind, solar, and tidal energies. The network planning exercise considers the stochastic nature of the network's state by including time-series models and hourly-based analysis to accurately determine the reliability indexes. Historical meteorological data has been used to model and deploy a set of renewable energy distributed generators which maximize reliability in a 37-bus primary-distribution network. Due to the probabilistic modeling of the system's components, a Sequential Monte-Carlo simulation is used to manage reliability evaluation at the network level. Although large reductions on energy-not-supplied are expected, it is shown that cost and other performance indexes do not follow the same trend, and project selection requires some compromise between cost and performance.
This paper aims to present a robust algorithm developed that aims to minimize the number of sensor nodes in a WSN using three quantum-behaved swarm optimization techniques based on Lorentz (QPSO-LR), ...Rosen-Morse (QPSO-RM), and Coulomb-like Square Root (QPSO-CS) potential fields. The algorithm aims to allocate the minimum number of wireless sensors in forested areas without losing connectivity in an environment with a high penetration of vegetation. The proposed approach incorporates a propagation model that locates the sensor nodes, calculates the approximate separation distance between each one, verifies Line of Sight (LOS) compliance, and avoids considerable intrusions in the first Fresnel zone. The results validate the robustness of the quantum-behaved swarm optimization algorithms in comparison to traditional particle swarm optimization (PSO).
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