• Energy Research
• 2016-2025close
• other engineering and technologies close
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AbstractSmart cities consist of various energy systems and services that must be optimally scheduled to improve energy efficiency and reduce operation costs. The smart city layout comprises a power distribution system, a thermal energy system, a water system, and the private and public transportation systems. Additionally, several new technologies such as reconfiguration, regenerative braking energy of the metro, etc. are considered. This study is one of the first to consider all these technologies together in a smart city. The proposed power distribution system is a grid‐connected hybrid AC–DC microgrid. The biogeography‐based optimization algorithm was utilized to seek the best solution for scheduling micro‐turbines, fuel cells, heat pumps, desalination units, energy storage systems, AC–DC converters, purchasing power from the upstream, distributed energy resources, and transferring power amongst electric vehicle parking stations and metro for the next day. Also, the reduced unscented transformation layout was used to capture the system's uncertainty. The suggested layout is implemented on an enhanced IEEE 33‐bus test system to show the efficiency of the suggested method. The results show that costs and environmental pollution are reduced. By comparing the proposed smart city with other studies, the efficiency and completeness of the proposed smart city are shown.

Abstract This work shows work flows supported by experimental work to analyse the efficiency of a plasma system in biomass conversion processes. The most common set of problems encountered when using biomass-to-energy (BTE) processes relate to tar formation and product gas composition. However, using plasma technology to convert biomass provides a solution because it unlocks more energy than can be achieved by other BTE systems by using a heat supply derived from electricity. The research presented in this paper focuses on the conversion of biomass to chemical energy (in gaseous form) with the aid of the electrical energy supplied by a water-cooled nitrogen plasma torch. The authors conducted a series of experiments in a continuous pyrolysis set up in which wood pellets were converted to syngas in a small-scale laboratory nitrogen plasma torch reactor with a maximum power supply of 15 kW. The efficiency of the process was measured in terms of the carbon conversion to all product gases which changed from 43 to 77%, at temperatures ranging from 400 °C to 1000 °C respectively. The combined carbon monoxide and hydrogen mole concentration in the product gas (without nitrogen) was 86% at 1:1 ratio for all temperatures studied. Syngas yield increased with increase in temperature. The overall biomass conversion obtained increased from 46% to 82% for the temperatures 400 °C to 1000 °C respectively, with the balance comprising carbon-rich solid residue and liquid. The work flow shows that a plasma system can get to high temperatures but work is also degraded in the overall process. Exergy analysis shows that the work lost by the overall process decreases with increase in process temperature.

Light sources are being competitive in the current market. Several types of these products have been widely used in the last two decades. They play a major role on the low voltage network as they produce and inject undesired noise onto the transmission lines of the PLC channel. This noise can be of a serious and negative effect when using the power line communications system to control the automatic switching of lamps in residential areas and public places. The main colour low energy indoor light sources that exist in the market, such as, LEDs and CFLs have been tested for the noise generation on the PLC channel and the results are analyzed and shown in this study. A mathematical analysis of LED bridge rectifier is introduced in this study.

The paper discusses an application of generalised additive models (GAMs) in predicting medium-term hourly electricity demand using South African data for 2009 to 2013. Variable selection was done using least absolute shrinkage and selection operator (Lasso) via hierarchical interactions, resulting in a model called GAM-Lasso. The GAM-Lasso model was then extended by including tensor product interactions to yield a second model, called GAM- -Lasso. Comparative analyses of these two models were done with a gradient-boosting model to act as a benchmark model and the third model. The forecasts from the three models were combined using a forecast combination algorithm where the average loss suffered by the models was based on the pinball loss function. The results showed significantly improved accuracy of forecasts, making this study a useful tool for decision-makers and system operators in power utility companies, particularly in maintenance planning including medium-term risk assessment. A major contribution of this paper is the inclusion of a nonlinear trend. Another contribution is the inclusion of temperature based on two thermal regions of South Africa.

AbstractThis work presents a theoretical numerical study of the bioconvection flow of Prandtl–Eyring nanofluid through a stretching cylinder with gyrotactic microorganisms. The mathematical model developed also incorporated the inclined magnetic field and heat generation effects. Further, stratification conditions are considered at the boundary of the stretched cylinder. The described flow problem conducting coupled high‐order partial differential equations (PDEs) is first reduced to the nonlinear system of ordinary differential equations (ODEs) by introducing suitable mathematical transformations. The resulting highly nonlinear flow equations are treated numerically by applying the shooting method. A comparison of the adapted method with previously reported data is also made to validate the presented results. The comparisons are in excellent agreement. The individual effect of controlling flow parameters/numbers on the flow profiles and physical quantities of engineering interest are represented graphically with physical descriptions. The significant results of the present analysis revealed that a rise in bioconvection Rayleigh number, thermal Grashof number, and angle of inclination boosts the velocity profile. The study shows that thermal stratification, mass stratification, and motile density stratification parameters diminish the temperature, concentration, and microorganism profiles, respectively. The nondimensional Sherwood number is decelerated significantly by thermophoresis and mass stratification parameters.

Modelling of electrical consumption has been used to assist utilities for short and long term planning of electrical production. More recently, electrical consumption modelling has been employed to plan and evaluate demand side management actions aimed at optimising the electrical consumption in various sectors. Based on data availability and on the application, a choice is generally made between using a statistical or engineering model, where trade-offs between accuracy and flexibility have to be decided. A statistical physically-based model for electrical demand of domestic water heater was developed aiming to combine advantages of both statistical and engineering methods. This was made possible by modelling the elements of the energy balance equation of a water heater with statistical models, achieving good results when compared to a monthly average model. The backbone of the electrical demand model is the water draw pattern, influencing both the modelled water heater energy consumption and efficiency. In this paper, probabilistic and autoregressive time series water draw models are described and integrated in a statistical physically-based model for electrical demand of a domestic water heater. The results show that both a generalised and specific autoregressive water draw models result in a better electrical model than the probabilistic water model when integrated in the overall electrical model provided that the appropriate seasonal autoregressive periods are selected.

As a consequence of energy issues and societal dilemmas, building insulation like the eco-block technology has proven its usefulness to reduce greenhouse gas emissions, improve energy security and enhance the living conditions of building occupants. In Mauritius, the eco-block building material was introduced to improve the energy efficiency of conventional buildings. As observed, limited people's knowledge, poor communication with developers and lack of support from policymakers slow the adoption of the building technology. Mauritian residents are the important stakeholders as they are the final decision-makers of the building insulation. Given recent studies reported that green building adoption is rather psychological than technical, the research makes an original contribution to the literature by extending two consistent psychological frameworks (technology of acceptance model and theory of planned behaviour) and proposing a new framework for assessing the unexplored predictors on eco-block building adoption. A survey questionnaire was forwarded to Mauritian residents through the purposive sampling method to collect data, where 283 responses were useful to undergo structural equation modelling. The results disclosed that attitudes, perceived usefulness, social norm, perceived behavioural control, personal innovativeness, energy concern and price sensitivity have an impact on the acceptance of the eco-block building. Contrarily, subjective knowledge and organisational trust have no influence on the adoption intention. Instead, organisational trust affects behavioural intention indirectly through perceived usefulness. The outcome of this research can serve as a roadmap for relevant stakeholders to promote eco-block building usage in Mauritius.

Frequency of supply is an important aspect of electrical power system. Active power balance and frequency control are important tasks in the daily management of a power system. Due to variation in power demand as a result of load changes based on consumer usage, resultant change in frequency impacts on power system operation. The phenomena i.e. load fluctuation creates a burden on the generator prime mover. When the load demand is greater than the generation, generator speed drops, thus initiating a drop-in frequency. An unstable power system condition could lead to generator falling out of synchronism or overheating machines or malfunction of equipment. Should the frequency drop below certain limits automatic load shedding will occur. Minimization of frequency error will enable the matching of frequency system generation to load frequency to nullify sudden blackouts and system imbalance. Increasing economic pressures for power system efficiency and reliability have led to a requirement for maintaining system frequency and power flows closer to specified values as much as possible. Therefore, in a modern power system, load frequency control plays a fundamental role, as a help service, in supporting and providing better conditions for the electricity trading. This paper presents a case study of PID controllers that can withstand load variations and produce improved functionality outputs (results) in a power system. The PID controller is incorporated with a trignometric function of a fourier series to mimimise the change in frequency. To ascertain the proficiency of the proposed technique, different versions of the PID controller in operation was undertaken. The proposed adaptive controller design provided the best results in terms of both frequency deviation and speed drop.