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Mobile edge computational power faces the difficulty of balancing the energy consumption of many devices and workloads as science and technology advance. Most related research focuses on exploiting edge server computing performance to reduce mobile device energy consumption and task execution time during task processing. Existing research, however, shows that there is no adequate answer to the energy consumption balances between multi-device and multitasking. The present edge computing system model has been updated to address this energy consumption balance problem. We present a blockchain-based analytical method for the energy utilization balance optimization problem of multi-mobile devices and multitasking and an optimistic scenario on this foundation. An investigation of the corresponding approximation ratio is performed. Compared to the total energy demand optimization method and the random algorithm, many simulation studies have been carried out. Compared to the random process, the testing findings demonstrate that the suggested greedy algorithm can improve average performance by 66.59 percent in terms of energy balance. Furthermore, when the minimum transmission power of the mobile device is between five and six dBm, the greedy algorithm nearly achieves the best solution when compared to the brute force technique under the classical task topology.

The decarbonization of transport and heating will introduce uncertain smart appliance growth in the power system, which fundamentally challenges traditional network pricing. In this paper, a new long-term distribution network charging is proposed to accommodate uncertain load growth. Instead of using fixed a load growth rate (LGR), it adopts a fuzzy model, developed based on a set of projected deterministic LGRs and confidence levels. This fuzzy model is incorporated into the pricing model through $ {\alpha } $ -cut intervals. In order to improve computational efficiency, an analytical pricing approach is introduced. The vertex extension approach is used to build charge membership functions. Thereafter, a common defuzzification approach, center of gravity, is employed to defuzzify membership functions in order to generate deterministic charges. The new approach is benchmarked with two existing standard charging methods on a practical U.K. high-voltage distribution system. Results show that it is effective in capturing the uncertainty in load growth.

Owners of power systems incur high costs and investments to transfer the electrical power to customers in the distribution network. Hence, the reliability of the distribution network is particularly important in the lives of customers. Natural disasters such as hurricane and earthquake or sudden faults may threaten the reliability of the distribution network. Therefore, the focus of this study is to provide a new formulation for the distribution system resilience and voltage security. To improve the mentioned objectives in the automated distribution system, the concept of distribution feeder reconfiguration (DFR) is used in this study. Due attention of distribution network resilience and voltage security issues, energy not supplied and voltage stability index along with power loss are considered as objective functions. According to the increase of distributed generators in the distribution network, the effect of these units is considered in the DFR problem. An improved particle swarm optimization is presented to solve the complex and non-convex DFR problem. The proposed algorithm is tested into two distribution systems including IEEE 33 and 70-node.

Abstract Background Parabolic Trough Solar Collector (PTSC) is one of the most popular and an effective device that converts solar radiation into a heat or useful energy. However, it suffers from high temperature gradient and low thermal efficiency. The solution for this problem is to use new advanced coolants (hybrid nanofluids) in order to enhance PTSC's thermal efficiency. Methods A numerical analysis on the thermo-hydraulic performance of a PTSC receiver's tube equipped with conical turbulators is presented. The Navier-Stokes equations are solved using Finite Volume Method (FVM) coupled with Monte Carlo Ray Tracing (MCRT) method. The flow and thermal characteristics as well as entropy generation of the PTSC's receiver tube are investigated for three hybrid nanofluids (Ag-SWCNT, Ag-MWCNT, and Ag-MgO) having a mixing ratio of (50:50) dispersed in Syltherm oil 800, Reynolds number (5000 to 100,000) and fluid inlet temperatures (400 to 650 K). Significant findings The conical turbulators effectively augmented the thermal performance by 233.4% utilising Ag-SWCNT/Syltherm oil instead of pure Syltherm oil. The performance evaluation criterion is found to be in the range of 0.9–1.82. The thermal and exergetic efficiencies increased by 11.5% and 18.2%, respectively. The maximum decrement in the entropy generation rate and entropy generation ratio are 42.7% and 33.7%.

A review of technologies surrounding the thermal management system of the modern diesel engine with increased attention on fuel consumption is presented. A system-based approach has been adopted, looking at the interaction with other key systems. Previous innovation has aimed at reducing the power consumption of the cooling system or incorporating different cooling strategies and improving the engine warm-up rate for improved fuel consumption by higher operating temperatures. Electrical pumps can operate independently of the engine speed, and precision cooling and nucleate boiling have improved the heat transfer within the engine, reducing coolant flow requirements by 90 per cent. Improved warm-up rates have been demonstrated by using reduced thermal inertia or energy recovery systems either simulated on the test rig or through heat exchangers with exhaust gases. The resultant reduction in the fuel consumption is a result of various effects of the temperature on both the lubricating system and the combustion process. Despite difficulties in accurately measuring the engine friction, studies suggest that an increase in the engine temperature from 50°C to 80°C reduces the engine friction by 44 per cent because of 67 per cent lower oil viscosity. Simultaneous reduction in the emissions of nitogen oxides (NO x) and the fuel consumption of 13.5 per cent and 0.7 per cent respectively have been achieved by including the engine thermal system in the calibration procedure. However, in-cylinder data needs to be studied to understand fully the mechanisms involved. Hotter engine temperatures reduce ignition delay, making combustion occur earlier in the cycle, which has a positive effect on the fuel consumption but a negative effect on the NO x emissions. Engine thermal management requires a system-based approach if the effects are to be fully understood but offers potential as an additional parameter in engine calibration.

Abstract Electricity dispatch is a difficult optimisation problem that aims at minimising total fuel cost while satisfying system power demand and certain thermal unit constraints. Modelling valve point effects, multiple fuel options or transmission losses brings non-convexity and non-smoothness into the mathematical models. This paper proposes mathematical programming-based models for valve point effects, multiple fuel options and transmission loss problems respectively. Mathematical programming leads to robust and rigorous optimisation methods for these problems. The applicability of the proposed methods is demonstrated through a number of case studies. For all the case studies, the corresponding methods identify power schedules at least as good as or better than the best known in literature.

Abstract In the context of climate change, global industrialised nations are grappling with transforming energy networks to support a low carbon future. Using an energy justice framework this work aims to understand holistic outcomes of one low-carbon energy network intervention: demand-side response enacted on domestic heat pumps. By exploring participants’ lived experience of a pilot project, from recruitment to installation and use, this work reveals how injustices were reduced, introduced and amplified. Choice, consent, cost, comfort, disruption, and control are highlighted as key aspects of interest when considering the distributive, procedural, and recognition implications of this domestic innovation. For a net reduction of energy injustices to be realised, we highlight the need for project designers to work in partnership with end users to optimise the benefits for the household and the electricity system. Whilst this is a UK study, the themes and findings are internationally applicable for interventions that aim to harness the flexibility of heating, the largest global energy end-use.

Utilising the theory of the ‘Energy Law and Policy Triangle’, this article analyses the consequences of not having a comprehensive national energy policy, whereby economics, environment and politics are all included. While focusing on two of the three points of the Triangle—economics and environment—the Australian 2015 Energy White Paper has not incorporated the third fully—the politics of energy security—and environmental protection is also inadequate. The article argues that the absence of a comprehensive national energy policy leaves Australia open to piecemeal, reactive approaches to critical issues. Using the example of the South Australian Nuclear Fuel Cycle Royal Commission it highlights the implications of a federal policy vacuum, as whatever decisions the South Australian Government takes on waste disposal, it is unclear whether the Australian Government will support them. It recommends the development of a comprehensive policy, clearer links between aspects, and to apply strategic environmental assessment to significant environmental effects of policy.