Energy Disaggregation for SMEs using Recurrence Quantification Analysis

Energy disaggregation determines the energy consumption of individual appliances from the total demand signal, which is recorded using a single monitoring device. There are varied approaches to this problem, which are applied to different settings. Here, we focus on small and medium enterprises (SMEs) and explore useful applications for energy disaggregation from the perspective of SMEs. More precisely, we use recurrence quantification analysis (RQA) of the aggregate and the individual device signals to create a two-dimensional map, which is an outlined region in a reduced information space that corresponds to ‘normal’ energy demand. Then, this map is used to monitor and control future energy consumption within the example business so to improve their energy efficiency practices. In particular, our proposed method is shown to detect when an appliance may be faulty and if an unexpected, additional device is in use

Electric vehicles and low-voltage grid: impact of uncontrolled demand side response

The authors are looking at the impact of electric vehicles (EV) charging from low-voltage (LV) networks. Based on the data obtained from two different pilot projects: (i) Mini-E trial where EV users were incentivised to charge during the night; (ii) My Electric Avenue trial, where there were no similar incentives, authors want to quantify the impact of EV charging, presuming that the number of home-charging EV users will increase significantly in the near future. By assuming that the current load at individual household level is known or inferred, simulations are performed to estimate the future load. The authors look at different percentages of EV uptake and model clustered scenarios, where the social networking effect is imposed – users adopt an EV with a higher probability if their neighbour already has one. Simulations demonstrate that incentivising night-time charging can create large new peaks during the night, which could have negative effects on LV networks. On the other hand, simulations based on the data with no incentives shows that naturally occurring diversity in charging behaviour does not automatically result in comparable network stress at the same penetrations

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes’ model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes’ equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined

A Bayesian Inverse Approach to Proton Therapy Dose Delivery Verification

This study presents a proof-of-concept for a novel Bayesian inverse method in a one-dimensional setting, aimed at proton beam therapy treatment verification. Our methodology is predicated on a hypothetical scenario wherein strategically positioned sensors detect prompt-{\gamma}'s emitted from a proton beam when it interacts with defined layers of tissue. Using this data, we employ a Bayesian framework to estimate the proton beam's energy deposition profile. We validate our Bayesian inverse estimations against a closed-form approximation of the Bragg Peak in a uniform medium and a layered lung tumour.Comment: 22 pages, 12 figure

Understanding material and supplier networks in the construction of disaster-relief shelters: the feasibility of using social network analysis as a decision-making tool

Purpose: Understanding the supply network of construction materials used to construct shelters in refugee camps, or during the reconstruction of communities, is important as it can reveal the intricate links between different stakeholders and the volumes and speeds of material flows to the end-user. Using social network analysis (SNA) enables another dimension to be analysed – the role of commonalities. This is likely to be particularly important when attempting to replace vernacular materials with higher-performing alternatives or when encouraging the use of non-vernacular methods. This paper aims to analyse the supply networks of four different disaster-relief situations. Design/methodology/approach: Data were collected from interviews with 272 displaced (or formally displaced) families in Afghanistan, Bangladesh, Nepal and Turkey, often in difficult conditions. Findings: The results show that the form of the supply networks was highly influenced by the nature/cause of the initial displacement, the geographical location, the local availability of materials and the degree of support/advice given by aid agencies and or governments. In addition, it was found that SNA could be used to indicate which strategies might work in a particular context and which might not, thereby potentially speeding up the delivery of novel solutions. Research limitations/implications: This study represents the first attempt in theorising and empirically investigating supply networks using SNA in a post-disaster reconstruction context. It is suggested that future studies might map the up-stream supply chain to include manufacturers and higher-order, out of country, suppliers. This would provide a complete picture of the origins of all materials and components in the supply network. Originality/value: This is original research, and it aims to produce new knowledge

Modulation theory for the Korteweg-de Vries equation with damping and periodic forcing

The Korteweg-de Vries (KdV) equation governs the evolution of weakly nonlinear and weakly dispersive long waves in a wide variety of applications. We first present asymptotic solutions to the KdV equation, perturbed by Burgers damping and periodic forcing. This equation models, amongst other applications, the resonant forcing of shallow water waves in a container. In particular, we seek periodic solutions to the steady forced KdV-Burgers (fKdVB) equation using a multiple-scale perturbation approach, where the first order solution in the perturbation hierarchy is the modulated cnoidal wave equation. Then using the second order equation in the hierarchy, we find a system of differential equations describing the slowly varying properties of the cnoidal wave. The fixed point solutions of this system are analysed, which correspond to periodic solutions to the fKdVB equation that are fully defined at first and second order. Furthermore, the stability of these solutions is established by conducting a linear stability analysis with this system of differential equations about the fixed points. As well, to support these findings, Floquet theory is used to determine stability. The unsteady fKdVB equation is also considered, where a multiple-scale perturbation technique based on modulated cnoidal waves is again applied. From the second order equation, we arrive at the well known `Whitham equations' with additional terms attributed to the damping and forcing. Next, steady solutions are sought using these modulation equations and as a result, the same family of first order steady periodic solutions that were previously identified, are now found. Moreover, our analysis is extended to the steady forced Kuramoto-Sivashinsky equation, which describes thin film flow down an inclined, corrugated surface. Subsequently, steady periodic solutions at first and second order are derived for this new problem and their stability is investigated