Impacts of plug-in hybrid vehicles and combined heat and power technologies on electric and gas distribution network losses

Distribution network operators (DNOs) require strategies that can offset the tradeoffs new embedded technologies have on their assets. This paper employs modelling to show that through control device manipulation, gas and electric (G&E) network operators can influence savings in energy losses under the presence of plug-in hybrid vehicles (PHEVs) and combined heat and power technologies (CHPs). An integrated gas and electric optimal power flow (OPF) tool is introduced to undertake various case studies. The OPF tool evaluates the technical impacts experienced in the networks when DNOs apply a "plug and forget" operation strategy and then compares the results against a "loss minimisation" strategy. Results show the benefits in applying different strategies are more considerable in electric networks than in gas networks. The study corroborates that an integrated G&E analysis offers a fresh perspective for stakeholders in evaluating energy service networks performance under different operation strategies

Diagnostic tools of energy performance for supermarkets using Artificial Neural Network algorithms

Supermarket performance monitoring is of vital importance to ensure systems perform adequately and guarantee operating costs and energy use are kept at a minimum. Furthermore, advanced monitoring techniques can allow early detection of equipment faults that could disrupt store operation. This paper details the development of a tool for performance monitoring and fault detection for supermarkets focusing on evaluating the Store's Total Electricity Consumption as well as individual systems, such as Refrigeration, HVAC, Lighting and Boiler. Artificial Neural Network (ANN) models are developed for each system to provide the energy baseline, which is modelled as a dependency between the energy consumption and suitable explanatory variables. The tool has two diagnostic levels. The first level broadly evaluates the systems performance, in terms of energy consumption, while the second level applies more rigorous criteria for fault detection of supermarket subsystems. A case study, using data from a store in Southeast England, is presented and results show remarkable accuracy for calculating hourly energy use, thus marking the ANN method as a viable tool for diagnosis purposes. Finally, the generic nature of the methodology approach allows the development and application to other stores, effectively offering a valuable analytical tool for better running of supermarkets

Optimal charging strategies of electric vehicles in the UK power market

In order to gain the most from their deployment, it is imperative for stakeholders to exploit the main benefits electric vehicles bring to utilities. Therefore, this paper focuses on the aspects required to model the management of electricity supply for electric vehicles. The framework presented details a time coordinated optimal power flow (TCOPF) tool to illustrate the tradeoffs distribution network operators (DNO) might encounter when implementing various load control approaches of electric vehicles. Within an UK context, a case study is performed where the TCOPF tool functions as the intermediary entity that coordinates cost-effective interactions between power markets, network operators, and the plugged vehicles. Results depict the stochastic but optimal charging patterns stakeholders might visualise from electric vehicles in local networks as they are operated to reduce energy and emission costs. Furthermore, results show current emission costs have a negligible weight in the optimisation process when compared to wholesale electricity costs

Optimal Technology Selection and Operation of Bio-methane CHP Units for Commercial Buildings

This paper explores the optimal implementation of bio-methane fuelled combined heat and power (CHP) systems to satisfy heat and electricity demands of commercial buildings; with the overarching goal of making cost-effective investments and decarbonizing building operations. The research work consisted in the development of a CHP technology selection and operation (TSO) optimization model. Its results can be utilized to develop a strategy for investment in bio-methane CHP projects for a portfolio of buildings. The TSO model enables a new approach for the selection and operation of CHP units that encompasses whole life costing, carbon emissions as well as real-time energy prices and demands, providing a more comprehensive result than current methods. Utilizing historic metered energy demands, projected energy prices and a portfolio of available CHP technologies, the mathematical model simultaneously solves for an optimal CHP unit selection and operational strategy for a determined building based on a preferred objective: minimizing cost, minimizing GHG emissions, or a mix of both. Results of this model prove that attractive cost and emissions savings are possible through the optimal selection and operation of CHP technologies fuelled by bio-methan

Operational and Economic Analysis of GSHP Coupled with Refrigeration Systems in UK Supermarkets

Ground Source Heat Pumps (GSHP) are capable of reducing energy consumption by operating at higher efficiencies than conventional gas systems, especially if coupled with refrigeration units such as in supermarkets. In principle, the heat rejected by refrigerators can be harnessed to raise the efficiency of the heat pumps. This paper presents the results of an operational and economic analysis conducted on this innovative system. Overall, the efficiency of all the GSHP systems under consideration appears to be above the eligibility threshold for the UK Government’s incentive (Renewable Heat incentive, RHI), with the average Seasonal Coefficient of Performance (SCOP) of the stores being 3.0 in 2014. From an economic perspective, such average performance leads to more than £120,000 of operational savings per year compared to gas boiler systems. Calculations show an investment Payback Time (PBT) of less than 8 years. Finally, the paper highlights potential cost reductions achievable through operational and design modifications. Overall results show that GSHP coupled with refrigeration systems present sound fundamentals to be considered as an attractive investment opportunity for food retailers

Assessing the modelling approach and datasets required for fault detection in photovoltaic systems

Reliable monitoring for photovoltaic assets (PVs) is essential to ensuring uptake, long term performance, and maximum return on investment of renewable systems. To this end this paper investigates the input data and machine learning techniques required for day-behind predictions of PV generation, within the scope of conducting informed maintenance of these systems. Five years of PV generation data at hourly intervals were retrieved from four commercial building-mounted PV installations in the UK, as well as weather data retrieved from MIDAS. A support vector machine, random forest and artificial neural network were trained to predict PV power generation. Random forest performed best, achieving an average mean relative error of 2.7%. Irradiance, previous generation and solar position were found to be the most important variables. Overall, this work shows how low-cost data driven analysis of PV systems can be used to support the effective management of such assets

Pressure effects in the triangular layered cobaltites NaxCoO2

We have measured transport properties as a function of temperature and pressure up to 30GPa in the NaxCoO2 system. For the x=0.5 sample the transition temperature at 53K increases with pressure, while paradoxically the sample passes from an insulating to a metallic ground state. A similar transition is observed in the x=0.31 sample under pressure. Compression on the x=0.75 sample transforms the sample from a metallic to an insulating state. We discuss our results in terms of interactions between band structure effects and Na+ order.Comment: 18 pages, 5 figure

A phenomenological model for the pressure sensitivity of the Curie temperature in hole-doped manganites

We performed high pressure experiments on La(0.8)Ca(0.2-x)Sr(x)MnO(3) (LCSMO) (0<x< 0.2) ceramic samples in order to analyze the validity of the well known relation between the A mean ionic radius () and the Curie temperature Tc of hole-doped manganites at a fixed doping level and for doping values below the 0.3 (Mn+4/Mn+3) ratio. By considering our results and collecting others from the literature, we were able to propose a phenomenological law that considers the systematic dependence of Tc with structural and electronic parameters. This law predicts fairly well the pressure sensitivity of Tc, its dependence with the A-cation radius disorder and its evolution in the high pressure range. Considering a Double Exchange model, modified by polaronic effects, the phenomenological law obtained for Tc can be associated with the product of two terms: the polaronic modified bandwidth and an effective hole doping.Comment: 5 pages, 7 figures, corresponding author: C. Acha ([email protected]

Optimal Design and Operation of Distributed Low-Carbon Energy Technologies in Commercial Buildings

Commercial buildings are large energy consumers and opportunities exist to improve the way they produce and consume electricity, heating and cooling. If energy system integration is feasible, this can lead to significant reductions in energy consumption and emissions. In this context, this work expands on an existing integrated Technology Selection and Operation (TSO) optimisation model for distributed energy systems (DES). The model considers combined heat and power (CHP) and organic Rankine cycle (ORC) engines, absorption chillers, photovoltaic panels and batteries with the aim of guiding decision makers in making attractive investments that are technically feasible and environmentally sound. A retrofit case study of a UK food distribution centre is presented to showcase the benefits and trade-offs that integrated energy systems present by contrasting outcomes when different technologies are considered. Results show that the preferred investment options select a CHP coupled either to an ORC unit or to an absorption chiller. These solutions provide appealing internal rates of return of 28–30% with paybacks within 3.5–3.7 years, while also decarbonising the building by 95–96% (if green gas is used to power the site). Overall, the TSO model provides valuable insights allowing stakeholders to make well-informed decisions when evaluating complex integrated energy systems