40 results found
Mavromatidis G, Acha S, Shah N, 2013, Diagnostic tools of energy performance for supermarkets using Artificial Neural Network algorithms, Energy and Buildings, Vol: 62, Pages: 304-314, ISSN: 1872-6178
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.
Acha Izquierdo S, Shah N, 2012, Optimal Lighting Control Strategies in Supermarkets for Energy Efficiency Applications via Digital Dimmable Technology, ECOS 2012, Publisher: Firenze University Press
Electricity consumption in the UK commercial sector accounts for 19% of total annual electricity demand.This implies any step taken towards energy efficiency applications for commercial buildings can generateimportant reductions in both energy use and carbon emissions. Sainsbury’s supermarkets, one of the UKslargest grocers, recognises the challenges climate change brings to businesses and hence is conductingefforts to reduce the operational carbon footprint of their stores. Lighting in stores is an essential service andis an important component of a stores power demand; ranging from 15 to 35% based on design features.This paper details the innovative lighting control application Sainsbury’s is currently employing in its newstores with the objective to maximise the benefits digital dimmable technology possesses. Basic lightingconcepts are described which explain the priorities supermarkets have when using this service, while thetradeoffs of using digital signal interface (DSI) controls are also discussed. The non-linear relationshipbetween DSI settings, lux drawn from ballasts, and power consumed by the system are showcased as aproper understanding of this concept is paramount in achieving energy savings. In addition, using aSainsbury’s 3,300 m2 eco-store, a thorough case study is presented in which various lighting strategysettings are applied; having very attractive results in monetary, energy, and environmental metrics withoutbeing detrimental to the shopping experience. Hence, it is proven digital dimmable technology controls caneffectively provide 20 to 25% savings in lighting services if sensors and settings are established properly.Furthermore, due to the robust and fast response capability digital dimming offers, the authors argue thistechnology is suitable for demand side management applications that can greatly benefit the operability ofthe grid and as a consequence provide an additional revenue stream for businesses in a smart-gridenviro
Acha S, van Dam KH, Shah N, 2012, Modelling spatial and temporal agent travel patterns for optimal charging of electric vehicles in low carbon networks, 2012 IEEE Power and Energy Society General Meeting, Publisher: IEEE, Pages: 1-8
The ability to determine optimal charging profiles of electric vehicles (EVs) is paramount in developing an efficient and reliable smart-grid. However, so far the level of analysis proposed to address this issue lacks combined spatial and temporal elements, thus making mobility a key challenge to address for a proper representation of this problem. This paper details the principles applied to represent optimal charging of EVs by employing an agent-based model that simulates the travelling patterns of vehicles on a road network. The output data is used as a reliable forecast so an optimal power flow model can devise optimal charging scenarios of EVs in a local electrical network. The effectiveness of the model is illustrated by presenting a multi-day case study in an urban area. Results show a high level of detail and variability in EV charging when a present-day carbon fuel mix is compared to one with lower carbon intensity.
Acha S, Green TC, Shah N, 2011, Optimal charging strategies of electric vehicles in the UK power market, 2011 IEEE PES Innovative Smart Grid Technologies (ISGT), Publisher: IEEE, Pages: 1-8
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.
Acha S, Green TC, Shah N, 2010, Effects of Optimised Plug-in Hybrid Vehicle Charging Strategies on Electric Distribution Network Losses, 2010 IEEE PES Transmission and Distribution Conference and Exposition - Smart Solutions for a Changing World, Publisher: IEEE
Acha S, Green TC, Shah N, 2010, Techno-economical Tradeoffs from Embedded Technologies with Storage Capabilities on Electric and Gas Distribution Networks, IEEE-Power-and-Energy-Society General Meeting, Publisher: IEEE, ISSN: 1944-9925
Acha S, Green TC, Shah N, 2009, Impacts of plug-in hybrid vehicles and combined heat and power technologies on electric and gas distribution network losses, 2009 IEEE PES/IAS Conference on Sustainable Alternative Energy (SAE), Publisher: IEEE, Pages: 1-7
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.
Acha Izquierdo S, Hernandez Aramburo C, 2008, Integrated Modelling of Gas and Electricity Distribution Networks with a High Penetration of Embedded Generation, CIRED Seminar 2008: SmartGrids for Distribution, Publisher: IET, ISSN: 0537-9989
Gas-based combined heat and power (CHP) has maturedenough to be regarded as the next evolutionary step inpromoting energy efficiency use in the urban environment.Although its potential market is increasing, little researchhas been conducted into the combined technical effects thata high penetration of these units may have on both naturalgas and electric (G&E) distribution networks. This paperpresents a power flow tool that performs a simultaneousassessment on some technical impacts that a highpenetration of heat-driven cogeneration units may have onG&E networks. A case study is presented and results showthat as expected, the gas demand increases as well as thelosses associated with its delivery, while the opposite effectsoccur in the electrical system. However, less evident is theload profile variations distribution networks will experienceand that overall energy losses will vary according to theCHP penetration and the type of technology used. The studyshows that an integrated G&E analysis offers a freshperspective in quantifying the effects cogenerationtechnologies will have on energy distribution networks.
Acha S, van Dam KH, Keirstead J, et al., Integrated modelling of agent-based electric vehicles into optimal power flow studies, Frankfurt, Germany
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