43 results found
Escriva EJS, Acha S, LeBrun N, et al., 2019, Modelling of a real CO2 booster installation and evaluation of control strategies for heat recovery applications in supermarkets, International Journal of Refrigeration, Vol: 107, Pages: 288-300, ISSN: 0140-7007
This paper compares and quantifies the energy, environmental and economic benefits of various control strategies recovering heat from a CO2 booster system in a supermarket for space heating with the purpose of understanding its potential for displacing natural gas fuelled boilers. A theoretical steady-state model that simulates the behaviour of the CO2 system is developed and validated against field measurements obtained from an existing refrigeration system in a food-retail building located in the United Kingdom. Five heat recovery strategies are analysed by modifying the mass flows and pressure levels in the condenser. The model shows that a reduction of 48% in natural-gas consumption is feasible by the installation of a de-superheater and without any advanced operating strategy. However, the CO2 system can fully supply the entire space-heating requirement by adopting alternative control strategies, albeit by penalising the coefficient of performance (COP) of the compressor. Results show that the best energy strategy can reduce total consumption by 32%, while the best economic strategy can reduce costs by 6%. Findings from this work suggest that heat recovery systems can bring substantial benefits to improve the overall efficiency of energy-intensive buildings; although trade-offs need to be carefully considered and further analysed before embarking on such initiatives.
Acha Izquierdo S, Le Brun N, Shah N, et al., Assessing the Modelling Approach and Datasets Required for Fault Detection in Photovoltaic Systems, IEEE Industry Applications Society Annual Meeting
Howard B, Acha Izquierdo S, Shah N, et al., 2019, Implicit sensing of building occupancy count with information and communication technology data sets building and environment, Building and Environment, Vol: 157, Pages: 297-308, ISSN: 0360-1323
Occupancy count, i.e., the number of people in a space or building, is becoming an increasingly important measurement to model, predict, and minimize operational energy consumption. Explicit, hardware-based, occupancy counters have been proposed but wide scale adoption is limited due to the cost and invasiveness of system implementation. As an alternative approach, researchers propose using data from existing information and communication technology (ICT) systems to infer occupancy counts.In the reported work, three different data streams, security access data, wireless connectivity data, and computer activity data, from ICT systems in a medium sized office building were collected and compared to the counts of a commercially available occupancy counter over 59 working days. The occupancy counts from the ICT systems are compared to the commercial counter with and without calibration to determine the ability of the data sets to measure occupancy. Various transformations were explored as calibration techniques for the ICT data sets. Training sets of 24, 48, and 120 hours were employed to determine how long an external calibration system would need to be installed.The analysis found that calibration is required to provide accurate counts. While each ICT data set provides similar magnitudes and time series behavior, incorporating all three data streams in a two layer neural network with 1 week of training data provides the most accurate estimates against 5 performance metrics. Whilst 1 week of data provides the best results, 24 hours is sufficient to develop similar levels of performance.
Chakrabarti A, Proeglhoef R, Bustos-Turu G, et al., 2019, Optimisation and analysis of system integration between electric vehicles and UK decentralised energy schemes, Energy, Vol: 176, Pages: 805-815, ISSN: 0360-5442
Although district heat network schemes provide a pragmatic solution for reducing the environmental impact of urban energy systems, there are additional benefits that could arise from servicing electric vehicles. Using the electricity generated on-site to power electric vehicles can make district heating networks more economically feasible, while also increasing environmental benefits. This paper explores the potential integration of electric vehicle charging into large-scale district heating networks with the aim of increasing the value of the generated electricity and thereby improving the financial feasibility of such systems. A modelling approach is presented composed of a diverse range of distributed technologies that considers residential and commercial electric vehicle charging demands via agent-based modelling. An existing district heating network system in London was taken as a case study. The energy system was modelled as a mixed integer linear program and optimised for either profit maximisation or carbon dioxide emissions minimisation. Commercial electric vehicles provided the best alternative to increase revenue streams by about 11% against the current system configuration with emissions effectively unchanged. The research indicates that district heating network systems need to carefully analyse opportunities for transport electrification in order to improve the integration, and sustainability, of urban energy systems.
Olympios A, Le Brun N, Acha Izquierdo S, et al., Installation of a dynamic controller for the optimal operation of a CHP engine in a supermarket under uncertainty, 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems
This work is concerned with the integration and coordination of decentralized combined heat and power (CHP) systems in commercial buildings. Although extensive research has been performed on theoretically optimizing the design, sizing and operation of CHP systems, less effort has been devoted to an understanding of the practical challenges and the effects of uncertainty in implementing advanced algorithms to real-world applications. This paper provides details of an undergoing field trial involving the installation of a dynamic controller for the optimal operation of an existing CHP engine, which provides electricity and heat to a supermarket. The challenges in developing and applying an optimization framework and the software architecture required to implement it are discussed. Deterministic approaches that involve no measure of uncertainty provide limited useful insight to decision makers. For this reason, the methodology here develops a stochastic programming technique, which performs Monte Carlo simulations that can consider the uncertainty related to the exporting electricity price. The method involves the formation of a bi-objective function that represents a compromise between maximizing the expected savings and minimizing the associated risk. The results reveal a risk-return trade-off, demonstrating that conservative operation choices emerging from the stochastic approach can reduce risk by about 15% at the expense of a noticeably smaller reduction of about 10% in expected savings.
Ayoub AN, Gaigneux A, Le Brun N, et al., 2019, The development of a carbon roadmap investment strategy for carbon intensive food retail industries, International Conference on Sustainable Energy and Resource Use in Food Chains including Workshop on Energy Recovery Conversion and Management, Publisher: Elsevier, Pages: 333-342, ISSN: 1876-6102
This work presents an approach to develop an innovative decarbonisation investment strategy framework for carbon intensive UK industries by using statistical analysis and optimisation modelling. The case study focuses on taking a representative sample of retail buildings and assesses the financial viability of installing low-carbon Combined Heat and Power units (CHPs) and Photovoltaic Solar Panels (PVs) across a portfolio of buildings. Simulation of each building are initially conducted, and the results generate a set of regression coefficients, via a multivariate adaptive regression splines (MARS), which are inputted into a Mixed Integer Linear Programming (MILP) problem. Solving the MILP yields the optimal decarbonisation investment strategy for the case study up to 2050, considering market trends such as electricity prices, gas prices and policy incentives. Results indicate the level of investment required per year, the operational and carbon savings associated, and a program for such investments. This method is reiterated for several scenarios where different parameters such as utility prices, capital costs and grid carbon factors are forecasted up to 2050 (following the Future Energy Scenarios from National Grid). This work shows how a clear mathematical framework can assist decision-makers in commercial organisations to reduce their carbon footprint cost-effectively and thus reach science-based targets.
Efstratiadi M, Acha Izquierdo S, Shah N, et al., 2019, Analysis of a closed-loop water-cooled refrigeration system in the food retail industry: A UK case study, Energy, ISSN: 0360-5442
Refrigeration in supermarkets accounts between 30% and 60% of total electricity demand in UK stores. The aim of this study is to conduct a pre-feasibility analysis of whether the use of a water-cooled configuration rejecting heat to the soil can improve the overall cooling performance of commercial refrigeration systems against air-cooled designs. In this work, a model simulating the operation of an existing refrigeration system is presented and validated against field data measurements taken from a supermarket. The examined system is used as a baseline and then modified to evaluate the impact of installing a water-cooled gas cooler. Results indicate that the use of water-cooled gas coolers has the potential to reduce electrical consumption of refrigeration systems by up to a factor of 5 when external temperatures are high. Overall, annual operation indicates the water-cooled alternative uses 3% less electricity than the air-cooled approach. A hybrid system is also considered consisting of coupled air-cooled and water-cooled units operating in parallel, for which an energy reduction of 6% is obtained compared against the baseline system. An economic evaluation of these systems shows promising results with a payback period of about 5 years for systems installed in new stores, although retrofits are costlier.
O'Dwyer E, Pan I, Acha S, et al., 2019, Smart energy systems for sustainable smart cities: Current developments, trends and future directions, Applied Energy, Vol: 237, Pages: 581-597, ISSN: 0306-2619
Within the context of the Smart City, the need for intelligent approaches to manage and coordinate the diverse range of supply and conversion technologies and demand applications has been well established. The wide-scale proliferation of sensors coupled with the implementation of embedded computational intelligence algorithms can help to tackle many of the technical challenges associated with this energy systems integration problem. Nonetheless, barriers still exist, as suitable methods are needed to handle complex networks of actors, often with competing objectives, while determining design and operational decisions for systems across a wide spectrum of features and time-scales. This review looks at the current developments in the smart energy sector, focussing on techniques in the main application areas along with relevant implemented examples, while highlighting some of the key challenges currently faced and outlining future pathways for the sector. A detailed overview of a framework developed for the EU H2020 funded Sharing Cities project is also provided to illustrate the nature of the design stages encountered and control hierarchies required. The study aims to summarise the current state of computational intelligence in the field of smart energy management, providing insight into the ways in which current barriers can be overcome.
Georgiou S, Acha S, Shah N, et al., 2018, A generic tool for quantifying the energy requirements of glasshouse food production, Journal of Cleaner Production, Vol: 191, Pages: 384-399, ISSN: 0959-6526
Quantifying the use of resources in food production and its environmental impact is key to identifying distinctive measures which can be used to develop pathways towards low-carbon food systems. In this paper, a first-principle modelling approach is developed, referred to as gThermaR (Glasshouse-Thermal Requirements). gThermaR is a generic tool that focuses on the energy requirements of protected heated production, by integrating holistic energy, carbon, and cost modelling, food production, data analytics and visualization. The gThermaR tool employs historic data from weather stations, growing schedules and requirements specific to grower and product needs (e.g. set-point temperatures, heating periods, etc.) in order to quantify the heating and cooling requirements of glasshouse food production. In the present paper, a case study is reported that employs a database compiled for the UK. Another relevant feature of the tool is that it can quantify the effects that spatial and annual weather trends can have on these heating and cooling requirements. The main contribution of this work, therefore, concerns the development a tool that can provide a simple integrated approach for performing a wide range of analyses relevant to the thermal requirements of heated glasshouses. The tool is validated through collaborations with industrial partners and showcased in a case study of a heated glasshouse in the UK, offering the capacity to benchmark and compare different glasshouse types and food growth processes. Results from the case study indicate that a significant reduction in the heating requirement and, therefore, carbon footprint, of the facility can be achieved by improving key design and operational parameters. Results indicate savings in the peak daily and annual heating requirements of 44-50% and 51-57% respectively, depending on the region where the glasshouse is located. This improvement is also reflected in the carbon emissions and operating costs for the different en
Acha Izquierdo S, Mariaud A, Shah N, et al., 2017, Optimal Design and Operation of Distributed Low-Carbon Energy Technologies in Commercial Buildings, Energy, Vol: 142, Pages: 578-591, ISSN: 0360-5442
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.
Acha S, Mariaud A, Shah N, et al., 2017, Optimal design and operation of low-carbon energy technologies in commercial buildings, 30th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems - ECOS 2017
© 2017 IMEKO Non-domestic buildings are large energy consumers and present many opportunities with which to enhance the way they produce and consume electricity, heating and cooling. If energy system integration is feasible, this can lead to significant reductions in energy use and emissions associated with building operations. Due to their diverse energy requirements, a broad range of technologies in flexible solutions need to be evaluated to identify the best alternative. This paper presents an integrated energy-systems model that optimizes the selection and operation of distributed technologies for commercial buildings. The framework consists of a comprehensive technology database, half-hourly electricity cost profiles, conventional fuel costs and building features. This data is applied to a mixed-integer linear programming model that optimizes the design and operation of installed technologies based on a range of financial and environmental criteria. The model aims to guide decision makers in making attractive investments that are technically feasible and environmentally sound. A case study of a food distribution centre in the UK is presented to illustrate the economic and environmental benefits the proposed integrated energy systems model could bring against a business as usual (BaU) approach. The technology portfolio considered in the case study includes combined heat and power (CHP) and organic Rankine cycle (ORC) engines, absorption chillers, photovoltaic (PV) panels, and battery systems. The results clearly illustrate the different outcomes and trade-offs that can emerge when stakeholders champion different technologies instead of making an exhaustive assessment. Overall, the model provides meaningful insights that can allow stakeholders to make well informed investment decisions when it comes to the optimal configuration and operation of energy technologies in commercial buildings.
Georgiou S, Acha Izquierdo S, Shah N, et al., 2017, Assessing, benchmarking and analyzing heating and cooling requirements for glasshouse food production: a design and operation modelling framework, 1st International Conference on Sustainable Energy and Resource Use in Food Chains, ICSEF 2017, Publisher: Elsevier, Pages: 164-172, ISSN: 1876-6102
Growing populations, increase in food demand, society’s expectations for out of season products and the dependency of the food system on fossil fuels stress resources due to the requirements for national production and from importation of products from remote origins. Quantifying the use of resources in food production and their environmental impacts is key to identifying distinctive measures which can develop pathways towards low carbon food systems. In this paper, a modelling approach is presented which can quantify the energy requirements of heated glasshouse food production. Based on the outputs from the model, benchmarking and comparison among different glasshouse types and growers is possible. Additionally, the effect of spatial and annual weather trends on the heating and cooling requirements of glasshouses are quantified. Case study results indicate that a reduction in heating requirements of about 50%, and therefore an equivalent carbon footprint reduction, can be achieved by replacing a single glass sealed cover with a double glass sealed cover.
Acha Izquierdo S, lambert R, Shah N, et al., 2017, Modelling and optimising the marginal expansion of an existing district heating network, Energy, Vol: 140, Pages: 209-223, ISSN: 0360-5442
Although district heating networks have a key role to play in tackling greenhouse gas emissions associated with urban energy systems, little work has been carried out on district heating networks expansion in the literature. The present article develops a methodology to find the best district heating network expansion strategy under a set of given constraints. Using a mixed-integer linear programming approach, the model developed optimises the future energy centre operation by selecting the best mix of technologies to achieve a given purpose (e.g. cost savings maximisation or greenhouse gas emissions minimisation). Spatial expansion features are also considered in the methodology.Applied to a case study, the model demonstrates that depending on the optimisation performed, some building connection strategies have to be prioritised. Outputs also prove that district heating schemes' financial viability may be affected by the connection scenario chosen, highlighting the necessity of planning strategies for district heating networks. The proposed approach is highly flexible as it can be adapted to other district heating network schemes and modified to integrate more aspects and constraints.
Dahmm H, Bustos-Turu G, Acha S, et al., 2017, Techno-economic analysis and trade-offs of cooperative community energy planning schemes in the UK, 30TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS
© 2017 IMEKO Community Energy (CE) is the ownership of distributed energy resources by local communities. this paper describes a modelling framework for how communities can realize new opportunities through cooperation. The model disaggregates a community into sectors, having unique combinations of energy profiles, financial conditions, and available technologies. A modified Nash Bargaining technique was used to optimize the selection and operation of boiler, heat pump and CHP technologies, while also managing the exchange of energy vectors within the community; sectors cooperated first by exchanging electricity generation, exchanging heat, and then exchanging electricity and heat together. This approach adds to the literature by comparing forms of energy integration while considering diverse community interests. A case study was developed from London residential data, combined with profiles of five non-residential sectors. Results show that the exchange of electricity or heat can increase CO2 mitigation relative to independent action, but exchanging electricity and heat together magnifies the possible mitigation. Economic benefits vary between sectors and scenarios, but exchanging electricity and heat together maximizes the objective. Cooperation increases community resilience to reductions in government support, and increasing existing subsidies might reduce the incentive to cooperate. Future work should consider business plans for realizing environmental and economic benefits.
Mariaud A, Acha S, Ekins-Daukes N, et al., 2017, Integrated optimisation of photovoltaic and battery storage systems for UK commercial buildings, Applied Energy, Vol: 199, Pages: 466-478, ISSN: 1872-9118
Decarbonising the built environment cost-effectively is a complex challenge public and private organisations are facing in their effort to tackle climate change. In this context, this work presents an integrated Technology Selection and Operation (TSO) optimisation model for distributed energy systems in commercial buildings. The purpose of the model is to simultaneously optimise the selection, capacity and operation of photovoltaic (PV) and battery systems; serving as a decision support framework for assessing technology investments. A steady-state mixed-integer linear programming (MILP) approach is employed to formulate the optimisation problem. The virtue of the TSO model comes from employing granular state-of-the-art datasets such as half-hourly electricity demands and prices, irradiance levels from weather stations, and technology databases; while also considering building specific attributes. Investment revenues are obtained from reducing grid electricity costs and providing fast-frequency response (FFR) ancillary services. A case study of a distribution centre in London, UK is showcased with the goal to identify which technologies can minimise total energy costs against a conventional system setup serving as a benchmark. Results indicate the best technology configuration is a combination of lithium-ion batteries and mono-crystalline silicon PVs worth a total investment of £1.72 M. Due to the available space in the facility, the preferred PV capacity is 1.76 MW, while the battery system has a 1.06 MW power capacity and a 1.56 MWh energy capacity. Although PV performance varies across seasons, the solution indicates almost 30% of the energy used on-site can be supplied by PVs while achieving a carbon reduction of 26%. Nonetheless, PV and battery systems seem to be a questionable investment as the proposed solution has an 8-year payback, despite a 5-year NPV savings of £300k, implying there is still a performance gap for such systems to be massively
Howard BN, acha Izquierdo S, polak J, et al., Measuring building occupancy through ICT data streams, ECEEE SUMMER STUDY PROCEEDINGS
Cedillos D, Acha Izquierdo S, Shah N, et al., 2016, A Technology Selection and Operation (TSO) optimisation model for distributed energy systems: Mathematical formulation and case study, Applied Energy, Vol: 180, Pages: 491-503, ISSN: 1872-9118
This paper presents a model which simultaneously optimises the selection and operation of technologies for distributed energy systems in buildings. The Technology Selection and Operation (TSO) model enables a new approach for the optimal selection and operation of energy system technologies that encompasses whole life costing, carbon emissions as well as real-time energy prices and demands; thus, providing a more comprehensive result than current methods. Utilizing historic metered energy demands, projected energy prices and a portfolio of available technologies, the mathematical model simultaneously solves for an optimal technology selection and operational strategy for a determined building based on a preferred objective: minimizing cost and/or minimizing carbon emissions. The TSO is a comprehensive and novel techno-economic model, capable of providing decision makers an optimal selection from a portfolio of available energy technologies. The current portfolio of available technologies is composed of various combined heat and power (CHP) and organic Rankine cycle (ORC) units. The TSO model framework is data-driven and therefore presents a high level of flexibility with respect to time granularity, period of analysis and the technology portfolio. A case study depicts the capabilities of the model; optimisation results under different temporal arrangements and technology options are showcased. Overall, the TSO model provides meaningful insights that allow stakeholders to make technology investment decisions with greater assurance.
Acha Izquierdo S, Cedillos D, Shah N, 2016, Optimal Technology Selection and Operation of Bio-methane CHP Units for Commercial Buildings, 2016 ASHRAE Annual Conference, Publisher: ASHRAE
This paper explores the optimal implementation of bio-methane fuelled combined heat and power (CHP) systems to satisfy heat and electricity demands ofcommercial buildings; with the overarching goal of making cost-effective investments and decarbonizing building operations. The research work consisted inthe development of a CHP technology selection and operation (TSO) optimization model. Its results can be utilized to develop a strategy for investment inbio-methane CHP projects for a portfolio of buildings. The TSO model enables a new approach for the selection and operation of CHP units thatencompasses 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 simultaneouslysolves for an optimal CHP unit selection and operational strategy for a determined building based on a preferred objective: minimizing cost, minimizingGHG emissions, or a mix of both. Results of this model prove that attractive cost and emissions savings are possible through the optimal selection andoperation of CHP technologies fuelled by bio-methane
Acha Izquierdo S, Dalpane P, Shah N, 2016, Operational and Economic Analysis of GSHP Coupled with Refrigeration Systems in UK Supermarkets, 2016 ASHRAE Annual Conference, Publisher: ASHRAE
Ground Source Heat Pumps (GSHP) are capable of reducing energy consumption by operating at higher efficiencies than conventional gas systems, especiallyif coupled with refrigeration units such as in supermarkets. In principle, the heat rejected by refrigerators can be harnessed to raise the efficiency of the heatpumps. This paper presents the results of an operational and economic analysis conducted on this innovative system. Overall, the efficiency of all the GSHPsystems under consideration appears to be above the eligibility threshold for the UK Government’s incentive (Renewable Heat incentive, RHI), with theaverage Seasonal Coefficient of Performance (SCOP) of the stores being 3.0 in 2014. From an economic perspective, such average performance leads tomore than £120,000 of operational savings per year compared to gas boiler systems. Calculations show an investment Payback Time (PBT) of less than8 years. Finally, the paper highlights potential cost reductions achievable through operational and design modifications. Overall results show that GSHPcoupled with refrigeration systems present sound fundamentals to be considered as an attractive investment opportunity for food retailers.
Acha Izquierdo S, Shah N, 2016, Re-commissioning Energy Conservation Measures in Supermarkets: An UK Case Study, CLIMA 2016, Publisher: Aalborg University, Department of Civil Engineering
Considering the UK’s ambitious carbon emission reduction target (i.e. reducingCO2e emissions by 80% below 1990 levels by 2050), it is evident that energyconservation measures in food retail buildings can substantially contribute inmeeting this goal. Supermarket buildings in particular are complex energy systemsthat require careful study to make sure they perform in a sensible manner. Retailpressure on quick store delivery makes commissioning teams prone to mistakes andtherefore, despite stores being newly built or refurbished, their systems are notideally set up. This circumstance makes buildings underperform by excessivelyconsuming energy which is a detriment in terms of costs and carbon emissions. Theobjective of this paper is to disseminate the energy savings that can come from lowcost re-commissioning measures linked to best operating practices; this is achievedby gathering insights from the monitoring of refrigeration, HVAC, and lightingsystems. A case study in a 3,300 m2 UK supermarket showcases the energyperformance of these systems before and after measures are implemented. The trialsconducted have the feature of being holistic by working closely with store staff andcontractors. Results show store energy use in Year 2 improved by 20% against itsbenchmark (Year 1); consequently reducing the carbon footprint and energy bills ofthe building. Furthermore, the learning’s are transferable and have quick paybackperiods; thus making clear a large potential exists in reducing energy bills ofretailers while simultaneously contributing to carbon mitigation in the UK.
Acha Izquierdo S, Bustos-Turu G, Shah N, 2016, Modelling Real-Time Pricing of Electricity for EnergyConservation Measures in the UK Commercial Sector, Energycon 2016, Publisher: IEEE
Electricity bills in the UK are increasing year after year due to power market conditions and they will most likely continue to rise. These high costs are reducing the profitability of businesses and thus efforts on understanding and mitigating these charges are a key concern for companies in order to improve their bottom line. This paper focuses on detailing a comprehensive bottom-up model of electricity commercial bills that generates real-time price curves; thus allowing customers to comprehend the true cost of the electricity they consume. The model provides profiles for different UK regions across various seasons. These insights are valuable because they can be used to inform more accurately energy efficiency programs in terms such as return on investment. By knowing where energy is more expensive it makes it easier to prioritize investments. Results overall show Yorkshire has the highest rates, while the South West has the most expensive peaks. Meanwhile, London and Southern England have the cheapest rates.
Acha Izquierdo S, Van Dam KH, Markides C, et al., 2016, Simulating residential electricity and heat demand in urban areas using an agent-based modelling approach, Energycon 2016, Publisher: IEEE
Cities account for around 75% of the global energy demand and are responsible for 60-70% of the global greenhouse gasses emissions. To reduce this environmental impact it is important to design efficient energy infrastructures able to deal with high level of renewable energy resources. A crucial element in this design is the quantitative understanding of the dynamics behind energy demands such as transport, electricity and heat. In this paper an agent-based simulation model is developed to generate residential energy demand profiles in urban areas, influenced by factors such as land use, energy infrastructure and user behaviour. Within this framework, impact assessment of low carbon technologies such as plug-in electric vehicles and heat pumps is performed using London as a case study. The results show that the model can generate important insights as a decision support tool for the design and planning of sustainable urban energy systems.
Acha Izquierdo S, Mavromatidis G, Caritte V, et al., Effective Low-cost Energy Saving Strategies in Supermarkets: An UK Case Study, ECOS 2013
Supermarket buildings are complex energy systems that require careful study to make sure they perform in asensible manner. The retail pressure of delivering stores in a short time makes engineering commissioningteams prone to mistakes and therefore, despite stores being newly built and carefully designed, theirsystems are not ideally set up; thus making the building underperform from day one. Consequently, energysavings are within easy reach if an effort is made to re-evaluate stores shortly after their opening date. Thispaper focuses on how adequate monitoring and good housekeeping can lead to effective energy savingstrategies for a better management of services such as lighting, refrigeration, heating and ventilation.Additionally, a focused effort in curtailing energy use in supermarkets can also seriously reduce operationalcarbon related emissions; an ever-growing concern for retailers in an environment where sustainabilitypractice is highly valued by consumers. A case study of a 35,000 ft2 supermarket located in the south-eastof England serves as a vehicle to present and quantify effective, low-cost energy saving strategies.Extensive monitoring capabilities allow us to set a benchmark for all systems which then serves to assessthe effectiveness of trials performed. Trials consist of: a) enhancing the dimming capabilities of the lightingsystem by improving sensor location and code, b) improving settings of fans and boiler system that reduceheating and ventilation requirements, and c) advocating the proper use of night-blinds in cabinets coupledwith suction optimization of compressors that save energy use in the refrigeration system. All of these livetrials have the feature of working closely with store staff and management, specialised contractors andacademics. The synergy of parties allows the energy trials to succeed since aside from having solid technicalfoundations they have the full support from the people that work day in and day out in the supermarket &nda
Acha S, Du Y, Shah N, 2016, Enhancing energy efficiency in supermarket refrigeration systems through a robust energy performance indicator, International Journal of Refrigeration, Vol: 64, Pages: 40-50, ISSN: 0140-7007
Bustos G, Guo M, van Dam KH, et al., 2016, Incorporating life cycle assessment indicators into optimal electric vehicle charging strategies: An integrated modelling approach, Editors: Kravanja, Bogataj, Publisher: ELSEVIER SCIENCE BV, Pages: 241-246
Acha Izquierdo S, Loh C, Noye S, et al., 2015, Retail Building Thermal Efficiency Improvement Through an Enhanced Re-Commissioning Framework, 2015 ASHRAE Annual Conference, Publisher: ASHRAE, ISSN: 1088-8586
End-use energy efficiency is recognized as a predominant contributor to achieve UK carbon reduction target that is still far from reach today. Theopportunity in retail buildings is apparent, especially supermarkets that account for 4 MtCO2e of total UK carbon footprint. This paper outlinesan enhanced re-commissioning (Re-Cx) framework that aims to mitigate supermarkets with poor energy performance, known as “cold-stores”. Theframework delivers a holistic approach with four critical strategies – Identification, Monitoring, Rectification and Prevention in sustainingsupermarket thermal efficiency throughout its operational lifecycle. This includes a comprehensive store characterization to identify “cold-store”, keyperformance indicators (KPIs) proposal for supermarket thermal efficiency monitoring, a cost-effective fault indication flowchart development for“cold-store” rectification, and the introduction of a novel Re-Cx and maintenance integration approach to prevent “cold-store” in a sustainablemanner. A case study is carried out on 350 stores from one of the biggest UK supermarket chains. Seven “cold-stores” are identified from thecomprehensive store benchmarking and characterization analysis. These results are also validated through the proposed KPIs. Moreover, acomparison between EnergyStar Re-Cx strategies and the supermarket maintenance procedures found 80% of the Re-Cx measures could beintegrated into the maintenance activities. This ascertains the feasibility of the suggested integration approach. In a nutshell, this framework bringsa new perception to retail Re-Cx regime, which can be implemented to effectively identify, monitor, rectify and prevent “cold-stores”.
Acha Izquierdo S, Shah N, Bos J, Cost effective low carbon store analysis and replication, CIBSE Technical Symposium 2015
This paper explores how low carbon buildings can be easily and cost effectivelyreplicated for a commercial retailer. The analysis investigates zero carbonsupermarkets using bio-methane combined heat and power (CHP). Results showthat CHP & district heating is the most cost effective design for a sustainablesupermarket. However, its implementation depends greatly on third parties and thusis not easy to replicate. The second best alternative is to use a CHP coupled with anOrganic Rankine Cycle (ORC) when the buildings heat-to-power ratio is below 0.5.Otherwise, a CHP with no heat recovery solution is deemed best. Overall, the mostcost effective ZCS projects are the ones implemented in stores with a high heat-topowerratio, high energy intensities and large surface floor area.
Andrianopoulos E, Acha S, Shah N, 2015, Achieving net zero carbon performance in a commercial building by aligning technical and policy alternatives - An UK case study
Quantifying a detailed inventory of carbon emissions attributed to a retail building is of vital importance to minimize (or offset) their environmental impact. However, quantifying the environmental impact of a commercial building's operation has attracted great controversy regarding both the carbon fields considered within the building's operational boundaries and the different responsibility levels among participants. This paper details a robust framework on how businesses operating under UK policy can measure the operational carbon performance attributed to their buildings. Furthermore, the paper investigates how the quantified emissions can be offset in order to reach net zero carbon operational performance. The analysis is structured in three levels and its applicability is showcased through an industry-sourced example of a supermarket building. The first level aims to classify building emissions according to their sources namely electricity consumption, on-site fuel burning, water supply, transport operations and waste management & disposal. The developed carbon fields' analysis technique treats a commercial building as an on-going energy consuming system where different operations (e.g. transport activities) contribute to the building's commercial use as well as to its operational carbon footprint. In the second level, the study compares a food store's carbon footprint across different supply and operation scenarios in order to analyse how each sector can influence emissions. In the third stage, the research details the carbon off-setting achieved by installing a bioenergy combined heat and power (CHP) unit in its premises and thus achieving net zero carbon performance. Results illustrate the environmental benefits for different CHP capacity solutions. These results show how urban cogeneration plants can de-carbonise UK buildings. However, the UK carbon accounting framework is still evolving and therefore is constantly subject to regulatory changes. Conse
Bustos-Turu G, van Dam KH, Acha S, et al., 2014, Estimating Plug-in Electric Vehicle Demand Flexibility through an Agent-Based Simulation Model, 5th IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), Publisher: IEEE, ISSN: 2165-4816
Caritte V, Acha S, Shah N, 2013, Enhancing corporate environmental performance through reporting and roadmaps, Business Strategy and the Environment, Vol: 24, Pages: 289-308, ISSN: 1099-0836
Managing the carbon footprint of companies and addressing their respective decarbonization plans is a challenging endeavour. The aim of this study is to help companies better understand the issues around decarbonization and environmental performance by suggesting a holistic management process on which they could embark. This process comprises two crucial steps, which are (a) sustainability reporting and (b) low-carbon roadmaps. These steps are covered and further developed based on a detailed study of the UK food retail sector. This sector is relevant due to its economic and environmental importance, but most importantly it has a significant record of available environmental reports in the public domain and a large potential to influence consumers, policy makers and multiple supply chains.Sustainability reporting is assessed by analysing environmental KPIs disclosed in corporate social responsibility (CSR) reports, and then these are compared against industry standards. This analysis highlights a general lack of consistency and transparency in CSR reporting of UK food retailers. Consequently, a low-carbon roadmap based on relevant KPIs and on the ‘backcasting’ framework is presented as a case study in order to showcase how a hypothetical UK food retailer can employ a low-carbon roadmap. The case study demonstrates that ambitious environmental targets are achievable if robust corporate action plans are followed. Furthermore, the case study indicates that capital might be misallocated in favour of highly visible environmental stores and on-site energy generation technologies, whilst more could be done by applying energy efficiency measures that have the potential to deliver substantial carbon savings.
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