Publications
79 results found
Olympios A, Le Brun N, Acha Izquierdo S, et al., 2019, Installation of a dynamic controller for the optimal operation of a CHP engine in a supermarket under uncertainty, ECOS2019: 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.
Sorrentino A, Pantaleo AM, Markides C, et al., 2018, Energy performance and profitability of biomass boilers in commercial sector: the case study of Sainsbury’s stores in the UK, 73rd Conference of the Italian Thermal Machines Engineering Association (ATI 2018), Publisher: Elsevier, Pages: 539-646, ISSN: 1876-6102
Commercial buildings or shopping malls are characterized by large thermal and electrical energy consumptions with high variability of energy demand. Therefore, there is a large interest to explore novel renewable energy generation systems for these applications. A novel flexible configuration of biomass-fired CHP system with organic Rankine cycle(ORC) is here proposedand applied to the case study of Sainsbury’s supermarkets in the UK.The proposed configuration adoptsa molten salt (MS) circuitto transfer heat from the biomass furnace to the ORC plant. A thermal Energy Storage (TES) is proposedtoimprove the flexible operation of the plantand reduce the size of the biomass boiler. Molten salts have been preferredto thermal oil as they have no fire risks and low environmental impactand can be used as medium for a Two Tank TES with a “direct heating” scheme. The planthas beenanalysedusing real input data of biomass boiler installed, conversion efficiency and heat demand from the store. The model is informed by hourly energy costs and electricity feed in tariff in order to define optimal size and operation of the bottoming ORC for the specific case study of large commercial energy end userin the UK.The results show that the use of thermal storage in a biomass-fired ORC plant can improve the boiler efficiency and reduce the biomass consumption in thermal-load following operating mode and increase the investment profitability.
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, Shah N, Markides C, et al., 2018, Fuel cells as CHP systems in commercial buildings: a case study for the food retail sector, 2018 ASHRAE Annual Conference, Publisher: ASHRAE
This study investigates fuel cells as combined heat and power systems (CHPs) for distributed applications in commercial buildings, specifically supermarkets. Up-to-date technical data from a specialized manufacturing company wasinvestigated and used to conduct a case study analysis on several food retail buildings using half-hourly historical data. A detail mathematical model, described in previous publications (Cedillos et al. 2016, Achaet al.2018), was used to simulate the performance of fuel cells through a year of operation in each supermarket. The simulations employ comprehensive energy market costing data and practical informationto evaluate project feasibility such as installation workcosts. The results of the simulations are discussed and a techno-economic assessment is conducted to evaluate the main factors affecting the economics of fuel cell projects.In addition, a comparative analysis with competing CHP technologies (internal combustion engines) is covered. Results show that fuel cells are becoming financially competitivealthough combustion engines are still amoreviableoption. For large-size supermarketsthe payback time forinstalling a fuel cell system is 4.7-5.6years versus 3.6-5.6years for internal combustion engines. The work alsodiscusses the prospects of fuel cells under different market and policy scenariosas well astechnologicalimprovements; thus,offering insights in what are the key aspects which can foster fuel cell installations
Acha Izquierdo S, Lambert R, Le Brun N, et al., 2018, Optimal CHP investments applying sensitivity analyses and financial risk management indicators, 2018 ASHRAE Annual Conference, Publisher: ASHRAE
Evaluating combined heat and power (CHP) investments for commercial applications is not a straightforward task.This work assesses the impact multipletechno-economicuncertainties can have on CHP investments.Understanding the impact these uncertaintiescanhave on projectviabilityallows decision-makers to make informed decisions on capital intensive projects. In this work,amathematical model described previously (Cedillos et al.)wasused to select the optimal CHP size and calculate a reference solution on the financial viability of such investments in a set of buildings. After generating these reference CHP solutions, the impact of uncertainty is then assessed by applying Monte-Carlo based sensitivity analyses and financial and risk management key performance indicators (KPIs). Results suggest thefour most influential parameters in CHP priojects areheating demand, installation costs, electricity prices, and electricity demand. For attractive investments cost uncertainty made projects vary in their payback from2.6 to 6.9years, while for unattractive investments payback ranged from 4 to 11.3 years. Furthermore, Monte-Carlo results illustrate thedifferent distributions of each project, with significant variations in tails risks; indicating which sites are more suitable than others. Results presented show the economic impactuncertainties have onCHP projects, hence allowing decision-makers to make informed decisions before committing their resources to such capital-intensive projects.
Chimento J, Gonzato S, O’Dwyer E, et al., 2018, District-level coordination of predictive control strategies for urban residential heating networks
Urban energy systems represent a significant proportion of global energy consumption, with residential and commercial buildings accounting for around 40%. This could be significantly reduced through the use of smarter control strategies for space heating. In district heating networks, the supply limitations associated with the electrical grid can lead to a misalignment between the locally optimal objectives of the individual dwellings and the globally optimal objective of the district. In this paper, a methodology is developed for coordinating a decentralised set of building heating subsystems within a district heating network by deriving a dynamic electricity price signal and communicating it to the network in order to satisfy a power supply limit. The price signal is transmitted by a high-level coordinator which discourages power usage when necessary. It was found that power supply limits could be satisfied in this way but only above a threshold value of 180 kW for the particular district, while lower values on the limit led to instability in the form of power shortages and occupant discomfort.
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 PV and battery storage systems for UK non-domestic buildings, ASHRAE Annual Conference, Publisher: ASHRAE, ISSN: 2578-5257
his paper presents an end-user technology selection and operation (TSO) optimisation model which simultaneously optimizes the selection, design and operation of photovoltaic(PV)and battery systems in the context of commercial buildings integration. Thismodelserves to guidebusiness decision makers by assessing investment attractivenessand strategies. A strong feature of themodel is that it encompasses whole life costing and carbon emissionswhile taking into accountbuilding loads and features. Input data relies on historic metered electricity demand and irradiance levels combined with real-time and forecasted UK electricity pricesat half-hourly intervals, hence providing more comprehensive results than previous works. For a selected building and from a portfolio of technologies, a mixed-integer linear programming model selects an optimal combination of technologies and capacities while establishing the optimum operational strategy that provides the best return on investment.The case study of aretail distribution centre is provided to highlight the capabilities of the model. Results showcase the model provides valuable insights into project evaluation and thus reducesthe uncertainty associated with high capital projects. Overall,attractive PV and battery storage systems investments can be identified for UK commercial buildingsthrough the implementation of integratedoptimization models.
Efstratiadi M, Acha Izquierdo S, Shah N, et al., 2017, Analysis of a closed-loop water-cooled refrigeration system in the food retail industry: A UK case study, 2017 ASHRAE Annual Conference, Publisher: ASHRAE, ISSN: 2578-5257
The need for refrigeration in the food retail industry and specifically in supermarkets, currently accounts for about 30% to 60% of the total energy consumed in the UK stores. A key characteristic of this consumption, is the high amount of low-grade heat rejected by the condensation units to the ambient air. The aim of this study, which focuses on transcritical CO2 (R744) refrigeration cycles, is to assess whether the use of a water-cooled condenser rejecting heat to the soil via an intermediate closed-loop water-circuit, can improve the overall cooling performance, while also considering the economic implications of this modifications. In this work, a detailed model simulating the operation of an existing supermarket refrigeration system is presented and validated against field data measurements taken from a refrigeration system in a UK supermarket. The examined direct-expansion system comprises an air-cooled condenser coupled with two sets of compressors for the provision of intermediate and low-temperature cooling. This baseline model is then modified and used to evaluate the performance of a similar system, in which a water-cooled condenser is used instead of the existing air-cooled unit or in parallel to it. Preliminary results indicate that the use of water-cooled condensers has the potential to reduce the energy consumption of these refrigeration systems by up to a factor of 5 when the external temperature is high. However, in cold ambient conditions, the air-cooled condensers reject 10% less heat, resulting in a better system performance. Furthermore, a more thorough case study is developed in order to examine the yearly operation of the existing system, and to compare this to various water-cooled alternatives. The analysis indicates a reduction of approximately 3% in the energy consumed by the water-cooled system (compared to the reference benchmark air-cooled system), and a reduction of almost 6%, for a hybrid system with coupled air-cooled and water-coole
Garcia AS, Acha S, Shah N, et al., 2017, Half-Hourly Regional Electricity Price Modelling for Commercial End Users in the UK, ASHRAE Annual Conference, Publisher: ASHRAE, ISSN: 2578-5257
This paper details a methodology to model half-hourly electricity priceprofiles fortheUK commercial end-users; thus allowing consumersto visualize and calculate more accurately thecost of the electricitythey consume.The methodologyconsistsin a bottom-up model that definesindividuallyall the tariff components of the bill and thenaggregatesthemto quantify the cost of a kWh across the day. In this work ,‘representative day’ electricity price curves for different months, day types, voltage levels connections, and regionsinthe UKfrom 2015 up to 2020are presented.Outputs from this work can informcompaniesto better understand their energy costs and accurately perform economic assessments of investments inschemes that reduce emissions andaim towardsreachingnet zero energy buildings. In addition, the disaggregated structure of the model allows specific analysis ofindividual components thus highlighting which elements carry a larger weight on costs across the year; such as network charges originatedfrom distribution and transmission system operators. Due to its multi-variable dependency, the model produces more than5,000 representative day curves. The results show that thosecommercial buildingsconnected to Low Voltage (LV) in North Wales and Merseyside, Northern Scotland, the South West and South Wales face the highest average electricity prices, whereas consumers connected to HV in London and Yorkshire have the cheapest electricity in the UK.
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., 2017, 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, 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, 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, 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, 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, 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, Mavromatidis G, Caritte V, et al., 2016, 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
Acha S, Le Brun N, Lambert R, et al., 2016, UK half-hourly regional electricity cost modelling for commercial end users
The rising prices of electricity in the UK risks rendering businesses uncompetitive if these costs are not controlled. This issue has created the need to properly comprehend the tariffs and costing framework that influence the total cost of electricity for non-domestic customers. This paper details an open source method to model UK electricity regional costs (MUKERC) for commercial end-users; allowing users to visualise and calculate the cost of the electricity they consume. The methodology consists in a bottom-up model that defines individually all the tariff components and then aggregates them to quantify the cost of a kWh across each half-hour of the day. The disaggregated structure of MUKERC allows users to conduct specific analysis of tariff components and to understand their rich temporal and spatial features. This granularity facilitates understanding which tariffs influence costs more during different time periods. Emphasis is given to showcasing commodity prices and network charges; known as Transmission Use of System and Distribution Use of System tariffs. ‘Representative day’ electricity price curves for different day types, voltage level connections, and across different UK regions for 2016-17 are presented. Outputs from MUKERC can better inform companies on their energy costs and therefore allows them to perform comprehensive and bespoke energy management and energy efficiency strategies as it is possible to understand when and where the cost of electricity is more expensive. Results show that commercial buildings connected at Low Voltage in North Wales and Merseyside and the South West face the highest average electricity prices, whereas consumers connected to High Voltage in London and the North West have the cheapest electricity in the UK. Other significant findings indicate sites connected at low-voltage pay 7.5% more than high-voltage sites, winter weekday costs are 18% higher than summer weekday costs, and overall weekdays are 35% more
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
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Acha Izquierdo S, Bustos-Turu G, Shah N, 2015, Modelling the business case to run on-site generators in UK commercial buildings through real-time electricity pricing, 2015 ASHRAE Energy Modeling Conference, Publisher: ASHRAE
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