Publications
79 results found
Wang Z, Acha S, Bird M, et al., 2024, A total cost of ownership analysis of zero emission powertrain solutions for the heavy goods vehicle sector, Journal of Cleaner Production, Vol: 434, ISSN: 0959-6526
Transport-related activities represented 34% of the total carbon emissions in the UK in 2022 and heavy-duty vehicles (HGVs) accounted for one-fifth of the road transport greenhouse gas (GHG) emissions. Currently, battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (FCEVs) are considered as suitable replacements for diesel fleets. However, these technologies continue to face techno-economic barriers, creating uncertainty for fleet operators wanting to transition away from diesel-powered internal combustion engine vehicles (ICEVs). This paper assesses the performance and cost competitiveness of BEV and FCEV powertrain solutions in the hard-to-abate HGV sector. The study evaluates the impact of battery degradation and a carbon tax on the cost of owning the vehicles. An integrated total cost of ownership (TCO) model, which includes these factors for the first time, is developed to study a large retailer's HGV fleet operating in the UK. The modelling framework compares the capital expenditures (CAPEX) and operating expenses (OPEX) of alternative technologies against ICEVs. The TCO of BEVs and FCEVs are 11% to 33% and 37% to 78% higher than ICEVs; respectively. Despite these differences, by adopting a longer lifetime for the vehicle it can effectively narrow the cost gap. Alternatively, cost parity with ICEVs could be achieved if BEV battery cost reduces by 56% or if FCEV fuel cell cost reduces by 60%. Besides, the pivot point for hydrogen price is determined at £2.5 per kg. The findings suggest that BEV is closer to market as its TCO value is becoming competitive, whereas FCEV provides a more viable solution than BEV for long-haul applications due to shorter refuelling time and lower load capacity penalties. Furthermore, degradation of performance in lithium-ion batteries is found to have a minor impact on TCO if battery replacement is not required. However, critical component replacement and warranty can influence commercial viability. Given
Soh QY, ODwyer E, Acha S, et al., 2023, Robust optimisation of combined rainwater harvesting and flood mitigation systems, Water Research, Vol: 245, ISSN: 0043-1354
Combined large-scale rainwater harvesting (RWH) and flood-mitigation systems are promising as a sustainable water management strategy in urban areas. These are multi-purpose infrastructure that not only provide a secondary, localised water resource, but can also reduce discharge and hence loads on any downstream wastewater networks if these are integrated into the wider water network. However, the performance of these systems is dependent on the specific design used for its local catchment which can vary significantly between different implementations. A multitude of design strategies exist, however, there is no universally accepted standard framework. To tackle these issues, this paper presents a two-player optimisation framework which utilises a stochastic design optimisation model and a competing, high intensity rainfall design model to optimise passively operated RWH systems. A customisable tool set is provided, under which optimisation models specific to a given catchment can be built quickly. This reduces the barriers to implementing computationally complex sizing strategies and encouraging more resource-efficient systems to be built. The framework was applied to a densely populated high-rise residential estate, eliminating overflow events from historical rainfall. The optimised configuration resulted in a 32% increase in harvested water yield, but its ability to meet irrigation demands was limited by the operational levels of the treatment pump. Hence, with the inclusion of operational levels in the optimisation model, the framework can provide an efficient large-scale RWH system that is capable of simultaneously meeting water demands and reducing stresses within and beyond its local catchment.
Sarabia-Escriva E-J, Soto-Francés V-M, Pinazo-Ojer J-M, et al., 2023, Economic and environmental analysis of domestic hot water systems for single-family homes, Energy and Buildings, Vol: 286, Pages: 1-16, ISSN: 0378-7788
The objective of this article is to compare the behaviour of the most representative domestic hot water systems (DHW) in single-family buildings. The study evaluates the energy consumption, equivalent CO2 emissions and cost for each system over a 15-year life period. This analysis is carried out in four climatic zones across Europe to observe the influence of climatic conditions on the results. The four climatic zones are located in the cities of Athens, Madrid, London and Berlin. The analysed systems are: a) natural gas-fired instantaneous water heaters, b) electric storage water heater, c) solar thermal system with gas-fired instantaneous, d) solar thermal system with electric storage water heater, e) air-source heat pump, f) photovoltaic system with electric storage water heater, and g) photovoltaic system with air-source heat pump. This range of technologies covers the most likely solutions to be implemented across domestic buildings in Europe.The heat pump system (HPWH) with PV considering self-consumption shows the lowest environmental impact in all zones, but is not an attractive investment in the coldest zones due to lower natural gas prices. Thermal solar systems have a high purchase and maintenance costs which do not compensate their energy savings. The PV HPWH system has a greater reduction of emissions and a lower cost than HPWH across a 15-year life. The gas boiler system has the lowest cost in a 15-year period in the coldest areas, despite having a greater environmental impact than the heat pump.
Acha Izquierdo S, vieira G, Bird M, et al., 2022, Modelling UK electricity regional costs for commercial buildings, Energy and Buildings, Vol: 271, Pages: 1-15, ISSN: 0378-7788
Motivated by rising electricity prices UK non-domestic consumers are being required to develop smart energy management practices. However, most of these consumers lack awareness of the spatial-temporal dynamics of electricity prices and their tariff components. To help overcome these barriers and contribute to energy prices digitalisation, this paper presents a Modelling UK Electricity Regional Costs (MUKERC) framework. A bottom-up methodology that defines all the tariff components and then aggregates them to quantify the cost of a kWh across each half-hour of the day. The framework not only facilitates understanding which tariffs components have a higher impact during different time periods but also depicts how they vary spatially across regions. This model was used to estimate and analyse the evolution of electricity costs from 2017 to 2024. Case studies from buildings in the education sector are showcased depicting their energy costs derived from their load profiles. Results show that the London area has the lowest average prices, while the Northern Wales & Merseyside is the most expensive. From the case studies conducted, peak period charges account for 17% of annual electricity costs (occurring between 4 to 7 p.m.). Winter period charges represented about 53% of the charges. The MUKERC framework showcases the valuable insights data-driven costing models offer as it allows to understand the dynamics of electricity charges and identifies “when” and “where” the cost of electricity is more expensive; thus, supporting the development of bespoke cost-effective energy measures that improve resource efficiency and smart energy management initiatives.
Bird M, Daveau C, O'Dwyer E, et al., 2022, Real-world implementation and cost of a cloud-based MPC retrofit for HVAC control systems in commercial buildings, Energy and Buildings, Vol: 270, Pages: 1-13, ISSN: 0378-7788
Many businesses are looking for ways to improve the energy and carbon usage of their buildings, particularly through enhanced data collection and control schemes. In this context, this paper presents a case study of a food-retail building in the UK, detailing the design, installation and cost of a generalisable model predictive control (MPC) framework for its Heating, Ventilation and Air Conditioning (HVAC) system. The hardware/software solution to collect relevant data, as well as the formulation of the MPC scheme, is presented. By utilising cloud-based microservices, this approach can be applied to all modern building management systems with little upfront capital, and an ongoing monthly cost as low as $6.39/month. The MPC scheme calculates the optimal temperature setpoint required for each Air-Handling Unit (AHU) to minimise its overall cost or carbon usage, while ensuring thermal comfort of occupants. Its performance is then compared to the existing legacy controller using a simulation the building’s thermal behaviour. When simulated across two months the MPC approach performed better, able to achieve the same thermal comfort for a lower overall cost. The economic optimisation resulted in an energy saving of 650 kWh, with an associated cost savings of $240 (1.7% compared to the baseline), while the carbon optimisation gave negligible CO2 savings due to the inability of the building to shift heating to low-carbon periods. Findings from this study indicate the potential for improving building performance via MPC strategies but impact will depend on specific building attributes.
Li K, Acha Izquierdo S, Sunny N, et al., 2022, Strategic transport fleet analysis of heavy goods vehicle technology for net-zero targets, Energy Policy, Vol: 168, ISSN: 0301-4215
This paper addresses the decarbonisation of the heavy-duty transport sector and develops a strategy towards net-zero greenhouse gas (GHG) emissions in heavy-goods vehicles (HGVs) by 2040. By conducting a literature review and a case study on the vehicle fleet of a large UK food and consumer goods retailer, the feasibilities of four alternative vehicle technologies are evaluated from environmental, economic, and technical perspectives. Socio-political factors and commercial readiness are also examined to capture non-technical criteria that influences decision-makers. Strategic analysis frameworks such as PEST-SWOT models were developed for liquefied natural gas, biomethane, electricity and hydrogen to allow a holistic comparison and identify their long-term deployment potential. Fossil and renewable natural gas are found to be effective transitional solutions. Technology innovation is needed to address range and payload limitations of electric trucks, whereas government and industry support are essential for a material deployment of hydrogen in the 2030s. Given the UK government’s plan to phase out new diesel HGVs by 2040, fleet operators should commence new vehicle trials by 2025 and replace a considerable amount of their lighter diesel trucks with zero-emission vehicles by 2030, and the remaining heavier truck fleet by 2035.
O'Dwyer E, Indranil P, Shah N, 2022, Decarbonisation of the urban landscape: integration and optimization of energy systems, Intelligent Decarbonisation: Can Artificial Intelligence and Cyber-PhysicalSystems Help Achieve Climate MitigationTargets?, Editors: Inderwildi, Kraft, Publisher: Springer, ISBN: 978-3030862145
We highlight the key pillars of urban energy systems which would leverage on AI and digital technologiesfor a low carbon future. We summarise a couple of real world applications where optimisation, intelligentcontrol systems and cloud based infrastructure have played a transformative role in improving systemperformance, cost effectiveness and decarbonisation. The case studies show that AI and digitaltechnologies can be implemented for standalone unit operations to achieve such benefits. However, moreimportantly as the second case study shows, applying such technologies at a system level by integratingmultiple energy vectors would give much more flexibility in terms of operation, resulting in betterperformance improvements and decarbonisation strategies. We conclude by highlighting the strategictrends in this fast evolving field and giving a broad outlook in terms of cost reductions and emissionssavings for similar intelligent energy systems.
Gulliford MJS, Orlebar RH, Bird MH, et al., 2022, Developing a dynamic carbon benchmarking method for large building property estates, Energy and Buildings, Vol: 256, Pages: 111683-111683, ISSN: 0378-7788
As supermarkets are known to be energy intensive, improvements made to their efficiency can enable operators to reduce not only carbon emissions but also costs, in line with corporate and legislative targets. This study presents a novel benchmarking method to appraise emission and cost performances across a portfolio, enabling building managers to identify sites that are underperforming, taking as a case study a large number of food retail stores. Multiple layers, detailed variable selection including weather features and regression technique comparisons (Multivariate Linear Regression (MLR), Artificial Neural Network (ANN) and Decision Tree (DT)), are considered in model construction. Efficiency is evaluated on multiple bases with a focus on emissions. These are clustered together to produce a benchmark to inform investment decision-making across a portfolio. The DT technique was found to be the most effective, producing a benchmark with low average error (1.5 kgCO2 m−2 period−1) and high maximum error (21 kgCO2 m−2 period−1) indicating high accuracy and high discernment respectively. This model also correctly classified buildings known to perform poorly into the worst 30% of buildings in the portfolio. This work highlights the need for further research into natural gas consumption benchmarking and particularly the use of humidity data to better understand the issues in decarbonising heat.
Soh QY, O'Dwyer E, Acha S, et al., 2022, Model agnostic framework for analyzing rainwater harvesting system behaviors, Computer Aided Chemical Engineering, Pages: 2023-2028
To evaluate risks and characterise the responses of a rainwater harvesting system under different rainfall types, this paper presents a model agnostic evaluation framework where a k-means clustering approach is supplemented with a statistical Partial Least Squares model. Four response modes were identified for a studied system. Using these response modes, a higher risk of system overflow was found in 4.5% of simulated scenarios with inadequate water supplies found in 48.2% scenarios. The rainfall distribution in time was found to be crucial in determining the response mode of the system, with sporadic high intensity events or consistent, high total volume events allowing the system to operate in a response mode corresponding to lower system stresses, but with reduced provision of rainwater.
Sarabia Escriva EJ, Hart M, Acha Izquierdo S, et al., 2022, Techno-economic evaluation of integrated energy systems for heat recovery applications in food retail buildings, Applied Energy, Vol: 305, ISSN: 0306-2619
Eliminating the use of natural gas for non-domestic heat supply is an imperative component of net-zero targets. Techno-economic analyses of competing options for low-carbon heat supply are essential for decision makers developing decarbonisation strategies. This paper investigates the impact various heat supply configurations can have in UK supermarkets by using heat recovery principles from refrigeration systems under different climatic conditions. The methodology builds upon a steady-state model that has been validated in previous studies. All refrigeration integrated heating and cooling (RIHC) systems employ CO2 booster refrigeration to recover heat and provide space heating alongside various technologies such as thermal storage, air-source heat pumps (ASHPs) and direct electric heaters. Seven cases evaluating various technology combinations are analysed and compared against a conventional scenario in which the building is heated with a natural gas boiler. The specific combinations of technologies analysed here contrasts trade-offs and is a first in the literature. The capital costs of these projects are considered, giving insights into their business case. Results indicate that electric heaters are not cost-competitive in supermarkets. Meanwhile, RIHC and ASHP configurations are the most attractive option, and if a thermal storage tank system with advanced controls is included, the benefits increase even further. Best solutions have a 6.3% ROI, a payback time of 16 years while reducing energy demand by 62% and CO2 emissions by 54%. Such investments will be difficult to justify unless policy steers decision makers through incentives or the business case changes by implementing internal carbon pricing.
Acha S, O’Dwyer E, Pan I, et al., 2022, Decarbonisation of the Urban Landscape: Integration and Optimization of Energy Systems, Lecture Notes in Energy, Pages: 133-144
We highlight the key pillars of urban energy systems which would leverage on AI and digital technologies for a low carbon future. We summarise a couple of real world applications where optimisation, intelligent control systems and cloud-based infrastructure have played a transformative role in improving system performance, cost-effectiveness and decarbonisation. The case studies show that AI and digital technologies can be implemented for standalone unit operations to achieve such benefits. However, more importantly as the second case study shows, applying such technologies at a system level by integrating multiple energy vectors would give much more flexibility in terms of operation, resulting in better performance improvements and decarbonisation strategies. We conclude by highlighting the strategic trends in this fast evolving field and giving a broad outlook in terms of cost reductions and emissions savings for similar intelligent energy systems.
Acha Izquierdo S, Shah N, Soler A, 2021, Best practices to mitigate CO2 operational emissions: a case study of the Basque Country energy ecosystem, Ekonomiaz Basque Economic Review, Vol: 99, ISSN: 0213-3865
This work reviews the best practices to reduce CO2 emissions in energy intensive organizations and energy value-chains by highlighting the synergy that can be built with like-minded organizations via collaborations; taking the Basque Country as a case study. An academic review covers how corporate strategies are attempting to curtail emissions in a systematic manner. The study is then complimented by findings obtained from interviews of key stakeholders in the Basque Country responsible for playing an important role in implementing a green agenda. The interviews allow us to highlight flagship projects and assess the collaborative framework strengths and challenges. Results indicate that organizations are well underway in implementing and researching low carbon solutions, but issues surrounding governance, strategy, and regulatory challenges can slow progress of goals.
Ayoub AN, Gaigneux A, Le Brun N, et al., 2021, Corrigendum to “The development of a low-carbon roadmap investment strategy to reach science based targets for commercial organisations with multi-site properties” [J. Build. Environ. 186 (2020) 107311], Building and Environment, Vol: 190, Pages: 107540-107540, ISSN: 0360-1323
Hart M, Austin W, Acha S, et al., 2020, A roadmap investment strategy to reduce carbon intensive refrigerants in the food retail industry, Journal of Cleaner Production, Vol: 275, Pages: 1-17, ISSN: 0959-6526
High global warming potential (GWP) refrigerant leakage is the second-highest source of carbon emissions across UK supermarket retailers and a major concern for commercial organizations. Recent stringent UN and EU regulations promoting lower GWP refrigerants have been ratified to tackle the high carbon footprint of current refrigerants. This paper introduces a data-driven modelling framework for optimal investment strategies supporting the food retail industry to transition from hydrofluorocarbon (HFC) refrigeration systems to lower GWP systems by 2030, in line with EU legislation. Representative data from a UK food retailer is applied in a mixed integer linear model, making simultaneous investment decisions across the property estate. The model considers refrigeration-system age, capacity, refrigerant type, leakage and past-performance relative to peer systems in the rest of the estate. This study proposes two possible actions for high GWP HFC refrigeration systems: a) complying with legislation by retrofitting with an HFO blend (e.g. R449-A) or b) installing a new natural refrigerant system (e.g. R744). Findings indicate that a standard (i.e. business-as-usual) investment level of £6 m/yr drives a retrofitting strategy enabling significant reduction in annual carbon emissions of 71% by the end of 2030 (against the 2018 baseline), along with meeting regulatory compliance. The strategy is also highly effective at reducing emissions in the short term as total emissions during the 12-year programme are 59% lower than would have been experienced if the HFC emissions continued unabated. However, this spending level leaves the business at significant risk of refrigeration system failures as necessary investments in new systems are delayed resulting in an ageing, poorly performing estate. The model is further tested under different budget and policy scenarios and the financial, environmental, and business-risk implications are analysed. For example, under a more agg
Ayoub AN, Gaigneux A, Le Brun N, et al., 2020, The development of a low-carbon roadmap investment strategy to reach Science Based Targets for commercial organisations with multi-site properties, Building and Environment, Vol: 186, Pages: 1-17, ISSN: 0360-1323
The Paris Climate Agreement has motivated commercial organisations to set and work towards Science Based Targets, a realignment of greenhouse gas emissions in line with climate science. This work presents a modelling framework to develop cost-effective decarbonisation investment programs that address electricity and heat carbon emissions in organisations with multiple properties. The case study takes a set of 60 supermarkets in the UK and evaluates the techno-economic viability of installing biomethane combined heat and power engines and photovoltaic panels to make them zero carbon buildings. Simulation results from the batch of buildings offer the financial and environmental benefits at each site and generates a set of regression coefficients which are then applied into an optimisation problem. Solving the optimisation yields the decarbonisation investment strategy for the estate up to 2050; indicating the preferred sequence of investments the company needs to undertake to embark upon an effective low-carbon roadmap. A sensitivity analysis compliments the study to understand how market and policy externalities may influence roadmaps. Results suggest a CAPEX ranging from £57-£80 million is required to deliver an ambitious decarbonisation plan, while OPEX and carbon savings benefits range between £197 and £683 million and 461–715 ktCO2e; respectively. The case study highlights that although carbon targets can be achieved by 2030, the 2050 targets are more challenging to meet; suggesting additional technologies and policies should be considered and implemented. The framework serves as a blueprint of how modelling can assist decision-makers in reducing their carbon footprint cost-effectively to reach Science Based Targets.
Le Brun N, Simpson M, Acha S, et al., 2020, Techno-economic potential of low-temperature, jacket-water heat recovery from stationary internal combustion engines with organic Rankine cycles: A cross-sector food-retail study, Applied Energy, Vol: 274, Pages: 1-14, ISSN: 0306-2619
We examine the opportunities and challenges of deploying integrated organic Rankine cycle (ORC) engines to recover heat from low-temperature jacket-water cooling circuits of small-scale gas-fired internal combustion engines (ICEs), for the supply of combined heat and power (CHP) to supermarkets. Based on data for commercially-available ICE and ORC engines, a techno-economic model is developed and applied to simulate system performance in real buildings. Under current market trends and for the specific (low-temperature) ICE + ORC CHP configuration investigated here, results show that the ICE determines most economic savings, while the ORC engine does not significantly impact the integrated CHP system performance. The ORC engines have long payback times (4–9 years) in this application, because: (1) they do not displace high-value electricity, as the value of exporting electricity to the grid is low, and (2) it is more profitable to use the heat from the ICEs for space heating rather than for electricity conversion. Commercial ORC engines are most viable (payback ≈ 4 years) in buildings with high electrical demands and low heat-to-power ratios. The influence of factors such as the ORC engine efficiency, capital cost and energy prices is also evaluated, highlighting performance gaps and identifying promising areas for future research.
Acha Izquierdo S, Le Brun N, Damaskou M, et al., 2020, Fuel cells as combined heat and power systems in commercial buildings: A case study in the food-retail sector, Energy, Vol: 206, Pages: 1-13, ISSN: 0360-5442
This work investigates the viability of fuel cells (FC) as combined heat and power (CHP) prime movers in commercial buildings with a specific focus on supermarkets. Up-to-date technical data from a FC manufacturing company was obtained and applied to evaluate their viability in an existing food-retail building. A detailed optimisation model for enhancing distributed energy system management described in previous work is expanded upon to optimise the techno-economic performance of FC-CHP systems. The optimisations employ comprehensive techno-economic datasets that reflect current market trends. Outputs highlight the key factors influencing the economics of FC-CHP projects. Furthermore, a comparative analysis against a competing internal combustion engine (ICE) CHP system is performed to understand the relative techno-economic characterisitcs of each system. Results indicate that FCs are becoming financially competitive although ICEs are still a more attractive option. For supermarkets, the payback period for installing a FC system is 4.7–5.9 years vs. 4.0–5.6 years for ICEs when policies are considered. If incentives are removed, FC-CHP systems have paybacks in the range 6–10 years vs. 5–8.5 years for ICE-based systems. A sensitivity analysis under different market and policy scenarios is performed, offering insights into the performance gap fuel cells face before becoming more competitive.
Olympios AV, Le Brun N, Acha S, et al., 2020, Stochastic real-time operation control of a combined heat and power (CHP) system under uncertainty, Energy Conversion and Management, Vol: 216, Pages: 1-17, ISSN: 0196-8904
In this paper we present an effort to design and apply a multi-objective real-time operation controller to a combined heat and power (CHP) system, while considering explicitly the risk-return trade-offs arising from the uncertainty in the price of exported electricity. 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 in real-world applications. In this work, a two-stage control architecture is proposed which applies an optimization framework to a real CHP operation application involving intelligent communication between two controllers to monitor and control the engine continuously. Since deterministic approaches that involve no measure of uncertainty provide limited insight to decision-makers, the methodology then proceeds to develop a stochastic optimization technique which considers risk within the optimization problem. The uncertainty in the forecasted electricity price is quantified by using the forecasting model’s residuals to generate prediction intervals around each forecasted electricity price. The novelty of the proposed tool lies in the use of these prediction intervals to formulate a bi-objective function that represents a compromise between maximizing the expected savings and minimizing the associated risk, while satisfying specified environmental objectives. This allows decision-makers to operate CHP systems according to the risk they are willing to take. The actual operation costs during a 40–day trial period resulting from the installation of the dynamic controller on an existing CHP engine that provides electricity and heat to a supermarket are presented. Results demonstrate that the forecasted electricity price almost always falls within the developed prediction intervals, achieving savings of 23% on energy costs against
Georgios M, Emilio Jose S, Acha Izquierdo S, et al., 2020, CO2 refrigeration system heat recovery and thermal storage modelling for space heating provision in supermarkets: An integrated approach, Applied Energy, Vol: 264, ISSN: 0306-2619
The large amount of recoverable heat from CO2 refrigeration systems has led UK food retailers to examine the prospect of using refrigeration integrated heating and cooling systems to provide both the space heating and cooling to food cabinets in supermarkets. This study assesses the performance of a refrigeration integrated heating and cooling system installation with thermal storage in a UK supermarket. This is achieved by developing a thermal storage model and integrating it into a pre-existing CO2 booster refrigeration model. Five scenarios involving different configurations and operation strategies are assessed to understand the techo-economic implications. The results indicate that the integrated heating and cooling system with thermal storage has the potential to reduce energy consumption by 17–18% and GHG emissions by 12–13% compared to conventional systems using a gas boiler for space heating. These reductions are achieved despite a marginal increase of 2–3% in annual operating costs. The maximum amount of heat that can be stored and utilised is constrained by the refrigeration system compressor capacity. These findings suggest that refrigeration integrated heating and cooling systems with thermal storage are a viable heating and cooling strategy that can significantly reduce the environmental footprint of supermarket space heating provision and under the adequate circumstances can forsake the use of conventional fossil-fuel (natural gas) boiler systems in food-retail buildings.
Hart MBP, Olympios A, Le Brun N, et al., 2020, Pre-feasibility modelling and market potential analysis of a cloud-based CHP optimiser, 2020 ASHRAE Annual Conference (Virtual), Publisher: ASHRAE, Pages: 300-307
Smart control system technologies for combined heat and power (CHP) units arenot previously reported in literature, and have potential to generate significant savings. Only minimal capital investment is required in infrastructure and software development. A live cloud-based solution has therefore been developed,and installed in a real UK supermarket store, to optimise CHP output based upon predicted price forecasts,and live electricity and head demand data. This has allowed validation of the optimiser price forecasts, and predicted cost savings, anda model of the optimiser has therefore been applied to three case study sites. The model itself has also been validated against the installed optimiser data.The pre-feasibility analysis undertaken indicates cost savings between 2% and 12%.CHP units sized within the feasible operating range, above a part loadlevelof 0.65, generate the greatest percentage savings. This is because the optimiser has the greatest flexibility to control the CHP output. However, larger units, even though less nearly optimal,may actually generate greater overall savings and would therefore be targeted for earlier optimiser implementation. Installation costs are not expected to vary greatly from site-to-site. Some stores, though,show no material improvement over the existing control systems, demonstrating the valueof the pre-feasibility analysis using the model.Though waste heat increases significantly with all strategies, the propensity to sell this heat within the UK is likely to improvein the near future.
Sarabia EJ, Acha Izquierdo S, Le Brun N, et al., 2020, Modelling of a CO2 refrigerant booster system for waste heat recovery applications in retail for space heating provision, 2020 ASHRAE Annual Conference (Virtual), Publisher: ASHRAE
This paper compares and quantifies the energy, environmental and economic benefits of various control strategies for recovering heat from a supermarket’s CO2 booster refrigeration system. There covered heat is used for space heating, with the goal of displacing natural gas fueled boilers. A theoretical model with thermal storage is presentedbased on a previous validated model from an existing refrigeration system in a food-retail building located in the UK. Sixheat recovery strategies are analysed by modifying thermal storage volumes and pressure levels in the gas-cooler/condenser. The model shows that a reduction of 30-40% in natural-gasc onsumption is feasible by the installation of a de-superheater and without any advanced operating strategy, and 40-50% by using a thermal storage tank. 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 35%, while the best economic strategy can reduce costs by 11%. 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.
Langshaw L, Ainalis D, Acha Izquierdo S, et al., 2020, Environmental and economic analysis of liquefied natural gas (LNG) for heavy goods vehicles in the UK: A Well-to-Wheel and total cost of ownership evaluation, Energy Policy, Vol: 137, Pages: 1-15, ISSN: 0301-4215
This paper evaluates the environmental and economic performance of liquefied natural gas (LNG) as a transition fuel to replace diesel in heavy goods vehicles (HGVs). A Well-to-Wheel (WTW) assessment based on real-world HGV drive cycles is performed to determine the life-cycle greenhouse gas (GHG) emissions associated with LNG relative to diesel. The analysis is complemented with a probabilistic approach to determine the total cost of ownership (TCO) across a range of scenarios. The methodologies are validated via a case study of vehicles operating in the UK, using data provided by a large food retailer. The spark-ignited LNG vehicles under study were observed to be 18% less energy efficient than their diesel counterparts, leading to a 7% increase in WTW GHG emissions. However, a reduction of up to 13% is feasible if LNG vehicles reach parity efficiency with diesel. Refuelling at publicly available stations enabled a 7% TCO saving in the nominal case, while development of private infrastructure incurred net costs. The findings of this study highlight that GHG emission reductions from LNG HGVs will only be realised if there are vehicle efficiency improvements, while the financial case for operators is positive only if a publicly accessible refuelling network is available.
Soh QY, O'Dwyer E, Acha S, et al., 2020, Optimization and Control of a Rainwater Detention and Harvesting Tank, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 547-552
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Pozo C, Limleamthong P, Guo Y, et al., 2019, Temporal sustainability efficiency analysis of urban areas via data envelopment analysis and the hypervolume indicator: Application to London boroughs, Journal of Cleaner Production, Vol: 239, Pages: 1-14, ISSN: 0959-6526
Transitioning towards a more sustainable society calls for systematic tools to assess the sustainability performance of urban systems. To perform this task effectively, this work introduces a novel method based on the combined use of Data Envelopment Analysis (DEA) and the hypervolume indicator. In essence, DEA is applied to (i) distinguish between efficient and inefficient urban systems through the identification of best practices; and to (ii) establish improvement targets for the inefficient urban systems that, if attained, would make them efficient. Meanwhile, the hypervolume indicator is employed in conjunction with DEA to evaluate how urban systems evolve with time. The capabilities of this approach are illustrated through its application to the sustainability assessment of London boroughs between 2012–2014. Results reveal that most boroughs tend to perform well in terms of the indicators selected, with 20–25 of the 32 boroughs found efficient depending on the year. Regarding the temporal assessment, a global improvement in sustainability performance was found, with a strong relationship between the boroughs’ performances and their locations. The method proposed opens new pathways of social and environmental research for the application of advanced multi-criteria decision-support tools in the assessment and optimisation of urban systems.
Acha Izquierdo S, Le Brun N, Shah N, et al., 2019, Assessing the modelling approach and datasets required for fault detection in photovoltaic systems, IEEE Industry Applications Society Annual Meeting, Publisher: IEEE
Reliable monitoring for photovoltaic assets (PVs) is essential to ensuring uptake, long term performance, and maximum return on investment of renewable systems. To this end this paper investigates the input data and machine learning techniques required for day-behind predictions of PV generation, within the scope of conducting informed maintenance of these systems. Five years of PV generation data at hourly intervals were retrieved from four commercial building-mounted PV installations in the UK, as well as weather data retrieved from MIDAS. A support vector machine, random forest and artificial neural network were trained to predict PV power generation. Random forest performed best, achieving an average mean relative error of 2.7%. Irradiance, previous generation and solar position were found to be the most important variables. Overall, this work shows how low-cost data driven analysis of PV systems can be used to support the effective management of such assets.
Gonzato S, Chimento J, ODwyer E, et al., 2019, Hierarchical price coordination of heat pumps in a building network controlled using model predictive control, Energy and Buildings, Vol: 202, ISSN: 0378-7788
Decarbonisation of the building sector is driving the increased use of heat pumps. As increased electrification of the heating sector leads to stress on the electricity grid, the need for district level coordination of these heat pumps emerges. This paper proposes a novel hierarchical coordination methodology, in which a price coordinator reduces the total instantaneous power demand of a building network below a power supply limit using a price signal. Each building has a model predictive controller (MPC) which maximises thermal comfort and minimises electricity costs. An additional term in the MPC objective function penalises the heat pump power demand quadratically, which when multiplied by a pseudo electricity price allows the price coordinator to reduce the peak power demand of the building network. A 2 building network is studied to analyse the price coordinator algorithm’s behaviour and demonstrate how this approach yields a trade off between comfort, energy consumption and peak demand reduction. A 100 building network case study is then presented as a proof of concept, with the price coordinator approach yielding results similar to that of a centralised controller (less than 0.7% increase in energy consumption per building per year) and a roughly fourfold decrease in computation time.
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.
O'Dwyer E, Pan I, Acha Izquierdo S, et al., 2019, Modelling and evaluation of multi-vector energy networks in smart cities, International Conference on Smart Infrastructure and Construction 2019, Publisher: ICE Publishing
Energy demand growth and the rapid rate of technological changein an urban contextare already having an impact on our energy systems. Considering global ambitions to reduce carbon emissions and minimise the rate and impacts of climate change, this demand will need to be met with energy from low carbon sources. Increased electrification of heat and transport networks is anticipated, however, the cross-sectoral impacts of different interventions in these systems must be better understood to prevent gains in one system leadingto losses in another while ensuring financial benefits for producers and consumers. As such, evaluating the impacts of specific interventions can be a challenge, with analyses typically focussed on individual systems. In this paper, asimulation environment is developed to capture the behaviour of interconnected heat, power and transport networks in an urban environment to act as a ‘digital twin’ for the energy systems of a district or city. The modelling environment illustrated here is based on the smart city interventions in Greenwich (London), with model validation carried out using real data measurements. Building retrofit and heat electrification interventions are demonstrated in terms of costs, energy consumption and CO2 emissions, considering constraints on power and thermal systems.
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.
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