http://bura.brunel.ac.uk/handle/2438/8625 2026-04-26T12:36:47Z 2026-04-26T12:36:47Z Abualshawareb, A Pisica, I König, C http://bura.brunel.ac.uk/handle/2438/33215 2026-04-26T09:59:39Z 2025-09-02T00:00:00Z

Title: System Sizing of Hybrid Renewable Systems Under Inverter and Contracted Grid Power Constraints with Flexible Load Integration Authors: Abualshawareb, A; Pisica, I; König, C Abstract: Island microgrids face significant challenges, including seasonal load variations, weak interconnections, and high demand charges leading to oversized energy systems. This paper introduces a novel bi-level optimization approach, combining a genetic algorithm for capacity sizing and a rolling-horizon mixed-integer linear programming controller for daily dispatch scheduling. The method simultaneously optimizes photovoltaic arrays, battery storage, hydrogen tanks, inverter ratings, and contracted grid-import limits to minimize the net present cost. The approach was applied to a municipal energy community in Formentera, Spain, with an annual demand of approximately 203 megawatt-hours. Compared to the baseline scenario (661,677 euros), the proposed framework reduced the net present cost to 612,945 euros without load flexibility. Introducing load flexibility further decreased costs: 606,879 euros at 6 percent and 599,134 euros at 8 percent flexibility. Increased flexibility resulted in modest reductions in photovoltaic capacity from 155 to 150 kilowatt-peak, inverter size from 77 to 72 kilowatts, and contracted grid-import limits from 41 to 37 kilowatts. The findings underscore the significant economic and operational advantages of integrating demand-side flexibility into the co-optimization of component sizing, enhancing both the resilience and autonomy of islanded hybrid renewable energy systems.

2025-09-02T00:00:00Z Chen, H Radmanesh, S Zhang, B Wang, H Cheng, R Liang, C Li, C Tao Ye, T Huang, J http://bura.brunel.ac.uk/handle/2438/33170 2026-04-20T02:01:02Z 2026-04-02T00:00:00Z

Title: Bioprinting of in vitro models for personalized therapeutic delivery Authors: Chen, H; Radmanesh, S; Zhang, B; Wang, H; Cheng, R; Liang, C; Li, C; Tao Ye, T; Huang, J Abstract: Personalized therapeutic delivery aims to match the type, dose, timing, and localisation of treatment to each patient's unique biological profile, requiring platforms that can model individual responses and precisely control how therapeutics are released. Achieving this precision is challenging because conventional 2D cultures and animal models fail to reproduce the 3D architecture and microenvironmental cues that shape drug, gene, and growth-factor dynamics in human tissues. Bioprinted in vitro models address these limitations by enabling the spatially defined assembly of cells, hydrogels, and bioactive components into physiologically relevant constructs. This review examines how bioprinting is advancing personalized therapeutic delivery, focusing on how bioink chemistry, construct architecture, and matrix mechanics influence transport behavior, release kinetics, and overall therapeutic performance. We highlight bioprinted liver, cardiac, and tumor models as predictive testbeds for evaluating patient-specific responses, and discuss advanced delivery strategies, including in situ bioprinting and 4D adaptive systems. Together, these developments position bioprinted in vitro platforms as integrated tools for designing, testing, and optimizing personalized therapeutic interventions within the broader framework of personalized medicine. Description: Availability of data: Not applicable.

2026-04-02T00:00:00Z Olabi, V Alhajeri, A Ghazal, H Jouhara, H http://bura.brunel.ac.uk/handle/2438/33117 2026-04-09T02:00:55Z 2026-04-07T00:00:00Z

Title: Dynamic multi-objective, multi-period optimisation of a hydrogen supply chain in the Gulf Cooperation Council (GCC) region: A Saudi Arabia case study Authors: Olabi, V; Alhajeri, A; Ghazal, H; Jouhara, H Abstract: Home to some of the highest solar radiation levels globally and a strategic export location, Saudi Arabia ranks among the top countries for green hydrogen potential. However, widescale deployment remains constrained by the challenge of designing a supply chain that can effectively balance trade-offs between economic, environmental, and safety/risk objectives. This study presents a multi-objective, multi-period optimisation model for the design of a green hydrogen supply chain (HSC) network in the Northwestern region of Saudi Arabia, considering various production technologies (electrolyser types), storage options, and transportation modes. A novel dynamic framework is developed to simultaneously optimise cost, carbon footprint, and safety/risk. Within this framework, a hybrid AHP–MILP approach is integrated to capture stakeholder preferences and their evolution over time through time-dependent weightings, enabling the relative importance of economic, environmental, and safety criteria to adapt across planning periods in line with changing stakeholder priorities. Four planning periods are considered in this study: establishment phase (T1); early operations phase (T2); steady operations phase (T3) and mature system (T4) - with low, medium, and high demand scenarios analysed in each period. Results showed that as hydrogen demand increases, production technologies converge in performance because their individual strengths and weaknesses counterbalance each other, while storage and transportation technologies diverge as scale amplifies the advantages of various criteria. Description: Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S036031992601476X#appsec1 .

2026-04-07T00:00:00Z Mathew, A Shapiro, S Wang, X Zhao, H http://bura.brunel.ac.uk/handle/2438/33113 2026-04-09T02:00:56Z 2025-10-19T00:00:00Z

Title: Dual-Fuel Ammonia Engines to Decarbonise Freight Operations Authors: Mathew, A; Shapiro, S; Wang, X; Zhao, H Abstract: Operators of diesel-powered locomotives face increasing pressure to reduce carbon and exhaust emissions from their operations and transition away from using fossil fuels. Compression ignition diesel engines remain the prime movers of choice for self-powered rolling stock due to their high torque and efficiency. However, the long service life of locomotives, often exceeding 70 years, limits rapid fleet replacement. This study presents a concept for a dual-fuel diesel-ammonia internal combustion engine for locomotives, as part of ongoing research at Brunel University of London. Using data from UK Class 37 locomotives supplied by their owners and operators, representative engine duty cycles were derived from On-Train Monitoring and Recording (OTMR) data for a number of operational routes. Engine data, obtained through load bank testing of a locomotive, was then mapped onto these operational route based engine duty cycles to calculate diesel fuel use and exhaust emissions for each route. Literature based ammonia:diesel fuel ratios, validated through engine testing at Brunel University of London, were then applied to generate a comparative dual-fuel dataset. Preliminary results suggest diesel consumption - and thus carbon emissions - can be reduced by 18–29%. A CAD model was developed to demonstrate integration of ammonia fuel tanks alongside one of the two original diesel fuel tanks. Ongoing work involves using Brunel University of London’s single-cylinder test engine, upgraded for ammonia fueling, to increase ammonia:diesel ratios and assess emissions impacts. The results support the potential of retrofitting existing diesel locomotives with dual-fuel capability as a transitional pathway to lower carbon rail transport.

2025-10-19T00:00:00Z