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Projects: Projects for Investigator
Reference Number NIA_NGN_242
Title Constraint Based Optimisation Solution: Network Reinforcement
Status Completed
Energy Categories Other Cross-Cutting Technologies or Research(Energy Models) 90%;
Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 10%;
Research Types Applied Research and Development 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 80%;
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 20%;
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Other Systems Analysis) 100%
Principal Investigator Project Contact
No email address given
Northern Gas Networks
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 March 2019
End Date 01 December 2019
Duration ENA months
Total Grant Value £329,733
Industrial Sectors Energy
Region Yorkshire & Humberside
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , Northern Gas Networks (100.000%)
  Industrial Collaborator Project Contact , Northern Gas Networks (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA_NGN_242
Objectives Going forward NGN would like to reduce the number of open cut replacements by making strategic reinforcement investments that will mitigate excessively low pressure for multiple replacement projects. These reinforcement investments will include some open cut replacement to allow larger diameter mains to be laid but also increasing the downstream pressure at district governors. Planning the optimal programme of network reinforcement investments for a given mains replacement programme will require a software solution combining hydraulic flow modelling capability with constraint-based optimisation. Constraints must include financial, physical and operational constraints for example, minimum pressure and maximum shrinkage. No current software solution available on the market meets these criteria without requiring significant manual intervention making them impractical for analysing multiple replacement scenarios and business as usual use.This project will develop a methodology and enabling tool to enable NGN to effectively plan the strategic network reinforcement investments required to deliver effectively the REPEX programme with maximum mains replacement by insertion. The methodology will build on the existing, partially manual, solution (Global Model) currently being used by Northern Gas Networks to develop and optimal programme of network reinforcements. The methodology and enabling tool developed through this NIA project will improve on the performance and usability of the Global model. The project will also deliver a technical and commercial feasibility study assessing how the tool could be developed and deployed as a business as usual solution.Technically the solution will require two key functionalities:A) Ability to model the hydraulic flow in the gas network to identify when and where low-pressure constraints are breached during the REPEX programme from now until 2032 without the requirement for manual intervention each time a constraint is identified.B) Intelligently select the optimal network reinforcement investments by using mathematical optimisation, based on a set of objective functions and constraints, to mitigate excessively low pressure and enable maximum mains replacement by insertion. Reinforcement options includes new pipes, open-cut replacement with larger diameter pipes and increasing District Governor outlet pressures. To improve upon current NGN capability (Global Model) the methodology and enabling tool will:A) fully automate and significantly speed up the end to end process, B) solve for all network constraints simultaneously (rather than one-by-one) and (B) leverage state of the art mathematical constraint-based optimisation and the scalability of cloud computing to evaluate much larger numbers and combinations of options than possible with a human decision maker.Hydraulic modelling approachOur approach will use a simple flow equation suitable for steady state analysis of natural gas flow in a distribution pipe. Plan to use Lacey/Pole or low pressure Spizglass formula (a Synergi Gas option) for pressures below 75 mbar. Focus will be to simplify hydraulic computation to its bare-bones to allow optimisation process to run efficiently but maintaining credible pressure predictions.Optimisation approachThis optimisation capability will be built using Constraint-Oriented Reasoning™ (COR). COR is a 5th generation programming language that enables the user to quickly create high-value analytical solutions in complexproblem domains. Unlike conventional modelling, COR automatically generates mathematical representations of all system constraints and their interactions. This avoids the need for specialised developers and allows users with asset and risk management to build models and apply their expertise directly. COR can be used to simultaneously model operational, physical and financial constraints, making it ideal for this application. COR will be required to model multiple constraints including but not limited to, minimum and maximum safe gas pressure, construction lead time and shrinkage/leakageCOR will make use of CPLEX to find the optimal (lowest cost) network reinforcement investments for a given mains replacement programme. To meet the planning challenge outlined about the proposed solution will:• Model the NGN low pressure distribution network at an individual pipe level.• Model the mains replacement projects, their costs and phasing.• Model the cumulative impact of the mains replacement projects on gas pressure to identify when and where “constraints” would develop.• Intelligently (using constraint-based optimisation) select the most cost-effective Capex investments to augment network capacity to mitigate the constraints.Allow the user to define the effective lead-time and planning constrains for reinforcement investments (for example 12 months before dependant replacement project).Take into consideration other types of constraint (other than low pressure) such as shrinkage/leakage and high pressure.Further, to ensure it is usable the solution will:• Have a rapid set-up and solve time to effectively support a dynamic and iterative planning process, for example re-solving for multiple C55 investment scenarios. We expect the solve time for a single scenario to be between 4 and 6 hours. If required multiple scenarios can be run in parallel with no additional time impact (assuming solution is hosted in the MS Azure cloud).Following the registration of the NIA project, NIA_NGN_242 Constraint Based Optimisation Solution: Network Reinforcement. The project has experienced timeline setbacks, resulting in the original delivery date being no longer attainable. To ensure the original project aims and objectives are met, it is necessary to extend the project timeline until the 15/11/2019. The objective is to develop and test a bespoke methodology, building on NGNs global model approach, and solution to optimise the network reinforcement investments required to minimise the use of open cute mains replacement. The project will deliver the following core objectives:• Quantified benefit case for optimised and automated network reinforcement planning process• Business case and plan to implement improved process as business as usual• Optimised network reinforcement programme (to 2032) using improved methodology
Abstract The objective is to develop and test a bespoke methodology, building on NGNs global model approach, and solution to optimise the network reinforcement investments required to minimise the use of open cute mains replacement.
Publications (none)
Final Report (none)
Added to Database 09/11/22