Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_NGET0114 | |
| Title | Industrial and Commercial Gas & Electric Scenario Modeling | |
| Status | Completed | |
| Energy Categories | Other Cross-Cutting Technologies or Research(Energy system analysis) 80%; Other Power and Storage Technologies(Electricity transmission and distribution) 10%; Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 10%; |
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| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100% | |
| UKERC Cross Cutting Characterisation | Systems Analysis related to energy R&D (Energy modelling) 100% | |
| Principal Investigator |
Project Contact No email address given National Grid Electricity Transmission |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 November 2013 | |
| End Date | 01 November 2014 | |
| Duration | 12 months | |
| Total Grant Value | £542,250 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid Electricity Transmission (99.999%) |
| Other Investigator | Project Contact , National Grid Gas Transmission (0.001%) |
|
| Web Site | http://www.smarternetworks.org/project/NIA_NGET0114 |
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| Objectives | The approach is designed to take the best available techniques for developing various scenarios, collating best available data and developing new information to account for various complex inter-related market trends (economy, technology, social drivers) to provide a depth of analysis that will significantly enhance demand scenarios for these sectors. Delivery of enhanced modelling capabilities. Similar models have been developed in house within National Grid and are proving highly beneficial for the residential sector. This proposal aims to enhance the process accuracy and confidence in subsequent downstream processes that influence National Grid’s gas and power demand scenarios. | |
| Abstract | National Grid have made continuing use of econometric methods to develop scenarios that support asset investment and maintenance processes. Such techniques assume that recent historical relationships between energy and economic growth remain a sound basis for future demand scenario development. As the energy market becomes increasingly subject to Government intervention policy such methods are becoming less reliable. National Grid now make use of "bottom up" modeling for the residential scenarios, matching consumer to energy trends. Developing similar models for the commercial and industrial sectors remains a challenge due to the highly complex and numerous sub-customer groups and limitations on public data available for scenario development. In addition, there is an increasing focus is being placed on the geographical breakdown of demand. This is driven by changing consumer behaviours and technology take up alongside the increased capacities of embedded generation causing a more varied picture of demand across the country. Enhancing our modelling capabilities and our understanding of the antecedents and consequences of demand both at a GB level and on a geographical basis would help us make more informed decisions regarding network investment. The provision of a better split of demand will also help in our stakeholder engagement, particularly; with our interactions with other networks (TO, DNO, GDNs) that aim to compare demand projections. ARUP and Oxford Economics have been identified through the procurement event. The proposal represents an innovative approach in combining the benefits of a robust macro-economic model to capture the future direction of demand from an economic perspective, with a bottom up technological model that captures the detailed potential of energy savings. The top down "enhanced" approach enables the evaluation of the key components of energy demand including a comprehensive view of industry outputs, prices, exports, imports, investment, and supply chain linkages that influence market scale relative to global competitiveness. The top down is linked to the bottom up model to explain the changes in demand due to energy efficiency or technology adaptation. Furthermore the models will be developed to interrogate, and then build up an aggregate demand projection from multiple (up to 30) industrial and commercial sub-sectors dependent upon varying energy drivers. The bottom up model will be supported with an up to date database of energy savings and technology measures enabling a review of demand changes from various policy developments or technology price / performance amendments. ARUP will make use of public data and leverage their own research in developing the models and databases. Furthermore ARUP will engage with industry experts through a series of workshops in order to augment the datasets for completeness. This engagement will include working with other internal and external projects to ensure compatibility (as appropriate) and prevent duplication. A separate module will be developed to split the annual demand into daily and half hourly profiles for heat, power and gas demand by sector. The module is integrated with the bottom up technology model and separate demand side management modules to provide a within day view of demand. The modules will break demand down by region enabling a geographical view that is key for our stakeholder engagement and network investment. The results of the project will be used to feed into other National Grid projects in order to define boundaries i.e. EDAM 2, and used in Future Energy Scenarios.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 31/08/18 | |
