Modernisation | Looking to FutureDAMS


New pragmatic tools have been developed for rethinking how river basins and power grids interact to jointly create societal benefits


Right: Figure 1. Hydropower locations act as the link between the water and energy system simulation models that can run independently of each other, or jointly


Authors


Jose M. Gonzalez – Research Associate at the Department of Mechanical, Aerospace and Civil Engineering (MACE), The University of Manchester.


Jamie Skinner – Principal researcher, Natural Resources at International Institute for Environment and Development and FurtureDAMS Capacity Director.


Julien J. Harou – Chair in Water Engineering at the Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester and FutureDAMS Research Director


UK FINANCED RESEARCH PROGRAMMES are addressing the global challenges of international development. Recent break throughs in online computer-assisted simulation and design now allow us to assess in increasing detail the consequences of alternative energy infrastructure choices as the world pivots towards a low carbon future. Hydropower is thrust front and centre as a potentially low carbon generation technology in a world of changing river flows and increasing competition for water both between sectors and between countries. The International Energy Agency (IEA) has highlighted the potential future role of sustainable hydropower in meeting energy demands and estimated that global hydropower capacity is set to increase by 17%, or 230GW, between 2021 and 2030. This is equivalent to 1150 new dams assuming an average of 200MW each. More broadly, over 75% of new hydropower capacity worldwide through 2030 is expected to come in the form of large-scale projects in Asia and Africa commissioned by state-owned enterprises. In parallel, electricity grids are facing the challenge of delivering grid ancillary services and meeting peak demands, in grids increasingly dominated by intermittent renewables.


Complexity One word summarises the emerging context –


complexity. Hydropower developers have traditionally needed to analyse and take account of multiple water users within a river system. Now, they also need to take


Inflows Thermal plants


Intermittent renewables


Reservoir


Energy demand


Hydropower Hydropower demand Water


Energy demand


account of the precise needs of the electricity system. Any adjustments to dam design and/or operations have increasingly far-felt impacts on both systems, yet the technical modelling and simulation tools able to analyse the cross-sectoral implications and choices available have not been available until now.


New approaches and tools The FutureDAMs project (Future Design and Assessment


of water-energy-food-environment Mega Systems) led by the University of Manchester has successfully integrated energy and river basin modelling and simulation, working with partners on the Eastern Nile and in Ghana. This tool is online (www.waterstrategy.org) and intends


to help coalitions of planners from different sectors to work collaboratively to achieve positive and sustainable societal outcomes. The FutureDAMS approach and tools build on research and development undertaken in the last decade in collaboration with UK planners and water utilities, which will invest on the order of £50 billion to meet water supply needs up to 2050. Simulating complex multi-resource systems (water,


Right: Figure 2. Transboundary Volta River Basin and Ghana’s national power system. The map shows the locations of existing and planned storage dams, solar PV potential, distribution of the energy demand through the county, the existing electrical transmission network, irrigation and public water supply diversions and flood recession activities which were included in the integrated water-energy simulation model


24 | January 2022 | www.waterpowermagazine.com


energy, food, and environment) helps better understand such systems and improve their design, management, and operation. The simulation models can be linked to multi-objective artificial intelligence design algorithms that help identify the synergies and trade-offs between different objectives for the best performing portfolios of interventions. This shows how an incremental change made to improve one objective and its co-benefits may come at the cost of one or more other different goals. The resulting multi-criteria trade-off analysis assists stakeholders in managing river systems, infrastructure and energy services. These methods can also explore strategies under multiple future scenarios to identify robust solutions that work acceptably over a range of possible futures. Performance metrics within the model quantify the benefits generated by the built and natural infrastructure and allow producing strategic planning studies that, for example: ● Minimise capital costs. ● Minimise operating costs. ● Minimise load curtailment and C02


emissions. ● Minimise eco-hydrological modifications.


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