Optimisation of Small Hydropower Units in Water Distribution Systems by Demand Forecasting

被引:0
|
作者
Oberascher, Martin [1 ]
Schartner, Lukas [2 ]
Sitzenfrei, Robert [1 ]
机构
[1] Univ Innsbruck, Fac Engn Sci, Dept Infrastructure Engn, Unit Environm Engn, Technikerstr 13, A-6020 Innsbruck, Austria
[2] Kirchebner Ziviltechniker GmbH, Grabenweg 3a, A-6020 Innsbruck, Austria
关键词
control; optimisation; renewable electrical energy; water distribution network; water-energy nexus; water surplus; ENERGY RECOVERY; DESIGN; SIMULATION; NEXUS;
D O I
10.3390/w15223998
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The potential of water supply systems for renewable electrical energy production is frequently utilised by a small-scale hydropower unit (SHPU) that utilises the surplus water or pressure. However, fluctuating demand on an hourly and daily basis represents a significant challenge in operating such devices. To address this issue, a control strategy based on demand forecast is implemented, adjusting the SHPU's inflow based on current demand conditions. Thus, individual days are categorised into control categories with similar flow conditions, and control is optimised for each category using a simplified evolutionary optimisation technique. Coupled with demand forecasts, the SHPU controller evaluates on a daily basis which set of water levels to utilise for the next day to optimise energy production. This approach is implemented in an alpine municipality, and its economic feasibility is evaluated through a long-term simulation over 10 years. This approach resulted in an annual profit increase compared to the reference status based on well-informed expert knowledge. However, it is worth noting that the approach has limited suitability for further improvements within the case study. Nonetheless, SHPUs also contribute to improving water quality and, if the electrical energy generated is directly used to operate the water supply, enhance resilience to grid failures.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Chlorine demand of biofilms in water distribution systems
    Lu, W
    Kiéné, L
    Lévi, Y
    WATER RESEARCH, 1999, 33 (03) : 827 - 835
  • [22] Electricity demand forecasting of single residential units
    Rossi, Maurizio
    Brunelli, Davide
    2013 IEEE WORKSHOP ON ENVIRONMENTAL, ENERGY AND STRUCTURAL MONITORING SYSTEMS (EESMS 2013), 2013, : 1 - 6
  • [23] Joint optimisation of demand forecasting and stock control parameters
    Tratar, Liljana Ferbar
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2010, 127 (01) : 173 - 179
  • [24] Water Demand Forecasting using Deep Learning in IoT Enabled Water Distribution Network
    Narayanan, L. K.
    Sankaranarayanan, S.
    Rodrigues, J. J. P. C.
    Kozlov, S.
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2020, 15 (06) : 1 - 15
  • [25] Multi-objective Optimisation of Distributed Generation Units in Unbalanced Distribution Systems
    Ramsami, Pamela
    King, Robert T. F. Ah
    SMART AND SUSTAINABLE ENGINEERING FOR NEXT GENERATION APPLICATIONS, 2019, 561 : 70 - 81
  • [26] RESIDENTIAL WATER DEMAND FORECASTING
    WHITFORD, PW
    WATER RESOURCES RESEARCH, 1972, 8 (04) : 829 - &
  • [27] THE EVOLUTION OF WATER DEMAND FORECASTING
    DEKAY, CF
    JOURNAL AMERICAN WATER WORKS ASSOCIATION, 1985, 77 (10): : 54 - 61
  • [28] WATER-DEMAND FORECASTING
    ARCHIBALD, GA
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 1987, 38 (12) : 1171 - 1171
  • [29] The Regional Small Hydropower Generated Energy Forecasting Method
    Han, Shuai
    Qin, Lijuan
    Lin, XiQiao
    Yan, Xu
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ENGINEERING AND ADVANCED TECHNOLOGY, 2016, 82 : 354 - 359
  • [30] Multiobjective Memetic Algorithm Applied to the Optimisation of Water Distribution Systems
    Euan Barlow
    Tiku T. Tanyimboh
    Water Resources Management, 2014, 28 : 2229 - 2242