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Pumps in drinking water distribution networks can be controlled to participate in demand response programs. In this paper, we estimate the demand response potential of water distribution networks based on actual network data. We calculate the power and energy capacities of community water systems within Wisconsin and Arizona, drawing on publicly available data of consumer water demand, population served, storage tanks, and pump specifications. We then extrapolate this data to get an order-of-magnitude estimate for the entire United States. Overall, we found that water distribution networks are sizable demand response assets with an estimated power capacity of 13 GW and energy capacity of 750 GWh in the United States. We also found that large and very large utilities may be the best demand response candidates. This paper also discusses factors impacting water supply flexibility and future research directions.
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STOCHASTIC OPTIMIZATION FOR FEASIBILITY DETERMINATION: AN APPLICATION TO WATER PUMP OPERATION IN WATER DISTRIBUTION NETWORK
Water Distribution Networks are a particularly critical infrastructure for the high energy costs and frequent failures. Variable Speed Pumps have been introduced to improve the regulation of water pumps, a key for the overall infrastructure performance. This paper addresses the problem of analyzing the effect of the VSPs regulation on the pressure distribution of a WDN, which is highly correlated to leakages and energy costs. Due to the fact that water network behavior can only be simulated, we formulate the problem as a black box feasibility determination, which we solve with a novel stochastic partitioning algorithm, the Feasibility Set Approximation Probabilistic Branch and Bound, that extends the algorithm previously proposed by two of the authors. We use, as black box, EPANet, a widely adopted hydraulic simulator. The preliminary results, over theoretical functions as well as a water distribution network benchmark case, show the viability and advantages of the proposed approach.
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- Award ID(s):
- 1632793
- PAR ID:
- 10108685
- Date Published:
- Journal Name:
- Proceedings of the 2018 Winter Simulation Conference
- Page Range / eLocation ID:
- 1945 to 1956
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1109/WSC.2018.8632513
