Journal
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 11, Issue 4, Pages 2698-2712Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2020.2971259
Keywords
Water heating; Heat pumps; Water resources; Resistance heating; Cogeneration; Uncertainty; Power systems; Integrated energy system; multi-energy flow; robust optimization; water-energy nexus; water distribution system (WDS)
Categories
Funding
- National Natural Science Foundation of China [51725702, 51627811, 51807059]
- 111 project [B08013]
- Fundamental Research Funds for the Central Universities [2018MS002]
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Due to the continuous development of renewable energy as well as the emerging high-efficiency energy conversion techniques, the interdependencies among the heterogenous energy systems, such as power, natural gas, and district heating, are strengthening, which gradually forms the concept of integrated energy systems (IESs) and has drawn much attention from academia and industry. However, few research efforts have been spent on analyzing the interdependencies between IESs and the water distribution system (WDS), especially in the operation time scale, though water is one of the most necessary materials during energy production and conversion. In this article, a robust operation model for the water-energy nexus against the uncertainties of wind generation outputs is proposed to explore the interdependency between the IES and the WDS. The overall model is a two-stage program with a nonlinear program (NLP) in each decision stages, owing to the ubiquitous pressure-flow equations as well as the on/off switching of device operation status. Further, a two-step solution procedure is devised to obtain a solution with good quality, including the mixed integer second-order program based approximation for the original NLPs and the convex optimization based feasibility recovery, which is further embedded into the traditional column-and-constraint generation algorithm to generate a robust solution. Simulation results validate the necessity and the effectiveness of the proposed model and methods.
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