4.7 Article

Coordinated Planning Strategy for Integrated Energy Systems in a District Energy Sector

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 11, Issue 3, Pages 1807-1819

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2019.2941418

Keywords

Planning; Cogeneration; Resistance heating; Heat pipes; Natural gas; Boilers; Coordinated planning; district energy sector; integrated energy systems; improved generalized Benders decomposition; optimal multi-energy flows

Funding

  1. Natural Sciences and Engineering Research Council (NSERC) of Canada
  2. Saskatchewan Power Corporation (SaskPower)
  3. National Key Research and Development Program of China (Basic Research Class) [2017YFB0903000]
  4. National Natural Science Foundation of China [U1509218]
  5. USA Department of Energy (DOE) [DE-AC36-08GO28308]

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With the ever-growing integration of diverse distributed energy resources, modern district energy sectors are transitioning into integrated energy systems (IESs), which generally consist of various energy carriers such as electric power, natural gas, and heat. Instead of modeling individual energy carriers, the emergence of IESs requires comprehensive consideration of all involved energy systems in both planning and operation phases. This paper proposes a comprehensive planning strategy for a district energy sector to address the challenges of IES planning considering the coupling of power, gas, and heat systems. The proposed planning model contains an operational module that develops a steady-state optimal multi-energy flow (OMEF) for the IES considered and a multi-stage expansion module that optimizes the investment decisions. To efficiently solve the proposed planning model, which is formulated as a mixed-integer nonlinear programming problem, an improved generalized Benders decomposition algorithm that utilizes dynamic dual multipliers to improve the convergence speed is employed. The effectiveness of the proposed planning model and the feasibility of the improved Benders decomposition algorithm are verified in case studies.

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