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May 14, 2021IEEE Transactions on Smart Grid152 citations

Risk-Averse Coordinated Operation of a Multi-Energy Microgrid Considering Voltage/Var Control and Thermal Flow: An Adaptive Stochastic Approach

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ZLZhengmao LiLWLei WuYXYan Xu

Key Points

  • To develop an adaptive risk-averse stochastic framework for multi-energy microgrids that coordinates active and reactive power dispatch alongside dynamic thermal flows and battery lifespan constraints.
  • Integrated a voltage/var control scheme, a dynamic thermal network model accounting for transmission delays, and a battery degradation model.
  • Incorporated conditional value-at-risk (CVaR) to evaluate uncertainty from renewable sources and reformulated the nonlinear system as a mixed-integer linear programming (MILP) model.
  • Evaluated performance using multi-energy microgrid numerical simulations under varying operating conditions.
  • Co-optimized active and reactive power flows while strictly maintaining voltage security limits across the microgrid.
  • Coordinated thermal energy distribution and battery storage usage to balance operating costs with equipment degradation.
  • Mitigated economic and operational risks arising from renewable generation intermittency through CVaR-constrained scheduling.

Abstract

With an increasing penetration level of intermittent renewable energy sources and heterogeneous energy demands, the secure and economic operation of multi-energy microgrids (MEMGs) becomes more and more critical. Under this circumstance, this paper proposes an adaptive (two-layer) stochastic approach to obtain optimal MEMG operation decisions by taking advantage of distinct energy properties. First, rather than merely focusing on the active power economic dispatch, voltage/var control (VVC) scheme is involved to co-optimize the active and reactive power flow while guaranteeing voltage security; Second, a battery degradation model and a comprehensive thermal network model with thermal energy flow and transmission delay are presented to derive practical and efficient operations; Third, a conditional value-at-risk (CVaR)-based risk evaluation method is included to avoid over-optimistic solutions. The original nonlinear operation problem is reformulated as a mixed-integer linear programming (MILP) model to achieve high solution quality with acceptable computation performance. Finally, case studies are conducted to indicate that our proposed approach can effectively coordinate the dispatch of active/reactive power as well as thermal flow, thus ensuring system security with minimal operating costs and risks.

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Cite This Study

Li et al. (2021) studied this question.

synapsesocial.com/papers/69db1c2b37b5141e3ba3cca4https://doi.org/10.1109/tsg.2021.3080312
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