Distributionally Robust Co-Optimization of Energy and Reserve for Combined Distribution Networks of Power and District Heating

The combined operations of power distribution and district heating networks catalyze ongoing progressions to smart cities. This paper proposes a distributionally robust energy and reserve co-optimization approach for combined power distribution and district heating networks. In particular, smart buildings are modeled as equivalent storage devices representing cost-effective resources to enhance operational flexibility and provide additional reserves in power systems. Uncertainties pertaining to renewable energy resource power and ambient temperature are captured within an ambiguity set that comprises a variety of statistical characterizations (e.g., the expected value, the variance, and the covariance) to generate more trustworthy and less conservative solutions. Linear decision rules and the second-order cone duality are employed to enhance the computational tractability of the proposed approach by transforming the original problem into a second-order cone program. Finally, numerical results provided based on the real-world Barry Island system demonstrate the risk-reduction and economic benefits of the proposed approach.