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Joint operation of power, water, and heating networks is expected to improve overall efficiency of infrastructure while also known as a challenging problem, due to complex couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power-water-heat flow (OPWHF) problem and develop a computationally efficient and privacy preserving heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are solved via convex relaxation and convex-concave procedure while iteratively exchanging information to reach consensus on coupling variables. Simulation results validate that the joint optimization can improve operational flexibility and social welfare of the interconnected system, wherein the water and heating networks respond to time-varying electricity price and electric load as virtual energy storage. We also compare two modes of heating network control: by flow rate and by temperature; case studies reveal that the latter is more effective for most practical systems.
Repurposing automotive batteries to second-use battery energy storage systems (2-BESS) may have environmental and economic benefits. The challenge with second-use batteries is the uncertainty and diversity of the expected packs in terms of their chem
The existence of multiple solutions to AC optimal power flow (ACOPF) problems has been noted for decades. Existing solvers are generally successful in finding local solutions, which satisfy first and second order optimality conditions, but may not be
We consider the problem of stability analysis for distribution grids with droop-controlled inverters and dynamic distribution power lines. The inverters are modeled as voltage sources with controllable frequency and amplitude. This problem is very ch
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In chance-constrained OPF models, joint chance constraints (JCCs) offer a stronger guarantee on security compared to single chance constraints (SCCs). Using Booles inequality or its improv