PNNL

Abstract

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as water system is one most energy intensive networks, an interruption in which may quickly result in a national security concern. This paper proposes chance-constrained analytics for day-ahead operation optimization of the interconnected power and water systems. Joint probabilistic constraint (JPC) programming is applied to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the nonlinear hydraulic constrains in the water network is linearized using piece-wise linearization technique and the non-convexity is efficiently tackled with a Boolean solution methodology. The proposed chance constrained model with JPCs is reformulated to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. The suggested framework is applied to a 15-node water network jointly operated with the IEEE 57-bus test power system. The numerical results demonstrate the effectiveness of the proposed stochastic framework, resulting in significant cost reduction and energy saving when the operation of both systems are jointly optimized.