Geometric Programming-Based Control for Nonlinear, DAE-Constrained Water Distribution Networks

TL;DR

This paper introduces a novel geometric programming-based control method for water distribution networks that handles nonlinear DAE models without simplifying assumptions on network topology or flow direction.

Contribution

It presents a new control approach that directly solves nonlinear DAE models of water networks using convex optimization, removing the need for topology modifications or flow direction assumptions.

Findings

Successfully applied to a case study demonstrating effectiveness.

Handles nonlinear water flow equations without simplifying network assumptions.

Provides a convex optimization framework for control of complex water networks.

Abstract

Control of water distribution networks (WDNs) can be represented by an optimization problem with hydraulic models describing the nonlinear relationship between head loss, water flow, and demand. The problem is difficult to solve due to the non-convexity in the equations governing water flow. Previous methods used to obtain WDN controls (i.e., operational schedules for pumps and valves) have adopted simplified hydraulic models. One common assumption found in the literature is the modification of WDN topology to exclude loops and assume a known water flow direction. In this paper, we present a new geometric programming-based model predictive control approach, designed to solve the water flow equations and obtain WDN controls. The paper considers the nonlinear difference algebraic equation (DAE) form of the WDN dynamics, and the GP approach amounts to solving a series of convex optimization problems and requires neither the knowledge of water flow direction nor does it restrict the water network topology. A case study is presented to illustrate the performance of the proposed method.