Optimal Scheduling of Water Distribution Systems

TL;DR

This paper develops a mixed-integer second-order cone programming approach for optimally scheduling water distribution systems under variable electricity prices, incorporating hydraulic constraints and ensuring feasible, near-optimal solutions.

Contribution

It introduces a novel relaxation technique for the non-convex OWF problem, enabling efficient, feasible scheduling solutions with proven optimality properties.

Findings

Relaxation yields exact solutions in numerical tests.

Method handles real-world demands and prices effectively.

Solutions achieve arbitrarily small optimality gaps under certain conditions.

Abstract

With dynamic electricity pricing, the operation of water distribution systems (WDS) is expected to become more variable. The pumps moving water from reservoirs to tanks and consumers, can serve as energy storage alternatives if properly operated. Nevertheless, optimal WDS scheduling is challenged by the hydraulic law, according to which the pressure along a pipe drops proportionally to its squared water flow. The optimal water flow (OWF) task is formulated here as a mixed-integer non-convex problem incorporating flow and pressure constraints, critical for the operation of fixed-speed pumps, tanks, reservoirs, and pipes. The hydraulic constraints of the OWF problem are subsequently relaxed to second-order cone constraints. To restore feasibility of the original non-convex constraints, a penalty term is appended to the objective of the relaxed OWF. The modified problem can be solved as a mixed-integer second-order cone program, which is analytically shown to yield WDS-feasible minimizers under certain sufficient conditions. Under these conditions, by suitably weighting the penalty term, the minimizers of the relaxed problem can attain arbitrarily small optimality gaps, thus providing OWF solutions. Numerical tests using real-world demands and prices on benchmark WDS demonstrate the relaxation to be exact even for setups where the sufficient conditions are not met.