Stochastic Power-Water Coordination: Unlocking Flexibility in Hybrid RO Desalination Plants via Variable-Speed Pumps and Tank Mixing

TL;DR

This work develops a coordinated HDP-power system framework for RO-based desalination plants that fully exploits desalination flexibility via variable-speed pumps and tank salinity management. By building a detailed HDP model (HPP dynamics, RO process, storage Tank TDS mixing) and integrating it with a distribution grid, the authors recast the nonlinear problem into a tractable MILP through careful simplifications and a triangular-piecewise linearization, then address PV and price uncertainties with a two-step stochastic scheduling (TDCSO). The approach is validated against a full desalination model, showing up to 6% operating-cost reductions and practical runtimes, with significant gains from proactive tank TDS control and mixing. The results demonstrate that end-to-end water quality and supply can be maintained while reducing system costs, highlighting the value of coupling water-system flexibility with power-system operations in HDP contexts.

Abstract

Water desalination plants (DPs) are among the most critical infrastructures and largest electricity loads in water-scarce regions worldwide. Although reverse osmosis (RO) desalination is the most energy-efficient and dominant technology, it remains energy-intensive but can offer substantial flexibility potential for power systems. This paper proposes a coordinated operation framework for power systems and DPs that explicitly accounts for both systems' operational constraints and fully unlocks DP flexibility. To achieve this, a detailed DP model is developed, incorporating the characteristics of an actual high-pressure pump with variable-speed operation, on-off operation with flushing requirements, water quality constraints, and water dynamics and salt mixing in the storage tank. By proactively managing freshwater storage and tank salinity in a closed-loop coordinated scheduling framework, the operational flexibility of the DP is significantly enhanced. With appropriate simplification and linearization, the resulting coordinated scheduling problem is formulated as a tractable mixed-integer linear programming (MILP) model, and a two-step decomposed commitment-scheduling stochastic optimization (TDCSO) is proposed to efficiently address uncertainties. Case studies validate the proposed approach and demonstrate up to a 6% operating cost reduction.

Figures (10)

• Figure 1: Diagram of the HDP and the power distribution system.
• Figure 2: Characteristic curves of a VFD-enabled variable-speed HPP. Black triangles denote the original data at nominal speed in the product manual, and red circles indicate the operating points with maximum efficiency.
• Figure 3: Flushing requirement of an example RO-DP.
• Figure 4: Water demand (top), forecast of the co-located PV, the load of the distribution system except the HDP, and the buy price of energy (bottom).
• Figure 5: Calculation errors of the simplified model for permeate flow (top) and TDS (bottom), computed as (simplified -- full).