Optimizing Photovoltaic Panel Quantity for Water Distribution Networks

TL;DR

This paper presents a novel iterative procedure to approximate the optimal number of photovoltaic panels for water distribution networks, reducing operational costs by 14.5% over 25 years through probabilistic modeling and derivative-free optimization.

Contribution

It introduces a new cost-minimization method combining probabilistic PV production modeling with Nelder-Mead optimization for WDNs.

Findings

Achieved a 14.5% cost reduction with PV integration.

Validated the procedure on the Randers water network.

Demonstrated effectiveness of derivative-free optimization in this context.

Abstract

The paper introduces a procedure for determining an approximation of the optimal amount of photovoltaics (PVs) for powering water distribution networks (WDNs) through grid-connected PVs. The procedure aims to find the PV amount minimizing the total expected cost of the WDN over the lifespan of the PVs. The approach follows an iterative process, starting with an initial estimate of the PV quantity, and then calculating the total cost of WDN operation. To calculate the total cost of the WDN, we sample PV power profiles that represent the future production based on a probabilistic PV production model. Simulations are conducted assuming these sampled PV profiles power the WDN, and pump flow rates are determined using a control method designed for PV-powered WDNs. Following the simulations, the overall WDN cost is calculated. Since we lack access to derivative information, we employ the derivative-free Nelder-Mead method for iteratively adjusting the PV quantity to find an approximation of the optimal value. The procedure is applied for the WDN of Randers, a Danish town. By determining an approximation of the optimal quantity of PVs, we observe a 14.5\% decrease in WDN costs compared to the scenario without PV installations, assuming a 25 year lifespan for the PV panels.