In the sun-scorched city of Zabol, in southeastern Iran, a team of engineers has demonstrated that the same renewable energy system designed to keep the lights on in a residential tower can also quench its thirst — and that doing so actually makes the whole setup cheaper. A new study published in Results in Engineering presents a fully integrated off-grid system combining photovoltaic panels, wind turbines, battery storage, and reverse osmosis desalination, optimized through a water-energy-economy-environment nexus approach. The counterintuitive headline finding: adding a desalination plant to a standalone renewable power system lowered the levelized cost of electricity from 0.1187 to 0.1043 dollars per kilowatt-hour, because the desalination unit converts surplus summer energy that would otherwise be wasted into a valuable product — freshwater.
The research addresses one of the most pressing coupled challenges of our era: the simultaneous scarcity of freshwater and electricity in arid and semi-arid regions such as the Middle East, North Africa, and parts of South Asia. Rapid population growth, limited natural water resources, and rising energy demand have intensified the need for solutions that tackle both supplies at once. While solar and wind power have become increasingly affordable, each technology on its own suffers from intermittency — photovoltaic generation vanishes after sunset and dips under cloud cover, while wind output depends on fluctuating wind speeds. The study exploits the complementary behavior of the two resources: winds in Zabol often blow strongest at night and during the region’s famous 120-day wind season, precisely when solar panels produce nothing. What is a liability for a single technology becomes a synergy advantage for a hybrid configuration.
The case study is a 23-story residential building with 161 apartments housing 408 residents, whose electricity demand was simulated hour by hour across a full year — 8,760 hours — using meteorological data for Zabol, including solar irradiance, ambient temperature, and wind speed profiles. Summer dry-bulb temperatures in the city reach 43.1 degrees Celsius, driving heavy cooling loads, while its proximity to the Oman Sea makes seawater desalination a plausible water source. Two system configurations were compared. Scenario A consists of photovoltaic panels, a wind turbine, and battery storage supplying only the building’s electrical load. Scenario B extends this by integrating a reverse osmosis desalination unit that converts excess renewable generation into freshwater for the occupants.
The technical modeling is notably detailed. The photovoltaic unit was simulated with a five-layer thermal model — glass, two ethylene vinyl acetate layers, silicon, and a backsheet — solving coupled energy balance equations to capture how cell temperature degrades power output. Each 580-watt panel operates at a reference efficiency of 22.47 percent with a temperature coefficient of 0.3 percent per degree Celsius, a critical consideration in a city where summer heat is punishing. Wind turbine output was calculated from hub-height wind speeds adjusted from reference measurements, with cut-in, rated, and cut-out velocities of 3, 12, and 25 meters per second respectively. The battery model accounts for self-discharge, an 85 percent charging efficiency, and a 91.55 percent inverter efficiency, while the reverse osmosis model tracks feed-water pumping power, concentrate disposal energy, and the recovery ratio that determines how much freshwater each cubic meter of seawater yields.
Optimization was performed with the Non-dominated Sorting Genetic Algorithm II, or NSGA-II, a widely used evolutionary algorithm that generates a diverse set of Pareto-optimal solutions when objectives conflict. Here, three objectives were minimized simultaneously: the levelized cost of electricity, the levelized cost of water, and the carbon footprint, expressed in kilograms of carbon dioxide equivalent using life-cycle emission factors for each component. Notably, battery storage dominates the environmental accounting at 64.30 kilograms of CO2-equivalent per kilowatt-hour of capacity, dwarfing the 0.08 for photovoltaics and 0.01 for wind. The algorithm ran with a population of 200 over 500 generations, and decision variables included the number of photovoltaic modules, wind turbines, battery capacity, and reverse osmosis capacity, subject to the strict constraint that both electricity and freshwater demand be fully satisfied at all times.
What distinguishes this study from prior work is its decision-making layer. Rather than assuming fixed priorities, the researchers applied the Technique for Order of Preference by Similarity to Ideal Solution — TOPSIS — under multiple weighting schemes reflecting different stakeholder preferences. For the electricity-only system, three weighting cases traded off cost against carbon; for the integrated system, four cases distributed priorities among electricity cost, water cost, and environmental impact. The results show that these weights directly reshape the optimal configuration: prioritizing cost objectives drives larger photovoltaic arrays and lower levelized costs, while environmental prioritization steers the solution toward smaller carbon footprints. Battery capacities across the optimized cases ranged from roughly 3,200 to 3,630 kilowatt-hours, and reverse osmosis capacities from about 203 to 231 cubic meters.
The generation profiles reveal why the hybrid design works so well in this location. On a representative July day, wind generation held near maximum throughout all 24 hours, delivering 144 kilowatt-hours in the electricity-only scenario. Photovoltaic output, by contrast, follows a predictable bell-shaped curve, peaking around solar noon — on a representative February day it reached 640 kilowatt-hours at 13:00, aided by strong irradiance and cooler temperatures. Combined daily production peaked at 8,053 kilowatt-hours in the integrated scenario during the mid-year months, when maximum solar irradiance constructively overlaps with the 120-day winds, and fell to roughly 1,540 to 1,674 kilowatt-hours at the year’s edges. Monthly totals in the integrated scenario climbed as high as 233,955 kilowatt-hours in August against a peak demand of 116,214 kilowatt-hours in July.
The battery management strategy is deliberately conservative. Stored energy builds during daylight hours and discharges overnight, but the energy management system restricts depth of discharge to no more than 20 percent, protecting battery health and extending service life — a meaningful consideration given that storage is both the most carbon-intensive and one of the costlier components at 200 dollars per kilowatt-hour. During a May morning in the electricity-only scenario, stored energy fell to 1,338 kilowatt-hours after a windless, sunless stretch, while on a September day in the integrated scenario the battery sustained a steady 3,390-kilowatt-hour plateau from 10:00 to 17:00, buoyed by late-summer irradiance and consistent wind inflow.
The economics tell the most compelling story. Because the system must be sized to reliably cover the lean winter period, summer generation in the electricity-only scenario vastly outstrips demand, leaving substantial surplus energy unutilized. Integrating reverse osmosis absorbs much of that summer spike, converting potential curtailment into freshwater and improving overall system utilization — which is why the integrated scenario achieves a lower levelized cost of electricity despite requiring more total renewable capacity, with a larger photovoltaic array but a smaller wind turbine fleet. Water costs respond strongly to weighting choices, with the lowest levelized costs of water appearing when that objective is prioritized in the decision matrix. The carbon footprint, meanwhile, rises in the integrated scenario because the desalination plant adds embodied and operational emissions, but environmental weighting demonstrably pushes the optimizer toward lower-emission designs.
The authors acknowledge limitations: the model assumes ideal component availability, neglects degradation of batteries, panels, and reverse osmosis membranes, and reflects a single location and building type. Future work includes degradation modeling, Monte Carlo uncertainty analysis for weather and prices, validation across other climates and building types, and exploration of hydrogen or biomass options for added flexibility. Still, the framework itself is deliberately generic — the mathematical models and optimization structure are site-independent and transferable to any water-stressed region by updating local resource and demand data. For the growing number of communities where the water tower and the power grid are one and the same problem, the message is striking: the surplus energy you would otherwise throw away may be exactly what your taps need.
Subject of Research: Multi-objective optimization of an off-grid hybrid renewable energy and reverse osmosis desalination system
Article Title: Multi-objective optimization of an off-grid photovoltaic-wind turbine-battery-reverse osmosis system using a water-energy-economy-environment nexus approach
Article References: Morasa, M. K., Shahverdian, M. H., & Sayyaadi, H. (2026). Multi-objective optimization of an off-grid photovoltaic-wind turbine-battery-reverse osmosis system using a water-energy-economy-environment nexus approach. Results in Engineering, 32, Article 113243. https://doi.org/10.1016/j.rineng.2026.113243
Image Credits: AI Generated
DOI: 10.1016/j.rineng.2026.113243
Keywords: photovoltaics, wind turbine, battery storage, reverse osmosis, desalination, NSGA-II, TOPSIS, levelized cost of electricity, water-energy nexus, carbon footprint, off-grid power, Zabol Iran