New Ranking Framework Reveals Where Solar Water Heaters Work Best in Türkiye

Solar domestic hot water systems have long been promoted as one of the simplest ways to cut fossil fuel use in homes, yet their real-world performance is anything but uniform. A rooftop collector in a sun-drenched southern province can deliver dramatically more useful heat than an identical unit installed in a cloudy coastal region, and that variability has made it difficult for policymakers to decide where public investment in solar heating will pay off most. A new study published in Clean Technologies and Environmental Policy tackles this problem head-on, offering a transparent, scenario-based method for ranking forty-five Turkish provinces according to the techno-environmental performance of a standardized solar hot water configuration.

The research, carried out by Sadrettin Çodur of Karadeniz Technical University and Musa Demir of Giresun University, builds on a growing body of work showing that solar water heating can meaningfully reduce residential carbon emissions in Türkiye. Rather than relying on a single metric such as annual solar radiation, the authors assembled five benefit criteria drawn from simulation of a standardized system: emission reduction, solar contribution, system efficiency, demand coverage, and solar-resource availability. This multi-dimensional picture matters because two provinces with similar sunshine levels can differ sharply in how much of a household’s hot water demand the system actually covers, depending on climate, consumption patterns, and technical conditions.

At the heart of the study is a multi-criteria decision-making, or MCDM, framework designed to convert a messy table of provincial indicators into a defensible priority list. The researchers evaluated one objective weighting scenario, in which criterion weights are derived mathematically from the data itself, alongside five policy-oriented scenarios that represent alternative planning priorities. In practice, this means the ranking can be stress-tested against different political realities: a government focused purely on carbon abatement, for example, would weight emission reduction more heavily, while one prioritizing energy security might emphasize demand coverage instead. By running all six weighting scenarios, the team could see which provinces remain at the top regardless of the policy lens applied.

To generate the rankings themselves, the study employed two compromise-based MCDM methods, drawing on approaches in the decision-science literature that seek solutions closest to an ideal point rather than a single dominant criterion. The first, the combined compromise solution method known as CoCoSo, aggregates weighted normalized performance through multiple aggregation steps to produce a compromise score for each province. The second, MARCOS, which stands for measurement of alternatives and ranking according to compromise solution, ranks alternatives by evaluating their distance from both ideal and anti-ideal reference points. Using two independent methods is a deliberate safeguard: if both converge on the same winners, the conclusion is far more robust than if it hinged on the quirks of one algorithm.

The headline finding is geographically striking. Provinces in Eastern and Southeastern Türkiye generally offer the highest solar domestic hot water potential, a result that may surprise readers who associate the country’s solar boom with its Mediterranean and Aegean coasts. The combination of strong solar availability, favorable climatic conditions for collector performance, and substantial heating demand gives these inland and eastern provinces an edge when all five criteria are considered together. By contrast, several Black Sea provinces tend to rank lower, a consequence of the region’s famously cloudy, rainy climate, which limits the solar resource that collectors can harvest over the course of a year.

Robustness testing forms the methodological backbone of the paper, and it is here that the study distinguishes itself from simpler ranking exercises. The authors compared the rankings produced by the two MCDM methods and found high Spearman correlations between them, indicating that the identification of priority provinces does not depend strongly on which ranking method is chosen under most scenarios. They also performed a winter-based seasonal analysis, recognizing that a solar hot water system’s value is tested most severely in the coldest months when demand peaks and solar input is weakest. A province that performs well annually but poorly in winter presents a very different policy proposition from one that maintains output year-round.

Two further stress tests round out the framework. A parameter-sensitivity analysis examined how the rankings respond to changes in underlying assumptions, probing whether small shifts in input values could reshuffle the priority list. Complementing this, criterion-ablation tests removed individual criteria one at a time to measure how much each one contributes to the overall ordering. Together, these procedures give decision-makers a quantified sense of confidence: provinces that stay near the top across weighting scenarios, both ranking methods, seasonal slices, and ablation cases can be treated as genuinely high-priority, while those whose positions swing wildly deserve closer scrutiny before funding decisions are made.

The practical implications extend well beyond Türkiye’s borders. Solar water heating remains one of the most cost-effective renewable heat technologies available, and global market analyses continue to track its growth, yet deployment policy is often designed at the national level with little regional differentiation. The framework demonstrated here offers a template for regionally differentiated renewable-heating planning: simulation-derived indicators feed into a transparent weighting and ranking process, whose outputs are validated through multiple robustness checks. Governments could use such rankings to target subsidy programs, prioritize demonstration projects, or sequence grid and gas infrastructure investments in areas where solar hot water delivers the least benefit.

The study also contributes to a broader methodological conversation in energy decision science. Previous work has applied fuzzy TOPSIS to rank renewable energy supply systems in Turkey, combined CRITIC and CoCoSo for hybrid solar-wind siting in Vietnam, and integrated multiple MCDM techniques for sustainable renewable energy selection in India. What the new framework adds is the systematic combination of scenario-based weighting, dual-method ranking, and layered robustness analysis applied at a fine provincial scale for a specific, deployable technology. The use of the MEREC objective weighting method, which determines weights based on the removal effects of criteria, further grounds the objective scenario in the structure of the data rather than in expert judgment alone.

For a country positioning itself within a net-zero pathway, the message is clear: the provinces where solar domestic hot water systems will deliver the greatest techno-environmental returns are not always the ones with the most visible solar markets. By making the weighting assumptions explicit and testing them from every angle, Çodur and Demir have produced a decision-support tool that is both rigorous and adaptable, one that other nations with strong regional climatic gradients could replicate with their own simulation data. As residential heating remains one of the stubborn sources of fossil fuel demand worldwide, frameworks that can tell policymakers precisely where each public lira, euro, or dollar of solar heating support will cut the most carbon are likely to become an increasingly valued part of the climate policy toolkit.

Subject of Research: Scenario-based multi-criteria decision-making assessment of solar domestic hot water system performance across Turkish provinces

Article Title: Scenario-based MCDM framework for performance assessment and provincial prioritization of solar domestic hot water systems

Article References: Çodur, S., & Demir, M. (2026). Scenario-based MCDM framework for performance assessment and provincial prioritization of solar domestic hot water systems. Clean Technologies and Environmental Policy, 28(10), Article 263. https://doi.org/10.1007/s10098-026-03621-6

Image Credits: AI Generated

DOI: 10.1007/s10098-026-03621-6

Keywords: solar water heating, multi-criteria decision-making, renewable energy, Türkiye, carbon emission reduction, CoCoSo, MARCOS, MEREC weighting, energy policy, provincial prioritization, solar thermal energy, robustness analysis