Optimal Photovoltaic Integration for Offsetting Temperature-Dependent Auxiliary Electricity Demand in an Air-Cooled Geothermal Power Plant

Air-cooled binary geothermal power plants experience increased auxiliary demand and reduced net output during hot operating periods.

By GülerEnergiesOct 9, 2026

Score████░░░░░░4.4

Key numbers

31.4% of the 19

VerdictWorth a reader's time today.

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Abstract

Air-cooled binary geothermal power plants experience increased auxiliary demand and reduced net output during hot operating periods. This study develops a grid-connected photovoltaic (PV) sizing framework for an operating approximately 25 MW plant in the Menderes Massif, Türkiye. A measured 8760 h plant-wide auxiliary-load series, calculated from the plant’s 2025 SCADA gross and net electrical-output records, was used directly as the demand input in MATLAB (R2026a) and HOMER Pro (version 3.18.4). NASA POWER provided hourly ambient-temperature and solar-irradiance data. MATLAB performed hourly dispatch, a 0–5 MW capacity sweep in 0.25 MW increments, lifecycle-cost analysis, and sensitivity analysis, while HOMER Pro provided an independent cross-platform comparison. Under the adopted 2025 scenario assumptions (PV CAPEX of $733/kW and an auxiliary-offset electricity value of $0.10/kWh), the minimum Net Present Cost (NPC) occurred at 4.50 MW. This configuration supplied 6199 MWh/year directly to the auxiliary loads, corresponding to 31.4% of the 19,764 MWh annual auxiliary demand. The selected 5 MW engineering design increased direct PV utilization to 6592 MWh/year and the renewable fraction to 33.4%, while avoiding approximately 3032 t CO2/year under the adopted displacement-accounting convention. Its NPC was $19.539 million, only approximately $27,000 (0.14%) higher than the 4.50 MW minimum-NPC configuration identified within the evaluated capacity grid, with a simple payback of approximately 7.36 years. Sensitivity analysis further showed that the economically preferred PV capacity is conditional on the auxiliary-electricity value, PV CAPEX, and discount rate rather than representing a universal optimum.

Onur Vahip Güler

The editor's rubric

Heuristic review

Dimension	Level	Weight	What that level means
Leverage	███░░ 3	16%	A method or resource many groups across the field will adopt within a year.
Magnitude	██░░░ 2	20%	Solid incremental gain on a meaningful problem.
Evidence	███░░ 3	20%	Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
Novelty	███░░ 3	10%	A genuinely new approach to an open problem.
Trajectory	███░░ 3	14%	A clear path to scale.
Stakes	███░░ 3	20%	Meaningful benefit to many people within a few years.

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: breadth (general-purpose, programmable); novelty (alternative to status quo, open problem); verification (independent replication); stakes (global scale, energy, climate).

How the score was computed

rank-2026-10-07

Score████░░░░░░4.4

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Merit: 5.6 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 4.7 / 10; Shrunk toward the desk prior by editor confidence (46%).
Attention: 0%; Citations, upvotes, points, mentions.
Freshness: 85%; Half-life decay since publication.

Citations0 (reference 15, via openalex, Oct 11, 2026, 07:29 UTC)

The record

Reviewed by heuristic-v6 on Oct 11, 2026, 07:29 UTC. Paper type: empirical.
Categories: Power Systems and Renewable Energy, Hybrid Renewable Energy Systems, Solar Thermal and Photovoltaic Systems, Energy Engineering and Power Technology, Energy
TOP, No.4 in the Climate & Energy edition of October 11, 2026.