<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research-Papers on FLEXsys</title><link>https://flexsys.fesb.unist.hr/hr/publications/categories/research-papers/</link><description>Recent content in Research-Papers on FLEXsys</description><generator>Hugo</generator><language>hr</language><lastBuildDate>Sun, 10 May 2026 14:23:39 +0000</lastBuildDate><atom:link href="https://flexsys.fesb.unist.hr/hr/publications/categories/research-papers/index.xml" rel="self" type="application/rss+xml"/><item><title>Day-Ahead Electricity Price Forecasting Using Gradient Boosting Models Decision Tree Models - A Case Study of the Croatian Market</title><link>https://flexsys.fesb.unist.hr/hr/publications/day-ahead-electricity-price-forecasting-using-gradient-boosting-models-decision-tree-models-a-case-study-of-the-croatian-market/</link><pubDate>Sun, 10 May 2026 14:23:39 +0000</pubDate><guid>https://flexsys.fesb.unist.hr/hr/publications/day-ahead-electricity-price-forecasting-using-gradient-boosting-models-decision-tree-models-a-case-study-of-the-croatian-market/</guid><description>&lt;p&gt;Accurate day-ahead electricity price forecasting is essential for market participants to optimize bidding strategies and manage financial risks in increasingly volatile energy markets. This paper presents a comprehensive web-based system designed for day-ahead electricity price forecasting based on gradient boosting models, specifically applied to the Croatian market. The proposed approach integrates a multi-layered architecture that includes data ingestion from ENTSO-E and Open-Meteo, a robust backend for model selection, training and management, with an interactive frontend presentation layer. The performance of two state-of-the-art gradient boosting algorithms, XGBoost and LightGBM was evaluated using hourly DA market price data from 2022 to 2024 from Croatian electricity market. The results demonstrate that both models achieve similar accuracy for the year 2024. Monthly analysis reveals significant performance variations, with higher errors during periods of extreme volatility and price spikes, such as summer and late winter. The study highlights the importance of meteorological features and market fundamentals in capturing price dynamics.&lt;/p&gt;</description></item><item><title>Participation of Battery Energy Storage in European Electricity Markets: Day-Ahead to Balancing</title><link>https://flexsys.fesb.unist.hr/hr/publications/participation-of-battery-energy-storage-in-european-electricity-markets-day-ahead-to-balancing/</link><pubDate>Sun, 10 May 2026 14:23:39 +0000</pubDate><guid>https://flexsys.fesb.unist.hr/hr/publications/participation-of-battery-energy-storage-in-european-electricity-markets-day-ahead-to-balancing/</guid><description>&lt;p&gt;Battery energy storage systems (BESS) can provide fast, bidirectional flexibility and participate across multiple market layers. This paper develops and compares two optimization models for joint day-ahead energy and reserve market participation. The strict model requires the BESS to always be able to deliver the full reserve it offers, while the intraday-correction model allows reserve activation to be corrected on the intraday market. Using realistic day-ahead prices and representative reserve payments, we quantify how intraday correction changes optimal reserve offers, state-of-charge trajectories, and revenue composition. Results show that allowing intraday correction relaxes the effective energy constraint, increases feasible reserve provision in specific hours, and improves overall profitability.&lt;/p&gt;</description></item><item><title>Single-Site–Driven Synthesis of High-Frequency PV Power for Dispersed Portfolios</title><link>https://flexsys.fesb.unist.hr/hr/publications/single-sitedriven-synthesis-of-high-frequency-pv-power-for-dispersed-portfolios/</link><pubDate>Sun, 10 May 2026 14:23:39 +0000</pubDate><guid>https://flexsys.fesb.unist.hr/hr/publications/single-sitedriven-synthesis-of-high-frequency-pv-power-for-dispersed-portfolios/</guid><description>&lt;p&gt;Minute-level photovoltaic (PV) power output time series are increasingly required for power-system operation studies such as regulation, ramping, and reserve sizing. Yet high-frequency irradiance (or PV) measurements are typically available at only
a small number of locations, while the operational need is to represent PV variability over a dispersed flet or a balancing area. This paper presents a single-site–driven framework that converts one high-frequency irradiance record into realistic PV power traces for dispersed PV portfolios by combining (i) a physically
motivated PV power conversion model and (ii) an aggregation filter that reproduces the reduction of short-term variability with geographic diversity&lt;/p&gt;</description></item><item><title>Techno-Economic Analysis of PV Prosumer Profiability Under Croatia’s Evolving Net Billing Scheme</title><link>https://flexsys.fesb.unist.hr/hr/publications/techno-economic-analysis-of-pv-prosumer-profiability-under-croatias-evolving-net-billing-scheme/</link><pubDate>Sun, 10 May 2026 14:23:39 +0000</pubDate><guid>https://flexsys.fesb.unist.hr/hr/publications/techno-economic-analysis-of-pv-prosumer-profiability-under-croatias-evolving-net-billing-scheme/</guid><description>&lt;p&gt;This paper presents a comprehensive techno-economic calculator for evaluating residential photovoltaic (PV) system profitability in Croatia under two distinct regulatory frameworks: the legacy monthly net-metering scheme and the new 15-minute interval net-billing scheme mandated by the 2025 amendments to the Act on Renewable Energy Sources and High-Efficiency Cogeneration. The transition from monthly aggregation to sub-hourly settlement fundamentally alters the economic value of self-generated solar energy by requiring near instantaneous matching of generation and consumption. Using high-resolution time-series modeling coupled with standard financial metrics —Net Present Value (NPV) and payback period— we quantify the profitability impact across realistic residential load profiles and Croatian-specific tariff structures. Results demonstrate that 15-minute settlement reduces NPV and extends payback periods compared to monthly net-metering, with the magnitude depending on self-consumption ratios, system sizing, and tariff parameters. For a representative 4.5 kW residential installation, the payback period increases from approximately 6 years under monthly net-metering to 12 years under 15-minute net-billing. The calculator provides transparent, reproducible decision support for Croatian prosumers navigating this regulatory transition and contributes methodological insights applicable to similar policy shifts across European Union member states.&lt;/p&gt;</description></item><item><title>Techno-Economic Optimization of PV-Wind-Battery Microgrids for EV Charging Under Price Volatility</title><link>https://flexsys.fesb.unist.hr/hr/publications/techno-economic-optimization-of-pv-wind-battery-microgrids-for-ev-charging-under-price-volatility/</link><pubDate>Sun, 10 May 2026 14:23:39 +0000</pubDate><guid>https://flexsys.fesb.unist.hr/hr/publications/techno-economic-optimization-of-pv-wind-battery-microgrids-for-ev-charging-under-price-volatility/</guid><description>&lt;p&gt;Large-scale transport electrification requires economically viable EV charging infrastructure with limited impact on distribution networks, especially under electricity price volatility. This paper presents a techno-economic planning and operation model for a grid-connected EV-charging microgrid integrating photovoltaic and wind generation together with battery energy storage. The proposed techno-economic model is formulated as a linear program that co-optimizes component capacities and hourly dispatch over a multi-year horizon by minimizing the levelized cost of energy (LCOE) while considering technical constraints related to power balance and energy component operation limitations. The case study considers two scenarios related to EV charging power supply: base scenario and renewable-only EV charging scenario to quantify the trade-off between costs and sustainability.&lt;/p&gt;</description></item></channel></rss>