arXiv subjects

Sergio Saludes-Rodil

Publications and source records attributed to Sergio Saludes-Rodil.

5 recordsLinked to original sources

arXiv2025

A Comparative Analysis of Electricity Consumption Flexibility in Different Industrial Plant Configurations

The increasing integration of renewable energy sources into power systems is intensifying the demand for greater flexibility among industrial electricity consumers. However, operational constraints, production requirements, and market dynamics pose significant challenges to achieving optimal flexibility. This paper presents an enhanced mixed integer linear programming (MILP) model that directly optimizes electricity consumption flexibility in manufacturing plants. Unlike previous approaches, the proposed model determines optimal transactions with both day-ahead and intraday continuous electricity markets, while ensuring production continuity and adhering to plant-specific operational constraints. The methodology is validated through annual simulations of two real world industrial configurations, cement manufacturing and steel production, using 2023 market data. Comparative results highlight that the steel plant achieved average electricity cost savings through flexibility of 0.41 euro/MWh, whereas the cement plant achieved 0.24 euro/MWh, reflecting differences in storage capacities, production rates, and operational flexibility. A comprehensive sensitivity analysis further identifies key parameters affecting flexibility potential, such as the production to demand ratio, storage capacity, and minimum operation periods. The findings offer valuable insights for industrial operators aiming to reduce energy costs, enhance operational flexibility, and support the decarbonization of electricity systems.

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arXiv2025

A Robust Optimization Framework for Flexible Industrial Energy Scheduling: Application to a Cement Plant with Market Participation

This paper presents a scenario based robust optimization framework for short term energy scheduling in electricity intensive industrial plants, explicitly addressing uncertainty in planning decisions. The model is formulated as a two-stage Mixed Integer Linear Program (MILP) and integrates a hybrid scenario generation method capable of representing uncertain inputs such as electricity prices, renewable generation, and internal demand. A convex objective function combining expected and worst case operational costs allows for tunable risk aversion, enabling planners to balance economic performance and robustness. The resulting schedule ensures feasibility across all scenarios and supports coordinated use of industrial flexibility assets, including battery energy storage and shiftable production. To isolate the effects of market volatility, the framework is applied to a real world cement manufacturing case study considering only day-ahead electricity price uncertainty, with all other inputs treated deterministically. Results show improved resilience to forecast deviations, reduced cost variability, and more consistent operations. The proposed method offers a scalable and risk-aware approach for industrial flexibility planning under uncertainty.

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arXiv2025

Enhancing Industrial Flexibility and Market Participation in Cement Manufacturing Through Optimized Production Scheduling

The growing share of variable renewable energy (VRE) sources in power systems is increasing the need for short term operational flexibility, particularly from large industrial electricity consumers. This study proposes a practical, two stage optimization framework to unlock this flexibility in cement manufacturing and support participation in electricity balancing markets. In Stage 1, a mixed integer linear programming (MILP) model minimizes electricity procurement costs by optimally scheduling the raw milling subsystem. In Stage 2, a flexibility assessment model evaluates profitable deviations, targeting participation in Spain manual Frequency Restoration Reserve (mFRR) market. A real world case study in a Spanish cement plant (including PV and battery storage) shows that flexibility services can yield monthly revenues of up to 800 EUR and paybacks as short as six years. This framework offers a replicable pathway for industrial flexibility in energy intensive sectors.

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arXiv2024

Aggregated demand flexibility prediction of residential thermostatically controlled loads and participation in electricity balance markets

The aggregate demand flexibility of a set of thermostatically controlled residential loads (TCLs) can be represented by a virtual battery (VB) in order to manage their participation in the electricity markets. For this purpose, it is necessary to know in advance and with a high level of reliability the maximum power that can be supplied by the aggregation of TCLs. A probability function of the power that can be supplied by a VB is introduced. This probability function is used to predict the demand flexibility using a new experimental probabilistic method based on a combination of Monte Carlo simulation and extremum search by bisection algorithm (MC&ESB). As a result, the maximum flexibility power that a VB can provide with a certain guaranteed probability is obtained. The performance and validity of the proposed method are demonstrated in three different case studies where a VB bids its aggregate power in the Spanish electricity balancing markets (SEBM).

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arXiv2021

Flexibility management with virtual batteries of thermostatically controlled loads: real-time control system and potential in Spain

Load flexibility management is a promising approach to face the problem of balancing generation and demand in electrical grids. This problem is becoming increasingly difficult due to the variability of renewable energies. Thermostatically controlled loads can be aggregated and managed by a virtual battery, and they provide a cost-effective and efficient alternative to physical storage systems to mitigate the inherent variability of renewable energy sources. But virtual batteries require of an accurate control system being capable of tracking frequency regulation signals with minimal error. A real-time control system allowing virtual batteries to accurately track frequency or power signals is developed. The performance of this controller is validated for a virtual battery composed of 1,000 thermostatically controlled loads. Using virtual batteries equipped with the developed controller, a study focused on residential thermostatically controlled loads in Spain is performed. The results of the study quantify the potential of this technology in a country with different climate areas and provides insight about the feasibility of virtual batteries as enablers of electrical systems with high levels of penetration of renewable energy sources.

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