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Publications

Publications by Filipe Joel Soares

2024

Extending AC Security Constrained Optimal Power Flow for Low Inertia Systems with Artificial Neural Network-based Frequency Stability Constraints

Authors
Alizadeh, MI; Capitanescu, F; Barbeiro, P; Gouveia, J; Moreira, L; Soares, F;

Publication
IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2024

Abstract
Frequency stability in inverter-based renewable energy sources (RES)-dominated, low-inertia, power systems is a timely challenge. This paper employs a systematic approach, utilizing an artificial neural network (ANN) and dynamic simulation, to infer two key frequency stability indicators: nadir and rate of change of frequency (RoCoF). By reformulating the ANN mathematical model, these indicators are then integrated as mixed-integer non-linear constraints into a classical AC security-constrained optimal power flow (AC SCOPF), resulting in the proposed AC-F-SCOPF problem. The results of the proposed AC-F-SCOPF on the IEEE 39-bus system show that the problem identifies accurately the synchronous condensers which must run to ensure the frequency stability. © 2024 IEEE.

2024

Optimal planning of a green hydrogen fueling station

Authors
Coelho, A; Soares, FJ; Iria, JP;

Publication
IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2024, Dubrovnik, Croatia, October 14-17, 2024

Abstract
As the global community transitions towards decarbonization and sustainable energy, green hydrogen is emerging as a key clean energy carrier. This paper addresses the role of hydrogen in transportation, emphasizing the European Union's additionality principle for renewable energy sources in green hydrogen production. It introduces a model for optimally designing hydrogen fueling stations, considering electrolyzers, hydrogen storage, fuel cells, PV systems, and batteries. This model also considers the participation in electricity (energy and secondary reserve), hydrogen, and oxygen markets, and it is evaluated under different additionality policy scenarios. Results indicate that stricter additionality policies reduce the internal rate of return. However, participation in secondary reserve markets significantly boosts operational revenues and compensates for higher investment costs. © 2024 IEEE.

2024

Effects of Temperature Variation on the Capacity of Gas Networks to Receive Injections of Green Hydrogen

Authors
Fontoura, J; Soares, FJ; Mourao, Z;

Publication
2024 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE, ISGT EUROPE

Abstract
The literature on the isothermal model gas flow is extensive, but the effect of temperature variation on the hydraulic characteristics has been rarely addressed. Additionally, the impact of hydrogen blending on the thermal condition of NG pipelines is also an emergent topic that requires new approaches to the gas flow problem formulation and resolution. In this paper, a model for the gas flow problem was developed to optimise the operation of natural gas distribution networks with hydrogen injection while maintaining pressure, gas flows, and gas quality indexes within admissible limits. The goal is to maximise the injection of hydrogen and investigate the influences of thermal variations in the gas blending. Also, this model enables the calculation of the maximum permitted volume of hydrogen in the network, quantifying the total savings in natural gas usage and carbon dioxide emissions in different temperature conditions.

2024

Operation of an industrial green amonnia fuel hub participating in secondary reserve markets

Authors
Coelho, A; Soares, F;

Publication
2024 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE, ISGT EUROPE

Abstract
Green ammonia production stands as a pivotal component in the transition towards sustainable energy and agriculture, poised to revolutionize numerous industries. This paper presents an optimization control framework for industrial green ammonia fuel hubs to engage in electricity, hydrogen, and oxygen markets, addressing both economic and technical considerations. By evaluating scenarios with and without battery storage, this study demonstrates the potential for increased profitability and energy independence through secondary reserve market participation, alongside insights into the economic viability of photovoltaic investments. These findings underscore the importance of considering market dynamics and technological integration in the sustainable operation of green ammonia production hubs.

2018

Building automation systems and smart meter integrated residential customer platform

Authors
Aydin, Z; Portela, JC; Kucuk, U; Zehir, MA; Gul, H; Bagriyanik, M; Soares, FJ; Ozdemir, A;

Publication
IET Conference Publications

Abstract
Building automation systems (BAS) have promising potential to support power and energy management applications, in addition to the current and conventional intention of use for improving comfort. Integration of BAS with smart meters to provide remote monitoring and control over user-friendly interfaces can foster consumer awareness, proactiveness towards more effective use of energy and it is one of the keystones of the future's smart cities. This paper proposes development and field implementation of a remote monitoring, control and data processing system for residential customers. The system is designed to comprise a widely used BAS protocol (KNX) and smart meters in the market, adding on a central database and a web application. The developed solution is implemented in 3 houses with real residents in Istanbul, Turkey. The study provides developments for hardware-software integration in building energy management and solutions for problems encountered during field implementation. Energy management potential of three houses from the field is also discussed.

2018

Explorative ex-ante consumer cluster delineation for electrification planning using image processing tools

Authors
Heymann, F; Heymann, F; Heymann, F; Martínez, PD; Soares, F; Miranda, V; Miranda, V;

Publication
IET Conference Publications

Abstract
The ex-ante division of consumers into potential off-grid and grid-extension clusters represents a crucial input to electrification planning. This paper explores the application of image processing tools to distinguish grid-expansion from offgrid consumer clusters spatially, considering peak-load surfaces. Instead of point-based cluster analysis, the proposed model induces morphological pixel changes in the image through filtering and segmentation techniques. This way, load clusters can be isolated based on texture and coherence in an unprecedented way. Various single and sequential image processing techniques are compared, together with a rough grid expansion-ratio estimate for each case. Model outcomes are benchmarked against off-grid/on-grid clusters retrieved by using the Rural Electrification Model.

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