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Sobre

Sobre

Ricardo Silva nasceu em 1988 no Porto. Completou o Mestrado Integrado em Engenharia Electrotécnica e de Computadores pela Faculdade de Engenharia da Universidade do Porto (FEUP) em 2018, tendo anteriormente completado o Mestrado em Biologia na Faculdade de Ciências da Universidade do Porto (FCUP) em 2011.


É atualmente investigador no INESC TEC desde 2018 no Centro de Sistemas de Energia. O seu trabalho tem-se focado essencialmente na gestão otimizada de microrredes, parques híbridos e mais recentemente comunidades de energia renovável, completada com abordagens inovadoras à modelização de baterias e outros recursos flexíveis. Participou em diversos projetos, nacionais e internacionais, com enfoque nesses mesmos tópicos, dos quais se destacam o projeto FLEXERGY, InterConnect, Baterias2030, SmartGlow e DigitalCER, entre outros.


Tem publicados, na área e à data de 2023, 3 artigos em revistas internacionais e 8 artigos em conferências internacionais.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Ricardo Silva
  • Cargo

    Investigador
  • Desde

    07 fevereiro 2018
011
Publicações

2024

Building Flexibility Bidding Curves for Energy Communities

Autores
Rodrigues, L; Mello, J; Ganesan, K; Silva, R; Villar, J;

Publicação
2024 20TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM 2024

Abstract
The integration of renewable generation requires new sources of flexibility, including the flexibility from distributed resources that can be unlocked via local flexibility markets (LFMs). In these markets, aggregators (AGGs) offer the flexibility from their portfolios to the flexibility requesting parties (FRP), i.e. system operators or other balancing requesting parties. To bid in LFMs and manage market uncertainty, AGGs must compute the flexibility they are willing to offer at each possible flexibility market price, by optimizing their portfolios. This paper proposes a 2-stage methodology to compute the flexibility bidding curve that an energy community can send to a LFM when behaving as an AGG of its members resources. At stage 1, the energy community (EC) manager computes the optimal EC operation without flexibility provision, minimizing the EC energy bill, and serving as the baseline to verify the flexibility provision. Then, at stage 2, for each possible flexibility price, the EC manager computes the optimal flexibility to be offered, minimizing the EC energy bill but including the flexibility provision incomes, to build the flexibility bidding curve.

2024

Shared Batteries Business Models for Energy Communities

Autores
Moreno, A; Villar, J; Macedo, P; Silva, R; Bayo, S; Bessa, R;

Publicação
2024 20TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM 2024

Abstract
The deployment of energy communities (EC) will foster new business models contributing to the decentralization and democratization of energy access and a reduction in the energy bill of final consumers. This decentralization is only possible if investments are made in production and storage technologies, that must be installed near the locals of consumption, according to common rules of the regulatory frameworks of EC. In this paper we propose a methodology for the optimal sizing of production and shared storage assets, and we assess the cost reduction of considering shared storage assets. We then formulate seven business models (BM) that dictate how to share this benefit among the EC members, and we propose two indicators to assess them. Results show the difficulty in choosing a BM as well as the limitations of the BM and of the indicators.

2023

A Three-Stage Model to Manage Energy Communities, Share Benefits and Provide Local Grid Services

Autores
Rocha, R; Silva, R; Mello, J; Faria, S; Retorta, F; Gouveia, C; Villar, J;

Publicação
ENERGIES

Abstract
This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer's individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers' energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer's new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

2023

Simulating a real time Walrasian local electricity market design: assessing auctioneer algorithm and price behavior

Autores
Mello, J; Retorta, F; Silva, R; Villar, J; Saraiva, JT;

Publicação
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
In Walrasian markets, an auctioneer proposes a price to the market participants, who react by revealing the quantities they are willing to buy or sell at this price. The auctioneer then proposes new prices to improve the demand and supply match until the equilibrium is reached. This market, common for stock exchanges, has also been proposed for electricity markets like power electricity exchanges, where iterations among auctioneer and market participants take place before the interval settlement period (ISP) until supply and demand match and a stable price is reached. We propose a Walrasian design for local electricity markets where the iterations between auctioneer and market participants happen in real time, so previous imbalances are used to correct the proposed price for the next ISP. The designs are simulated to test convergence and their capability of achieving efficient dynamic prices.

2023

Flexibility Modeling and Trading in Renewable Energy Communities

Autores
Agrela, J; Rezende, I; Soares, T; Gouveia, C; Silva, R; Villar, J;

Publicação
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
This work presents an approach to the flexibility of energy consumption in Renewable Energy Communities (RECs). A two-stage model for quantifying the flexibility provided by the domestic energy resources operation and its negotiation in a market platform is proposed. In stage 1, the optimal consumption of each prosumer is determined, as well as the respective technical flexibility of their resources, namely the maximum and minimum resource operation limits. In stage 2, this technical flexibility is offered in a local flexibility-only market structure, in which both the DSO and the prosumers can present their flexibility needs and requirements. The flexibility selling and buying bids of the prosumers participating in the market are priced based on their base tariff, which is the energy cost of the prosumers corresponding to their optimal schedule of the first stage when no flexibility is provided. Therefore, providing flexibility is an incentive to reduce their energy bill or increase their utility, encouraging their participation in the local flexibility market.

Teses
supervisionadas

2023

Local Electricity Market Simulator for Energy Communities

Autor
João Miguel da Costa Pinho

Instituição