Ricardo J. Bessa's research while affiliated with Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) and other places
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Publications (108)
The deployment of smart metering technologies in the low voltage (LV) grid created conditions for the application of data-driven monitoring and control functions. However, data privacy regulation and consumers’ aversion to data sharing may compromise data exchange between utility and customers. This work presents a data-driven method, based on smar...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...
Abstract As the penetration levels of renewable energy sources increase and climatic changes produce more and more extreme weather conditions, the uncertainty of weather and power production forecasts can no longer be ignored for grid operation and electricity market bidding. In order to support the energy industry in the integration of uncertainty...
The papers in this special section focus on advances in renewable energy forecasting, predictability, business models, and applications in the power industry. During the last 25 years, research has been conducted for developing renewable energy source (RES) forecasting algorithms, especially for wind and solar energy, seeking an improvement of pred...
Dealing with scarcity events is nowadays gaining relevance in electricity market studies, as traditionally predictable generation and consumption patterns are fading. Policymakers and system planners use therefore adequacy studies to a) understand if the current market design will attract sufficient generation capacity to meet electricity demand in...
The need to take into account and explicitly model forecast uncertainty is today at the heart of many scientific and applied enterprises. For instance, the ever-increasing accuracy of weather forecasts has been driven by the development of ensemble forecasts, where a large number of forecasts are generated either by generating forecasts from differ...
Network human operators’ decision-making during grid outages requires significant attention and the ability to perceive real-time feedback from multiple information sources to minimize the number of control actions required to restore service, while maintaining the system and people safety. Data-driven event and alarm management have the potential...
An IEA Wind Task 36 & WEXICOM “Probabilistic Forecasting Games and Experiments” initiative: How do Humans decide under Wind Power Forecast Uncertainty?
The need to take into account and explicitly model forecast uncertainty is today at the heart of many scientific and applied enterprises. For instance, the ever-increasing accuracy of weather forec...
Download the AWARD WINNING poster from windeurope.org/tech2021 #WindTech21 and hear the author's description here: https://windeurope.org/ElectricCity2021/conference/posters/PO008/
Abstract:
As penetration levels of renewable energy sources increase and climatic changes produce more and more extreme weather conditions, the uncertainty of weather a...
One of the major barriers for the retailers is to understand the consumption elasticity they can expect from their contracted demand response (DR) clients. The current trend of DR products provided by retailers are not consumer-specific, which poses additional barriers for the active engagement of consumers in these programs. The elasticity of cons...
Electricity systems around the world are decarbonizing, driven by reductions in the cost of renewable energy and encouraged by supportive regulatory policy. Electricity market designs are increasingly being tested to ensure that the bulk power system can deliver reliable, cost-effective energy to all consumers.
One of the major barriers for the retailers is to understand the consumption elasticity they can expect from their contracted demand response (DR) clients. The current trend of DR products provided by retailers are not consumer-specific, which poses additional barriers for the active engagement of consumers in these programs. The elasticity of cons...
The evolution of the electrical power sector due to the advances in digitalization, decarbonization and decentralization has led to the increase in challenges within the current distribution network. Therefore, there is an increased need to analyze the impact of the smart grid and its implemented solutions in order to address these challenges at th...
It is widely recognized by both academia and industry that renewable energy sources (RES) uncertainty forecasting can provide more information, enable risk quantification in power system operation and lead to economic savings and reliability improvement. The literature about stochastic approaches that integrate RES forecast uncertainty in various u...
Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, v...
Data exchange between multiple renewable energy power plant owners can lead to an improvement in forecast skill thanks to the spatio-temporal dependencies in time series data. However, owing to business competitive factors, these different owners might be unwilling to share their data. In order to tackle this privacy issue, this paper formulates a...
Probabilistic forecasting of distribution tails (i.e., quantiles below 0.05 and above 0.95) is challenging for non-parametric approaches since data for extreme events are scarce. A poor forecast of extreme quantiles can have a high impact in various power system decision-aid problems. An alternative approach more robust to data sparsity is extreme...
Forecasts of residual demand curves (RDCs) are valuable information for price-maker market agents since it enables an assessment of their bidding strategy in the market-clearing price. This paper describes the application of deep learning techniques, namely long short-term memory (LSTM) network that combines past RDCs and exogenous variables (e.g.,...
My contributions to this voluminous publication can be found on
pp 38-40 "The natural law of growth in competition" and on
pp 169-170 "Dealing with logistic forecasts in practice"
This paper provides a survey of big data analytics applications and associated implementation issues. The emphasis is placed on applications that are novel and have demonstrated value to the industry, as illustrated using field data and practical applications. The paper reflects on the lessons learned from initial implementations, as well as ideas...
The modern digital era is characterized by a plethora of emerging technologies, methodologies and techniques that are employed in the manufacturing industries with intent to improve productivity, to optimize processes and to reduce operational costs. Yet, algorithms and methodological approaches for improvement of energy consumption and environment...
Wind power forecasts have been operationally used for over 25 years. Despite this fact, there are still many possibilities to improve and enhance forecasts, both from the weather prediction side and in the use of the forecasts. Until now, most applications have focused on deterministic forecast methods. This is likely to change in the future as pen...
As the penetration levels of RES increase and climatic changes lead to increasingly more extreme weather conditions, the uncertainty of the weather forecasts and power production forecasts can no longer be ignored for the grid operation. In order to support the power industry in the adaptation of uncertainty forecasts into their business practices,...
This study offers an overview of the H2020 InterConnect project, which targets the relation between smart homes and distribution grids. The project vision is to produce a digital marketplace, using an interoperable marketplace toolbox and Smart appliances REference Ontology (SAREF) compliant Internet of Things (IoT) reference architecture as the ma...
Geographically distributed wind turbines, photovoltaic panels and sensors (e.g., pyranometers) produce large volumes of data that can be used to improve renewable energy forecasting skill. However, data owners may be unwilling to share their data, even if privacy is ensured, due to a form of prisoner's dilemma: all could benefit from data sharing,...
The implementation of efficient demand response (DR) programs for household electricity consumption would benefit from data-driven methods capable of simulating the impact of different tariffs schemes. This paper proposes a novel method based on conditional variational autoencoders (CVAE) to generate, from an electricity tariff profile combined wit...
Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in coll...
This paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this must be based on conservative approaches able to...
The implementation of efficient demand response (DR) programs for household electricity consumption would benefit from data-driven methods capable of simulating the impact of different tariffs schemes. This paper proposes a novel method based on conditional variational autoencoders (CVAE) to generate, from an electricity tariff profile combined wit...
The grid and market hub is a core development of InteGrid, an H2020 project, which has recently entered its demonstration phase. This central and neutral hub aims to demonstrate the key role of the DSO in the energy transition, namely in a scenario foreseen to have a large-scale dissemination of DERs, being them small generation (PV, wind), electri...
The current coordination between the transmission system operator (TSO) and the distribution system operator (DSO) is changing mainly due to the continuous integration of distributed energy resources (DER) in the distribution system. The DER technologies are able to provide reactive power services helping the DSOs and TSOs in the network operation....
The aim of this paper is to present the objectives, research directions and first highlight results of the Smart4RES project, which was launched in November 2019, under the Horizon 2020 Framework Programme. Smart4RES is a research project that aims to bring substantial performance improvements to the whole model and value chain in renewable energy...
The aim of this paper is to present the objectives, research directions and first highlight results of the Smart4RES project, which was launched in November 2019, under the Horizon 2020 Framework Programme. Smart4RES is a research project that aims to bring substantial performance improvements to the whole model and value chain in renewable energy...
Cooperation between different data owners may lead to an improvement of forecast skill by, for example, taking advantage of spatio-temporal dependencies in geographically distributed renewable energy time series. Due to business competitive factors and personal data protection, these data owners might be unwilling to share their information, which...
The decarbonization of the economy, for which the contribution of power systems is significant, is a growing trend in Europe and in the world. In order to achieve the Paris Agreement's ambitious environmental goals, a substantial increase in the contribution of renewable sources to the energy generation mix is required. This trend brings about rele...
Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data privacy and protection imposes the need to develop local models for flexibility modeling and forecasting and...
Urban wastewater sector is being pushed to optimize processes in order to reduce energy consumption without compromising its quality standards. Energy costs can represent a significant share of the global operational costs (between 50% and 60%) in an intensive energy consumer. Pumping is the largest consumer of electrical energy in a wastewater tre...
Forecasting for wind and solar renewable energy is becoming more important as the amount of energy generated from these sources increases. Forecast skill is improving, but so too is the way forecasts are being used. In this paper, we present a brief overview of the state‐of‐the‐art of forecasting wind and solar energy. We describe approaches in sta...
Providing a price tariff that matches the randomized behavior of residential consumers is one of the major barriers to demand response (DR) implementation. The current trend of DR products provided by aggregators or retailers are not consumer-specific, which poses additional barriers for the engagement of consumers in these programs. In order to ad...
Distribution system operators (DSO) are currently moving towards active distribution grid management. One goal is the development of tools for operational planning of flexibility from distributed energy resources (DER) in order to solve potential (predicted) congestion and voltage problems. This work proposes an innovative flexibility management fu...
Variable-speed pump power storage is an innovative large-scale technology that is being deployed across the world. In addition to price arbitrage and provision of downward replacement reserve, its operational flexibility enables the provision of frequency restoration reserve (FRR) both in turbine and pump modes. This work proposes a bidding optimiz...
This paper presents a new method to identify classes of events, by processing phasor measurement units (PMU) frequency data through deep neural networks. Deep tapered Multi-layer Perceptrons of the half-autoencoder type, Deep Belief Networks and Convolutional Neural Networks (CNN) are compared, using real data from Brazil. A sound success is obtain...
The wastewater management sector is being pushed to optimize processes in order to reduce energy consumption without compromising its quality standards. Energy costs can represent a significant share of the global operational costs (between 50\% and 60\%) in a energy intensive consumer. Recent advancements in smart water networks and internet-of-th...
Concerns about global warming, scarcity of fossil fuel reserves, and primary energy independence of regions or countries have led to a dramatic increase of renewable energy sources (RES) penetration in electric power systems, mainly wind and solar power. This chapter describes developments in several interdisciplinary topics related with managing h...
Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data privacy and protection imposes the need to develop local models for flexibility modeling and forecasting and...
The penetration of Distributed Renewable Energy Sources (DRES) in the distribution grid is increasing considerably in the last years. This is one of the main causes that contributed to the growth of technical problems in both transmission and distribution systems. An effective solution to improve system security is to exploit the flexibility that c...
This paper reviews flexibility products and flexibility markets, currently being discussed or designed to help in the operation of power systems under their evolving environment. This evolution is characterized by the increase of renewable generation and distributed energy resources (including distributed generation, self-consumption, demand respon...
The technological revolution in the electric power system sector is producing large volumes of data with pertinent impact in the business and functional processes of system operators, generation companies, and grid users. Big data techniques can be applied to state estimation, forecasting, and control problems, as well as to support the participati...
The system operator is responsible for maintaining a constant balance between generation and load to keep frequency at the nominal value. This fundamental objective is achieved with upward (e.g., synchronized and nonsynchronized generation units) and downward (e.g., demand response, storage) reserve capacity. The system operator needs to define, in...
Near-future electric distribution grids operation will have to rely on demand-side flexibility, both by implementation of demand response strategies and by taking advantage of the intelligent management of increasingly common small-scale energy storage. The Home energy management system (HEMS), installed at low voltage residential clients, will pla...
Probabilistic forecasts in general and ensemble forecasting in particular may contain a paradigm shift in the way renewable energy forecasts have been used and evaluated in the past 20 years, where deterministic forecasting has been established and been practiced in all power markets, where the level of wind power penetration increased over a few p...
It is in the nature of chaotic atmospheric processes that weather forecasts will never be perfectly accurate. This natural fact poses challenges not only for private life, public safety, and traffic but also for electrical power systems with high shares of weather-dependent wind and solar power production. To facilitate a secure and economic grid a...
Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset,...
Probabilistic forecasts in general and ensemble forecasting in particular may contain a paradigm shift in the way renewable energy forecasts have been used and evaluated in the past 20 years. In this work we demystify the use of uncertainty forecasts by providing some important definitions, showing a number of applications with best practices cases...
RESUMO A perspectiva de uma maior participação das fontes eólicas no Sistema Interligado Nacional aponta para a necessidade de incluir a previsão de curto prazo da geração eólica nos procedimentos da operação em tempo real e da programação diária da operação. No presente trabalho apresentam-se duas abordagens para previsão probabilística da geração...
This study presents the results of field tests performed on French medium-voltage distribution networks with two novel algorithms developed in the framework of the evolvDSO Project. Working in the transmission system operator and distribution system operator (TSO–DSO) cooperation domain, the interval constrained power flow tool estimates the flexib...
First comprehensive Review of Uncertainty Forecasting for the power industry including the entire range of methods from weather forecasting methods generating probabilistic input to wind to power and solar to power models.
We also describe a number of applications, where uncertainty forecasts are relevant and beneficial.
Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather...
The increasing penetration of renewable energy sources characterized by a high degree of variability and uncertainty is a complex challenge for network operators that are obligated to ensure their connection while keeping the quality and security of supply. In order to deal with this variable behavior and forecast uncertainty, the distribution netw...
Further integration of distributed renewable energy sources in distribution systems requires a paradigm change in grid management by the distribution system operators (DSO). DSOs are currently moving to an operational planning approach based on activating flexibility from distributed energy resources in day/hour-ahead stages. This paper follows the...
In the last two decades, renewable energy forecasting progressed towards the development of advanced physical and statistical algorithms aiming at improving point and probabilistic forecast skill. This paper describes a forecasting framework to explore information from a grid of numerical weather predictions (NWP) applied to both wind and solar ene...
This paper provides an overview of the expected role that variable speed hydro power plants can have in future electric power systems characterized by a massive integration of highly variable sources. Therefore, it is discussed the development of a methodology for optimising the operation of hydropower plants under increasing contribution from new...
The increase penetration of renewable energy sources (RES) into the European power system has introduced a significant amount of variability and uncertainty in the generation profiles raising the needs for ancillary services as well as other tools like demand response, improved generation forecasting techniques and changes to the market design. Whi...
Near-future electric distribution grids operation will have to rely on demand-side flexibility, both by implementation of demand response strategies and by taking advantage of the intelligent management of increasingly common small-scale energy storage. Home energy management systems (HEMS) will play a crucial role on the flexibility provision to b...