Osório, Gerardo J.
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Osório
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Gerardo J.
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Gerardo J. Osório
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Gerardo J. Osório is an Assistant Professor and Coordinator at the 1st Cycle of Industrial Engineering and Management at the Science and Technology Department of Portucalense University Infante D. Henrique, Porto, Portugal. He finished the Ph.D. degree in Industrial Engineering and Management (Specialization in Energy and Optimization Systems), on 11/07/2015/ at the University of Beira Interior, Covilhã, Portugal. From the same university, he finished the MSc. in Computer Sciences and Electrical Engineering (Specialization in Automation and Controlling), on 07/07/2011. He authored or co-authored 125 publications, including more than 35 journal papers, 86 conference proceedings papers, and 5 book chapters, with an h-index of 22 and over 1940 citations. He was awarded directly and indirectly for his research work and scientific supervision 14 times. He has participated as Research Fellow in 5 project(s), and as Post-Doctoral Fellow in 2 projects, interacting with more than 150 collaborators in co-authoring scientific works. His domains are in the areas of Engineering Sciences and Technologies, Other Engineering Sciences, considering operational research, with an emphasis on renewable energy.
BD19-D0AD-65DB
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54783251300
C-3616-2014Research Projects
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REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura.
Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture.
Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations:
- the understanding of local, national and international environment;
- the development of activities oriented to professional practice, namely in the business world.
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Publication Restricted Access Assessing the impact of peer-to-peer markets on distribution grid operation2021-10 - Reina, Fábio C. G.; Santos, Sérgio F.; Erdinç, Ozan; Catalão, João P. S.; Osório, Gerardo J.; Santos, Sérgio F.Due to the considerable increase of distributed energy resources, a new model of energy trading called peer- to-peer (P2P) has emerged in local energy communities that play a key role in the proliferation of renewable energy sources. However, although local and distributed power trading allows for a more decentralized and open grid, these models have a significant impact on the control, operation, and planning of the electricity distribution grid. Thus, reducing the demand for power at an affordable price is one of the main objectives of P2P markets, considering the different voltage limits and possible congestion existing in the distribution system. Thus, the main goal of this work is to evaluate the impact of the P2P market on the distribution network operation. This work includes an energy community in a neighborhood involving nine connected houses and one school, involving different renewable technologies and energy storage systems installed in each consumer and/or prosumer. The simulation results indicate that in the presence of local distributed generation and the inclusion of energy storage devices and electric vehicles allow a high-cost reduction (16%) and a very positive impact on the distribution system in terms of congestion and voltage deviations.Publication Restricted Access Impact of uncertainty on energy hub optimization based on energy resources distribution and demand Response [comunicação oral]2024-06-17 - Azevedo, Tiago M.M.; Ghavidel, Morteza V.; Catalão, João P. S.; Osório, Gerardo J.; Santos, Sérgio F.In recent years, significant efforts have been made worldwide, including research projects and political resolutions, to support the incorporation of renewable energy sources into power systems to help sustainable energy goals. Moreover, to build cleaner and sustainable energy systems, it is necessary to develop integrated systems, known as multi-energy systems (MES), where multiple electricity production facilities optimally communicate with each other in different layers, creating an energy hub. This work seeks to develop an energy hub model to help energy system operators make better decisions in scenarios of high uncertainty. In this model, the information-gap decision theory (IGDT) is applied to measure risk. The considered uncertainties in this study include the price of natural gas and electricity. A ‘time-of-use’ code is also considered the change of a percentage of the load from peak hours to valley hours, minimizing the operating costs. The results demonstrate that risk management tools, such as an IGDT-risk-averse model and the introduction of demand response programs, are fundamental tools for assessing the impact of uncertainty on energy hubs. Indeed, the tool allows the operator to maintain an acceptable level of uncertainty and robustness of the system while ensuring that the system is reliable and has acceptable operating costs.Publication Restricted Access A fully decentralized machine learning algorithm for optimal power flow with cooperative information exchange2022-02-05 - Lotfi, Mohamed; Javadi, Mohammad; El Moursi, Mohamed; Monteiro, Cláudio; Catalão, João P. S.; Osório, Gerardo J.Traditional power grids, being highly centralized in terms of generation, economy, and operation, continually employed probabilistic methods to account for load uncertainties. In modern smart grids (SG), the rapid proliferation of non-dispatchable generation (physical decentralization) and liberal markets (market decentralization) leads to the dismantling of the centralized paradigm, with operations being performed by several decentralized agents. Handling uncertainty in this new paradigm is aggravated due to 1) a vastly increased number of uncertainty sources, and 2) decentralized agents only have access to local data and limited information on other parts of the grid. A major problem identified in modern and future SGs is the need for fully decentralized optimal operation techniques that are computationally efficient, highly accurate, and do not jeopardize the data privacy and security of individual agents. Machine learning (ML) techniques, being successors to traditional probabilistic methods are identified as a solution to this problem. In this paper, a conceptual model is constructed for the transition from a fully centralized operation of an SG to a decentralized one, proposing the transition scheme between the two paradigms. A novel ML algorithm for fully decentralized operation is proposed, formulated, implemented, and tested. The proposed algorithm relies solely on local historical data for local agents to accurately predict their optimal control actions without knowledge of the physical system model or access to historical data of other agents. The capability of cloud-based cooperative information exchange was augmented through a new concept of s-index activation codes, being encoded vectors shared between agents to improve their operation without sharing raw information. The algorithm is tested on a modified IEEE 24-bus test system and synthetically generates historical data based on typical load profiles. A week-ahead high-resolution (15-minute) fully decentralized operation case is tested. The algorithm is shown to guarantee less than 0.1% error compared to a centralized solution and to outperform a neural network (NN). The algorithm is exceptionally accurate while being highly computationally efficient and has great potential as a versatile model for the fully decentralized operation of SGs.Publication Restricted Access Day-Ahead optimal management of plug-in hybrid electric vehicles in smart homes considering uncertainties2021-01-30 - Hasankhani, Arezoo; Hakimi, Seyed M.; Bodaghi, Maryam; Shafie-khah, Miadreza; Catalão, João P. S.; Osório, Gerardo J.The plug-in hybrid electric vehicles (PHEVs) integration into the electrical network introduces new challenges and opportunities for operators and PHEV owners. On the one hand, PHEVs can decrease the environmental pollution. On the other hand, the high penetration of PHEVs in the network without charging management causes harmonics, voltage instability, and increased network problems. In this study, a charging management algorithm is presented to minimize the total cost and flatten the demand curve. The behavior of the PHEV owner in terms of arrival time and leaving time is modeled with a stochastic distribution function. The battery model and hourly power consumption of PHEV are modeled, and the obtained models are applied to determine the battery's state of charge. The proposed method is tested on a sample demand curve with and without a charging management algorithm to verify the efficiency. The results verify the efficiency of the proposed method in decreasing the total cost using the management algorithm for PHEVs, especially when the PHEVs sell the electricity to the network.Publication Restricted Access Towards reducing electricity costs in an energy community equipped with home energy management systems and a local energy controller2023-09-22 - Javadi, Mohammad S.; Cardoso, Ricardo J.A.; Catalão, João P. S.; Osório, Gerardo J.An energy community equipped with Home Energy Management Systems (HEMSs) is considered in this paper. A local energy controller in the energy community makes it possible to transact energy between houses to support the different consumption patterns of each end-user. Price-based voluntary Demand Response (DR) programs are applied to each house to motivate end-users to alter their consumption patterns, allowing the necessary flexibility of the electrical grid. Also, the existence of Renewable Energy Sources (RES) micro-generation and an Energy Storage System (ESS) are taken into account. The results demonstrate that the proposed model based on Mixed-Integer Linear Programming (MILP) is fully capable of reducing daily electricity costs while considering end-users' comfort and respecting the different technical constraints.Publication Restricted Access Impact of P2P market transactions on distribution network congestion considering physical constraints2023-09-27 - Santos, Sérgio F.; Branco, José T. R. A.; Catalão, João P. S.; Osório, Gerardo J.; Santos, Sérgio F.The novel trend of peer-to-peer (P2P) transactions has allowed traditional consumers to become prosumers, capable of maximizing the usage of their energy production by sharing it with their neighbors. Thus, the P2P market has emerged to allow both prosumers and consumers to trade energy independently from the conventional market. However, while local energy transactions will allow for a more open and decentralized grid, they will nevertheless have a significant impact on the planning, control and operation of distribution grids. Hence, in this paper, an improved model is presented to evaluate the impact of P2P transactions on distribution grid congestion, considering its restrictions and the uncertainty associated with renewable energy sources generation and load. The objective function has been modeled to minimize the transaction costs of each prosumer/consumer. The model was tested on a branch adapted from a 119-bus IEEE test grid, in which different operational scenarios have been considered through case studies, considering the various RES technologies and energy storage systems (ESS) installed by each prosumer/consumer. Comprehensive simulation results indicate that the introduction of smart grid enabling technologies and P2P transactions has led to both technical (voltage profile and grid congestion) and economic benefits for the distribution grid and its users.Publication Restricted Access Influence of demand response programs in microgrids facing photovoltaic and battery integration2021-10-21 - Ramos, Bruno P.; Vahid-Ghavidel, Morteza; Shafie-khah, Miadreza; Erdinç, Ozan; Catalão, João P. S.; Osório, Gerardo J.Yearly, the number of Distributed Energy Resources (DER) integrated into the power grid increases has increased, having a large impact on power generation globally, promoting the introduction of renewable energy resources (RER). To increase the flexibility of the power system with integrated RER, the introduction of energy storage systems (ESS) is essential. Demand response (DR) programs also help to increase grid flexibility, resulting in increased grid reliability as grid congestion and losses decrease. However, this new paradigm shift needs further research and careful analysis. In this work, two types of DR programs are addressed to promote greater participation by different consumers features. To interconnect the different consumers, DR aggregators are inserted to ensure that individual consumers have influence on the power market. All these aspects, if accompanied by information, measurement, communication, and control systems, give rise to the smart grids, playing an essential role. The results show, considering the worst uncertainty case scenario, that there is a suitable total RER of 2151.50 kW, against 3227.30 kW, by not considering the RER uncertainty.Publication Restricted Access Modeling an electric vehicle parking lot with solar rooftop participating in the reserve market and in ancillary services provision2021-10-10 - Lotfi, Mohamed; Gough, Matthew; Javadi, Mohammad; Espassandim, Helena M. D.; Shafie-khah, Miadreza; Catalão, João P. S.; Osório, Gerardo J.Electric vehicles (EVs) are seen as a crucial tool to reduce the polluting emissions caused by the transport and power systems (PS) sector and the associated shift to a cleaner and more sustainable energy sector. The combination of EVs and solar photovoltaics (PV) in PS, specifically through the aggregation of EVs in parking lots (PLs), may improve the reliability and flexibility of the PS, assisting the power network in critical moments. This work proposes a novel aggregator agent in the energy system which is an EV charging station with an installed PV system. In this work, an optimal operation strategy for the solar-powered EV PL (EVSPL) operation is presented. The model optimizes the EVSPL’s participation in various energy and ancillary services markets, including the effects of capacity payments. The results show that the EVSPL leads to higher profits. The EVSPL’s participation in ancillary services is highly influenced by the prices. The results of this work show that this novel agent can actively participate in the energy system in an economically viable manner while respecting the technical constraints of the network and providing important ancillary services to the system operator.Publication Restricted Access Flexibility participation by prosumers in active distribution network operation2022-08-19 - Lopez, Sergio R.; Gutierrez-Alcaraz, Gillermo; Javadi, Mohammad S.; Catalão, João P. S.; Osório, Gerardo J.This paper investigates prosumers' flexibility provision for the optimal operation of active distribution networks in a transactive energy (TE) market. From a prosumer point of view, flexibility can be provided to operators using renewable energy resources (RES) and demand response (DR) through home appliances with the ability to modify their consumption profiles. In the TE market model, the distribution system operator (DSO) is responsible for market-clearing mechanisms and controlling the net power exchange between the distribution network and the upstream grid. The contribution of this work is the enhancement of a strategy to reduce the operational costs of an active distribution network by using prosumers' flexibility provision through an aggregator or a smart building coordinator. To this end, a TE market for both energy and flexibility trading at distribution networks is presented, demonstrating the possibility to fulfill DSO requirements through flexibility contributions in the day-ahead (DA) and real-time (RT) markets.Publication Restricted Access Stochastic distribution network operation for transactive energy markets2021-09 - Santos-Gonzalez, E. E.; Gutierrez-Alcaraz, G.; Nezhad, A. E.; Javadi, Mohammad; Catalão, João P. S.; Osório, Gerardo J.In this paper, a stochastic optimization model is developed for optimal operation of the active distribution networks. The proposed model is investigated on the transactive energy market in the presence of active consumers, local photovoltaic power generations and storage devices. The stochastic behavior of photovoltaic panel power generation units and load consumptions have been modeled using scenario generations and scenario reduction technique. Besides, the stochastic nature of the demand power, as well as rooftop photovoltaic panels, have been investigated in this paper. In the transactive energy market model, the distribution system operator is the main responsible for the market-clearing mechanisms and controlling the net power exchange between the distribution network and upstream grid. The proposed model is tested and verified on a radial medium voltage distribution network with 16 buses.