Santos, Sérgio F.

Santos, Sérgio F.

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Santos

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Sérgio F.

Name

Santos, Sérgio F.

Biography

Sérgio F. Santos, doutorado em Engenharia Eletrotécnica e de Computadores, prof. auxiliar na Universidade Portucalense Infante D. Henrique e prof. Convidado na Universidade de Aveiro. Autor de mais de 30 publicações em jornais científicos e mais de 45 publicações em atas de conferencia, com um h-index de 20 e mais 2075 citações de acordo com SG, tendo supervisionadomais de 30 alunos entre mestrado e doutoramento, estágios curriculares e outros alunos com bolsas. Os interesses de investigação são “demand response”, “multi-energy systems”, “system flexibility”, “energy communities”, “virtual power plants” e “ancillary services” e “grid resilience”. Afiliação: REMIT – Research on Economics, Management and Information Technologies. DCT - Departamento de Ciência e Tecnologia.

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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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Now showing 1 - 10 of 26

Open Access
Optimal stochastic conditional value at risk-based management of a demand response aggregator considering load uncertainty
2021-11-03 - Vahid-Ghavidel, Morteza; Javadi, Mohammad Sadegh; Santos, Sérgio F.; Gough, Matthew; Shafie-khah, Miadreza; Catalão, João P. S.; Santos, Sérgio F.
This paper models a novel demand response (DR) trading strategy. In this model, the DR aggregator obtains the DR from the end-users via two types of DR programs, i.e. a time-of-use (TOU) program and an incentive-based DR program. Then, it offers this DR to the wholesale market. Three consumer sectors, namely residential, commercial and industrial, are included in this problem. The DR program is dependent on their corresponding load profiles during the studied time horizon. This paper uses a mixed-integer linear programming (MILP) problem and it is solved using the CPLEX solver through a stochastic programming approach in GAMS. The risk measure chosen to represent the load uncertainty of the users who are participating in the DR program is Conditional Value-at-Risk (CVaR). The proposed problem is simulated and assessed through a case study of a test system. The results indicate that the industrial loads play a major role in the power system and this directly affects the DR program. Moreover, the risk-averse decision-maker in this model favors a reduced participation in the DR programs when compared to a decision-maker who is risk-neutral, since the risk-averse decision maker prefers to be more secure against uncertainties. In other words, an increase in risk factor results in a decrease in the participation rate of the consumers in DR programs.
Open Access
Influence of battery energy storage systems on transmission grid operation with a significant share of variable renewable energy sources
2022-03 - Santos, Sérgio F.; Gough, Matthew; Fitiwi, Desta Z.; Silva, André F. P.; Shafie-khah, Miadreza; Catalão, João P. S.; Santos, Sérgio F.
The generation mix of Portugal now contains a significant amount of variable renewable energy sources (RES) and the amount of RES is expected to grow substantially. This has led to concerns being raised regarding the security of the supply of the Portuguese electric system as well as concerns relating to system inertia. Deploying and efficiently using various flexibility options is proposed as a solution to these concerns. Among these flexibility options proposed is the use of battery energy storage systems (BESSs) as well as relaxing system inertia constraints such as the system nonsynchronous penetration (SNSP). This article proposes a stochastic mixed-integer linear programming problem formulation, which examines the effects of deploying BESS in a power system. The model is deployed on a real-world test case and results show that the optimal use of BESS can reduce system costs by as much as 10% relative to a baseline scenario and the costs are reduced further when the SNSP constraint is relaxed. The amount of RES curtailment is also reduced with the increased flexibility of the power system through the use of BESS. Thus, the efficiency of the Portuguese transmission system is greatly increased by the use of flexibility measures, primarily the use of BESS.
Restricted Access
Impact of P2P market transactions on distribution network congestion considering physical constraints
2023-09-27 - 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.
Open Access
Flexibility provision by active prosumers in microgrids
2021-11-03 - Castro, Rodrigo M.; Javadi, Mohammad S.; Santos, Sérgio F.; Gough, Matthew; Vahid-Ghavidel, Morteza; Catalão, João P. S.; Santos, Sérgio F.
This paper focuses primarily on the flexibility of active prosumers in an islanded microgrid operation. The main objective is finding the best strategy to implement on an existing medium voltage grid, with several consumers, with the capability of producing some power for the grid operation, via Renewable Energy Resources (RES), or thermal Units, generally gas turbines, also there is the capability of some energy storage through batteries. Since power output of RES has a cost per kw of zero, it is greatly important to find the best combination of these resources who best suit the test system. For the purposes of these tests, the available investment funds are unlimited, although, there are some constraints regarding maximum RES penetration and ESS capacity.
Restricted Access
Blockchain-based transactive energy framework for connected virtual power plants
2022-01 - Gough, Matthew; Santos, Sérgio F.; Almeida, A.; Lotfi, Mohamed; Javadi, Mohammad; Fitiwi, Desta Z.; Castro, Rui; Catalão, João P. S.; Osório, Gerardo J.; Santos, Sérgio F.
Emerging technologies are helping to accelerate the ongoing energy transition. At the forefront of these new technologies is blockchain, which has the potential to disrupt energy trading markets. This paper explores this potential by presenting an innovative multi-level Transactive Energy (TE) optimization model for the scheduling of Distributed Energy Resources (DERs) within connected Virtual Power Plants (VPPs). The model allows for energy transactions within a given VPP as well as between connected VPPs. A blockchain based smart contract layer is applied on top of the TE optimization model to automate and record energy transactions. The model is formulated to adhere to the new regulations for the self-generation and self-consumption of energy in Portugal. This new set of regulations can ease barriers to entry for consumers and increase their active participation in energy markets. Results show a decrease in energy costs for consumers and increased generation of locally produced electricity. This model shows that blockchain based smart contracts can be successfully integrated into a hierarchical energy trading model, which respects the novel energy regulation. This combination of technologies can be used to increase consumer participation, lower energy bills, and increase the penetration of locally generated electricity from renewable energy sources
Open Access
Distribution systems resilience improvement utilizing multiple operational resources
2021-11-03 - Home-Ortiz, Juan M.; Melgar-Dominguez, Ozy D.; Javadi, Mohammad S.; Santos, Sérgio F.; Mantovani, José Roberto Sanches; Catalão, João P. S.; Santos, Sérgio F.
This paper presents a strategy based on mixed-integer linear programing (MILP) model to improve the resilience in electric distribution systems (EDSs). The restoration process considers operational resources such as the optimal coordination of dynamic switching operations, islanding operation of distributed generation (DG) units, and displacement of mobile emergency generation (MEG) units. In addition, the benefits of considering a demand response (DR) program to improve the recoverability of the system are also studied. The switching operations aim to separate the in-service from the out-of-service part of the system keeping the radiality of the grid. The proposed MILP model is formulated as a stochastic scenario-based problem where the uncertainties are associated with PV-based power generation and demand consumption. The objective function minimizes the amount of energy load shedding after fault, and the generation curtailment of the PV-based DG. To validate the proposed strategy, a 33-bus EDS is analyzed under different test cases. Results show the benefits of coordinating the dynamic switching operations, the optimal scheduling of MEG units, and a demand response program during the restoration process.
Restricted Access
Agent-based modeling of peer-to-peer energy trading in a smart grid environment
2021-09 - Silva, Pedro; Gough, Matthew; Santos, Sérgio F.; Shafie-khah, M.; Catalão, João P. S.; Osório, Gerardo J.; Santos, Sérgio F.
End users have become active participants in local electricity market transactions because of the growth of the smart grid concept and energy storage systems (ESS). This participation is optimized in this article using a stochastic two-stage model considering the day-ahead and real-time electricity market data. This model optimally schedules the operation of a Smart Home (SH) to meet its energy demand. In addition, the uncertainty of wind and photovoltaic (PV) generation is considered along with different appliances. In this paper, the participation of an EV (electric vehicle), together with the battery energy storage systems, which allow for the increase in bidirectional energy transactions are considered. Demand Response (DR) programs are also incorporated which consider market prices in real-time and impact the scheduling process. A comparative analysis of the performance of a smart home participating in the electricity market is carried out to determine an optimal DR schedule for the smart homeowner. The results show that the SH’s participation in a real-time pricing scheme not only reduces the operating costs but also leads to better than expected profits. Moreover, total, day-ahead and real-time expected profits are better in comparison with existing literature. The objective of this paper is to analyze the SH performance within the electrical market context so as to increase the system’s flexibility whilst optimizing DR schedules that can mitigate the variability of end-users generation and load demand.
Restricted Access
Two-stage optimal operation of smart homes participating in competitive electricity markets
2021-11-03 - Silva, Pedro; Gough, Matthew; Santos, Sérgio F.; Home-Ortiz, Juan M; Shafie-khah, Miadreza; Catalão, João P.S.; Osório, Gerardo J.; Santos, Sérgio F.
End users have become active participants in local electricity market transactions because of the growth of the smart grid concept and energy storage systems (ESS). This participation is optimized in this article using a stochastic two-stage model considering the day-ahead and real-time electricity market data. This model optimally schedules the operation of a Smart Home (SH) to meet its energy demand. In addition, the uncertainty of wind and photovoltaic (PV) generation is considered along with different appliances. In this paper, the participation of an EV (electric vehicle), together with the battery energy storage systems, which allow for the increase in bidirectional energy transactions are considered. Demand Response (DR) programs are also incorporated which consider market prices in real-time and impact the scheduling process. A comparative analysis of the performance of a smart home participating in the electricity market is carried out to determine an optimal DR schedule for the smart homeowner. The results show that the SH’s participation in the real-time pricing, scheme not only reduces the operating costs but also leads to better than expected profits. Moreover, total, day-ahead, and real-time expected profits are better in comparison with existing literature. The objective of this paper is to analyze the SH performance within the electrical market context so as to increase the system’s flexibility whilst optimizing DR schedules that can mitigate the variability of end-users generation and load demand.
Open Access
Providing flexibility in distribution systems by electric vehicles and distributed energy resources in the context of technical virtual power plants
2021-11-03 - Gough, Matthew; Santos, Sérgio F.; Pereira, Pedro M. C.; Home-Ortiz, Juan M.; Castro, Rui; Catalão, João P. S.; Santos, Sérgio F.
In the recent past structural changes in the operation and topology of the electrical system have occurred. These changes have coincided with the emergence of distributed energy resources (DERs). Relating to supply side technologies, distributed generation (DG) units have become increasingly common. The demand side has also seen the growth of new technological applications, including electric vehicles (EVs). These changes to the electrical system are being especially felt at the low voltage network level. Technical Virtual Power Plants (TVPPs) have been used to optimally schedule these DERs to increase the network flexibility and at the same time increasing the reliability and power quality of the network and this can bring economic benefits to both the TVPP operator and the customer. This paper develops a stochastic mixed-integer linear programming (MILP) optimization model to maximize the profit of a TVPP. The main objective of the TVPP is to increase operational flexibility of the low voltage network by aggregating DERs, including DG units, Heating Ventilation and Air Conditioning units, and EVs. The model is examined through the use of the IEEE 119-Bus test system. Results demonstrate that the inclusion of DG units and EVs, the profit of the TVPP increases by approximately 45% and system flexibility is increased while respecting the technical constraints of the network and the thermal comfort of the consumers.
Open Access
Bi-level stochastic energy trading model for technical virtual power plants considering various renewable energy sources, energy storage systems and electric vehicles
2023-09-15 - Gough, M.; Santos, Sérgio F.; Javadi, M.S.; Home-Ortiz, J.M.; Castro, R.; Catalão, J.P.S.; Santos, Sérgio F.
he ongoing transition of the energy system towards being low-carbon, digitized and distributed is accelerating. Distributed Energy Resources (DERs) are playing a major role in this transition. These DERs can be aggregated and controlled by Virtual Power Plants (VPPs) to participate in energy markets and make full use of the potential of DERs. Many existing VPP models solely focus on the financial impact of aggregating DERs and do not consider the technical limitations of the distribution system. This may result in technically unfeasible solutions to DERs operations. This paper presents an expanded VPP model, termed the Technical Virtual Power Plant (TVPP), which explicitly considers the technical constraints of the network to provide operating schedules that are both economically beneficial to the DERs and technically feasible. The TVPP model is formulated as a bi-level stochastic mixed-integer linear programming (MILP) optimization model. Two objective functions are used, the upper level focuses on minimizing the amount of power imported into the TVPP from the external grid, while the lower level is concerned with optimally scheduling a mixture of DERs to increase the profit of the TVPP operator. The model considers three TVPPs and allows for energy trading among the TVPPs. The model is applied to several case studies based on the IEEE 119-node test system. Results show improved DERs operating schedules, improved system reliability and an increase in demand response engagement. Finally, energy trading among the TVPP is shown to further reduce the costs of the TVPP and power imported from the upstream electrical network.

Santos, Sérgio F.

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