Santos, Sérgio F.
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Santos
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Sérgio F.
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Santos, Sérgio F.
Biografia
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.
Identificadores
E41A-D6C6-E3D7
56483358000
GNM-6353-2022Projetos de investigação
Unidades organizacionais
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.
26 resultados
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Publicação Acesso Restrito Two-stage optimal operation of smart homes participating in competitive electricity markets2021-11-03 - 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.Publicação Acesso Aberto Providing flexibility in distribution systems by electric vehicles and distributed energy resources in the context of technical virtual power plants2021-11-03 - 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.Publicação Acesso Aberto Optimal stochastic conditional value at risk-based management of a demand response aggregator considering load uncertainty2021-11-03 - 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.Publicação Acesso Aberto Influence of battery energy storage systems on transmission grid operation with a significant share of variable renewable energy sources2022-03 - 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.Publicação Acesso Aberto Opportunistic info-gap approach for optimization of electrical and heating loads in multi-energy systems in the presence of a demand response program2021-11-03 - Vahid-Ghavidel, Morteza; Javadi, Mohammad S.; Santos, Sérgio F.; Gough, Matthew; Shafie-khah, Miadreza; Catalão, João P. S.; Santos, Sérgio F.There are significant changes occurring both in the electricity system and the natural gas system. These two energy carries can be combined to form what is known as an energy hub. These energy hubs can play a significant role in the energy system and thus understanding of their optimization, especially their costs, is important. This paper proposes a risk management framework for an energy-hub through the utilization of the information-gap decision theory (IGDT). The uncertainties introduced from the various load profiles, such as the electric and heating loads, are considered in this risk management framework. The modeled energy-hub consists of several distributed generation systems such as a micro-combined heat and power (μCHP), electric heat pump (EHP), electric heater (EH), absorption chiller (AC) and an energy storage system (ESS). A demand response (DR) program is also considered to shift a percentage of electric load away from the peak period to minimize the operational cost of the hub. A feasible test system is also applied to demonstrate the proposed model’s effectiveness.Publicação Acesso Aberto Dynamic distribution system reconfiguration considering distributed renewable energy sources and energy storage systems2022-09 - Santos, Sérgio F.; Gough, Matthew; Fitiwi, Desta Z.; Pogeira, José; Shafie-khah, Miadreza; Catalão, João P. S.; Santos, Sérgio F.Electric power systems are in state of transition as they attempt to evolve to meet new challenges provided by growing environmental concerns, increases in the penetration of distributed renewable energy sources (DRES) as well as the challenges associated with integrating new technologies to enable smart grids. New techniques to improve the electrical power system, including the distribution system, are thus needed. One such technique is dynamic distribution system reconfiguration (DNSR), which involves altering the network topology during operation, providing significant benefits regarding the increased integration of DRES. This paper lays out an improved model which aimed to optimize the system operation in a coordinated way, where DRES, energy storage systems (ESS) and DNSR are considered as well as the uncertainty of these resources. The objective function was modeled to incentivize the uptake of DRES by considering the cost of emissions to incentivize the decarbonization of the power system. Also, the switching costs were modeled to consider not only the switching, but also the cost of degradation of these mechanisms in the system operation. Two systems are used to validate the model, the IEEE 119-bus system, and a real system in São Miguel Island. The results of this paper show that using DNSR, DRES, and ESS can lead to a significant 59% reduction in energy demand through a 24-hour period. In addition, using these technologies results in a healthier, more efficient, and higher quality system. This shows the benefits of using a variety of smart grid technologies in a coordinated manner.Publicação Acesso Aberto Bi-level stochastic energy trading model for technical virtual power plants considering various renewable energy sources, energy storage systems and electric vehicles2023-09-15 - 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.Publicação Acesso Aberto Energy storage system impact on the operation of a demand response aggregator2023-08-01 - Vahid-Ghavidel, Morteza; Javadi, M.S.; Santos, Sérgio F.; Gough, M.; Shafie-khah, M.; Catalão, J.P.S.; Santos, Sérgio F.In this paper, we consider a demand response (DR) aggregator responsible for participating in the wholesale electricity market on behalf of the end-users who participated in the DR programs. Thus, the DR aggregator can trade its acquired DR within the short-term electricity markets, i.e., the day-ahead and the balancing (real-time) markets. In the proposed framework, the electricity market prices are considered uncertain, and a robust optimization approach is applied to address the uncertainties to maximize the profit of the DR aggregator. A model for analyzing the impact of the energy storage system (ESS) unit on a DR aggregator's performance is developed to provide more flexibility for the consumers. The direct interactions of a DR aggregator with an ESS are neglected in many models. However, this consideration can lead to improvement in the flexibility of the aggregator and also increase the profit of the entity by trading energy in the short-term markets to charge the ESS during the low-price periods and discharge it to the market while the electricity market prices are high. Hence, it is assumed that the DR aggregator owns an ESS unit and can cover a percentage of its traded power through the ESS. An analysis of the impact of the ESS unit on the DR aggregator's performance is applied to study the most appropriate size of the ESS that can maximize the profit of the aggregator. In addition, renewable energy production is employed for end-users through the installation of rooftop photovoltaic (PV) panels. This demand-side renewable generation can provide more flexibility for the participants in DR programs. Various feasible case studies have been applied to demonstrate the model's effectiveness and usefulness, and conclusions are duly drawn. The numerical results indicate that having an ESS seems necessary when the decision-maker desires to protect its profit from the worst-case scenarios and reduces the negative effect of the uncertain parameter, i.e., the wholesale electricity market prices. Thus, it can be shown that having a greater capacity for the ESS has a significant and direct impact on increasing the profit of the aggregator even in the worst-case scenarios, where the profit rises 20 % when the budget of uncertainty in the robust optimization is equal to 12.Publicação Acesso Aberto Pool trading model within a local energy community considering flexible loads, photovoltaic generation and energy storage systems2022-04 - Javadi, Mohammad Sadegh; Gough, Matthew; Nezhad, Ali Esmaeel; Santos, Sérgio F.; Shafie-khah, Miadreza; Catalão, Joao P. S.; Santos, Sérgio F.This paper presents a pool trading model within a local energy community considering home energy management systems (HEMSs) and other consumers. A transparent mechanism for market clearing is proposed to incentivise active prosumers to trade their surplus energy within a rule-based pool market in the local energy community. A price-based demand response program (PBDRP) is considered to increase the consumers’ willingness to modify their consumption. The mathematical optimization problem is a standard mixed-integer linear programming (MILP) problem to allow for rapid assessment of the trading market for real energy communities which have a considerable number of consumers. This allows for novel energy trading strategies amongst different clients in the model and for the integration of a pool energy trading model at the level of the local energy community. The objective function of the energy community is to minimize the overall bills of all participants while fulfilling their demands. Two different scenarios have been evaluated, independent and integrated operation modes, to show the impacts of coordination amongst different end-users. Results show that through cooperation, end-users in the local energy community market can reduce the total electricity bill. This is shown in a 16.63% cost reduction in the independent operation and a 21.38% reduction in the integrated case. Revenues for active consumers under coordination increased compared to independent operation of the HEMS.Publicação Acesso Restrito Blockchain-based transactive energy framework for connected virtual power plants2022-01 - 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
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