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The energy sector, as many, is being adapted to meet environmental concerns and avoid fossil fuels. So, Smart Grids concept is promoted, penetrating Distributed Generation into the grid, namely renewable-based energy, providing an environmentally friendly alternative. Also, the consumers’ role is empowered through Demand Response (DR). The consumers are incentivized to actively modify their consumption behavior receiving the proper remuneration. With this, the power system will decrease operation costs and DR can be used as an alternative to generation. However, manage these new and active resources as well as their transactions in the energy market is a complex task due to the uncertainty associated. Many factors can cause a non-response and the Aggregator must be able to manage these situations mainly when a certain target of reduction is required from the wholesale market. The authors proposed an approach including a Trustworthy Rank to select consumers for on DR events: consumers participate considering their reliability. In the present paper, the effects of the approach will be compared between two seasons, proving the viability on giving the correct information to the community manager and understanding how variable is the behavior of this rank at different times of the year.
Cátia Silva; Pedro Faria; Zita Vale. Rating consumers participation in demand response programs according to previous events. Energy Reports 2020, 6, 195 -200.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Rating consumers participation in demand response programs according to previous events. Energy Reports. 2020; 6 ():195-200.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2020. "Rating consumers participation in demand response programs according to previous events." Energy Reports 6, no. : 195-200.
Aggregation of small size consumers and Distributed Generation (DG) units have a considerable impact to catch the full flexibility potential, in the context of Demand Response programs. New incentive mechanisms are needed to remunerate consumers adequately and to recognize the ones that have more reliable participation. The authors propose an innovative approach to be used in the operation phase, to deal with the uncertainty to Demand Response events, where a certain target is requested for an energy community managed by the Aggregator. The innovative content deals with assigning and updating a Reliability Rate to each consumer according to the actual response in a reduction request. Three distinct methods have been implemented and compared. The initial rates assigned according to participation in the Demand Response events after one month of the enrolment period and the ones with higher reliability follow scheduling, performed using linear optimization. The results prove that using the proposed approach, the energy community manager finds the more reliable consumers in each period, and the reduction target achieved in DR events. A clustering algorithm is implemented to determine the final consumer rate for one month considering the centroid value.
Cátia Silva; Pedro Faria; Zita Vale. Rating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Period. Electronics 2020, 9, 349 .
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Rating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Period. Electronics. 2020; 9 (2):349.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2020. "Rating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Period." Electronics 9, no. 2: 349.
The current Energy Market is not yet ready for the integration of the Smart Grid context. Concepts such as Demand Response and Distributed Generation, namely renewable energy resources, are not yet included in current business models in order to the system flow properly. Therefore, the authors propose a methodology that gathers all these concepts through the optimization, aggregation and remuneration of resources. The purpose of this paper will be to study the influence of the tariff used for the remuneration and incentive of the participants in the formation of the groups in the aggregation phase. Three studies were performed: aggregation with only the result of the optimization (schedule power for each resource); this result and the fixed tariff associated with each resource; result and a new tariff that considers real-time values.
Cátia Silva; Pedro Faria; Zita Vale. Combining real-time and fixed tariffs in the demand response aggregation and remuneration. Energy Reports 2020, 6, 114 -119.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Combining real-time and fixed tariffs in the demand response aggregation and remuneration. Energy Reports. 2020; 6 ():114-119.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2020. "Combining real-time and fixed tariffs in the demand response aggregation and remuneration." Energy Reports 6, no. : 114-119.
Local energy communities with information from the real-time market may improve the market operation but also increase the complexity of the management problem thanks to the uncertainty associated with the actual response of these resources. For instance, consumers with price knowledge may change their power consumption to lower-cost periods. The authors present a model to deal with uncertainty from the Aggregator perspective: apply reliability rates to each consumer according to their actual response in events of Demand Response (DR). The consumers with higher rates are chosen to participate in the local flexibility markets. To compute the final rate, three different independent rates are used: Historical rate with past information, Cut-rate from the response in the actual period and the Last Day Rate which is the final reliability rate from the previous day. In the present paper, the influence of each independent rate, through the weight used, is studied.
Cátia Silva; Pedro Faria; Zita Vale. A Consumer Trustworthiness Rate for Participation in Demand Response Programs. IFAC-PapersOnLine 2020, 53, 12596 -12601.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. A Consumer Trustworthiness Rate for Participation in Demand Response Programs. IFAC-PapersOnLine. 2020; 53 (2):12596-12601.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2020. "A Consumer Trustworthiness Rate for Participation in Demand Response Programs." IFAC-PapersOnLine 53, no. 2: 12596-12601.
The demand response program explained in this article is designed to be implemented in communities seeking to achieve a self-sustaining system, namely through renewable energy such as photovoltaic energy. This article, through concepts such as prosumer and clustering, aims to make the most efficient management of the resources provided by the energy community. The developed demand response clusters the different consumers who have the same type of consumption throughout the day. That is, it brings together those whose behavior of the respective loads resemble each other and can be viewed from the perspective of an individual load or even clustered with one or more loads. The study comprises three villages with different numbers of consumers and charges, where, through their participation, it is estimated that there are reductions in electricity bills and, for those who collaborated for the study, it is attributed a remuneration according to their performance.
Rúben Barreto; Pedro Faria; Cátia Silva; Zita Vale. Clustering Direct Load Control Appliances in the Context of Demand Response Programs in Energy Communities. IFAC-PapersOnLine 2020, 53, 12608 -12613.
AMA StyleRúben Barreto, Pedro Faria, Cátia Silva, Zita Vale. Clustering Direct Load Control Appliances in the Context of Demand Response Programs in Energy Communities. IFAC-PapersOnLine. 2020; 53 (2):12608-12613.
Chicago/Turabian StyleRúben Barreto; Pedro Faria; Cátia Silva; Zita Vale. 2020. "Clustering Direct Load Control Appliances in the Context of Demand Response Programs in Energy Communities." IFAC-PapersOnLine 53, no. 2: 12608-12613.
Nowadays, the data can be considered an asset when properly managed. An entity with the right tool to analyse the amount of data existent and withdraw crucial information will have the power to obliterate the competition. In the Energy sector, with Smart Grid introduction, small resources have more influence in the market through Demand Response and bidirectional communication. However, none of the actual business models is prepared to deal with the uncertainty related to these resources. The authors, in order to find a solution for this complex problem, proposed a methodology which the goal is to minimize operation costs and give fair compensation for resources who participate in the management of local markets. With this fair payment, it is expected continuous participation. Through clustering methods, remuneration groups are created. In the present paper, a study about the optimal number of clusters is performed. The information gives the Aggregator control in results of the following phases, understanding the impact in the remuneration of the resources.
Cátia Silva; Pedro Faria; Zita Vale. Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods. 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP) 2019, 1 -6.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods. 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP). 2019; ():1-6.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2019. "Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods." 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP) , no. : 1-6.
Giving the small resources more information about the transactions in the market will have a great influence on the balance and increase the uncertainty. Business models that are prepared to deal with small consumers and/or with small Distributed Generation units need to emerge to deal with this problem. The authors present a methodology able to minimize the operation costs for the Aggregator of these small resources but also find a fair remuneration according to their participation in the management of the local grid. The methodology could be explored by two approaches depending on time horizon: planning or operation. In the present paper, the two will be compared showing the viability of the path selected by the authors for the real-time approach - assign a remuneration group to a consumer considering the actual participation and the rules provided by a classification method.
Cátia Silva; Pedro Faria; Zita Vale. Real-Time Approach for Demand Response Tariffs Definition Using Decision Trees. 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP) 2019, 1 -6.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Real-Time Approach for Demand Response Tariffs Definition Using Decision Trees. 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP). 2019; ():1-6.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2019. "Real-Time Approach for Demand Response Tariffs Definition Using Decision Trees." 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP) , no. : 1-6.
Bruno Canizes; João Soares; Fernando Lezama; Cátia Silva; Zita Vale; Juan Manuel Corchado. Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation. Renewable Energy 2019, 138, 937 -954.
AMA StyleBruno Canizes, João Soares, Fernando Lezama, Cátia Silva, Zita Vale, Juan Manuel Corchado. Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation. Renewable Energy. 2019; 138 ():937-954.
Chicago/Turabian StyleBruno Canizes; João Soares; Fernando Lezama; Cátia Silva; Zita Vale; Juan Manuel Corchado. 2019. "Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation." Renewable Energy 138, no. : 937-954.
The need for new business models to replace existing ones, soon obsolete, is a subject often discussed among researchers in the area. It is essential to find a practical solution that includes the concepts of demand response and distributed generation in the energy markets, these being the future of the electricity grid. It is believed that these resources can bring advantages to the operation of the system, namely increasing technical efficiency. However, one of the problems is the aggregation of small resources as a result of the associated uncertainties. The authors propose a business model with three main phases used in planning: optimal scheduling, aggregation, and remuneration. In this paper, a new phase was added, the classification, with the main purpose of assisting the aggregator of these small resources in operating situations. The focus is on the fair remuneration of participants in the management of the market, in addition to minimizing operating costs. After testing four different remuneration methods, it was proved that the method proposed by the authors obtained better results, proving the viability of the proposed model.
Cátia Silva; Pedro Faria; Zita Vale. Demand Response and Distributed Generation Remuneration Approach Considering Planning and Operation Stages. Energies 2019, 12, 2721 .
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Demand Response and Distributed Generation Remuneration Approach Considering Planning and Operation Stages. Energies. 2019; 12 (14):2721.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2019. "Demand Response and Distributed Generation Remuneration Approach Considering Planning and Operation Stages." Energies 12, no. 14: 2721.
The energy market, with the introduction of the smart grids concept, opens the door to small distributed energy resources. However, these resources introduce an added level of difficulty to market management, requiring an entity to aggregate and manage them optimally. This paper proposes an approach that integrates these small resources. The methodology is composed of optimal scheduling, aggregation and remuneration based on aggregation. The method chosen for aggregation is k-means. In relation to previous works, the innovation goes through the multi-period and the comparison that this can have in the formation of groups. Thus, three scenarios were created: Whole Week, Work Days and Weekend. Profiles were added for 548 units of DG. The justification for the formation of groups will be a fairer remuneration and according to the contribution of each resource to the management of the network.
Cátia Silva; Pedro Faria; Zita Vale. Study of Multi-Tariff Influence on the Distributed Generation Remuneration. Advances in Intelligent Systems and Computing 2019, 14 -19.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Study of Multi-Tariff Influence on the Distributed Generation Remuneration. Advances in Intelligent Systems and Computing. 2019; ():14-19.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2019. "Study of Multi-Tariff Influence on the Distributed Generation Remuneration." Advances in Intelligent Systems and Computing , no. : 14-19.
The electric sector revolution towards Smart Grids, requires new market models. The authors propose a business model that allows the virtual power player to manage the small resources like distributed generation units, consumers belonging to demand response programs, and prosumers. Grouping these resources and remunerating them according to the maximum tariff of the group that was allocated is proposed. The purpose of this paper is to understand whether the tariff associated with each resource influences or not the formation of groups when applying the clustering method. Three case studies were carried out: aggregation only with the potential of each resource, power and the fixed tariff and, finally, taking into account a tariff that changes according to the period of the day.
Catia Silva; Pedro Faria; Zita Vale. Influence of Combining Real-time and Fixed Tariffs in the Demand Response Aggregation and Remuneration Scheems Definition. 2019 IEEE Milan PowerTech 2019, 1 -6.
AMA StyleCatia Silva, Pedro Faria, Zita Vale. Influence of Combining Real-time and Fixed Tariffs in the Demand Response Aggregation and Remuneration Scheems Definition. 2019 IEEE Milan PowerTech. 2019; ():1-6.
Chicago/Turabian StyleCatia Silva; Pedro Faria; Zita Vale. 2019. "Influence of Combining Real-time and Fixed Tariffs in the Demand Response Aggregation and Remuneration Scheems Definition." 2019 IEEE Milan PowerTech , no. : 1-6.
Distributed energy resources can improve the operation of power systems, improving economic and technical efficiency. Aggregation of small size resources, which exist in large number but with low individual capacity, is needed to make these resources’ use more efficient. In the present paper, a methodology for distributed resources management by an aggregator is proposed, which includes the resources scheduling, aggregation and remuneration. The aggregation, made using a k-means algorithm, is applied to different approaches concerning the definition of tariffs for the period of a week. Different consumer types are remunerated according to time-of-use tariffs existing in Portugal. Resources aggregation and remuneration profiles are obtained for over 20.000 consumers and 500 distributed generation units. The main goal of this paper is to understand how the aggregation phase, or the way that is performed, influences the final remuneration of the resources associated with Virtual Power Player (VPP). In order to fulfill the proposed objective, the authors carried out studies for different time frames (week days, week-end, whole week) and also analyzed the effect of the formation of the remuneration tariff by considering a mix of fixed and indexed tariff. The optimum number of clusters is calculated in order to determine the best number of DR programs to be implemented by the VPP.
Cátia Silva; Pedro Faria; Zita Vale. Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response. Energies 2019, 12, 1248 .
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response. Energies. 2019; 12 (7):1248.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2019. "Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response." Energies 12, no. 7: 1248.
The future of the industry foresees the automation and allocation of more intelligence to processes. A revolution in relation to the present. With this, new challenges and consequently more complexity is added to the management of the sectors. In the electric sector is introduced the theme of the Smart grids and so all the concepts aggregated with it. The possibility of the existence of demand response programs and the expansion of the distributed generation units for small players are key concepts and with enormous influence in the management of the markets belonging to this sector. Thus, a method is proposed that would help manage these resources through their aggregation, opening a new port for business models based on this idea. The benefit will be to take advantage of a more effective and efficient way the energy potential present in each group that is formed. Thus, in this paper will be explored the potential of clustering methods for the aggregation of resources.
Cátia Silva; Pedro Faria; Zita Vale. Clustering Support for an Aggregator in a Smart Grid Context. Advances in Intelligent Systems and Computing 2019, 156 -165.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Clustering Support for an Aggregator in a Smart Grid Context. Advances in Intelligent Systems and Computing. 2019; ():156-165.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2019. "Clustering Support for an Aggregator in a Smart Grid Context." Advances in Intelligent Systems and Computing , no. : 156-165.
With the introduction of the Smart Grid context in the current network, it will be necessary to improve business models to include the use of distributed generation and demand response programs regarding the remuneration of participants as a form of incentive. Throughout this article a methodology is presented which will aggregate generation units and consumers participating in DR programs. A comparison of clustering methods will be carried out in order to understand which one of them will be the most appropriate for the scenario studied. After grouping all the resources, the remuneration of the groups are made considering the maximum rate in each group. The hierarchical clustering proved to be the most appropriate because it grouped the resources so that the total cost for the aggregator was the minimum.
Cátia Silva; Pedro Faria; Zita Vale. Discussing Different Clustering Methods for the Aggregation of Demand Response and Distributed Generation. 2018 IEEE Symposium Series on Computational Intelligence (SSCI) 2018, 1645 -1650.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Discussing Different Clustering Methods for the Aggregation of Demand Response and Distributed Generation. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). 2018; ():1645-1650.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2018. "Discussing Different Clustering Methods for the Aggregation of Demand Response and Distributed Generation." 2018 IEEE Symposium Series on Computational Intelligence (SSCI) , no. : 1645-1650.
There are currently efforts to implement the concept of smart grids throughout the electric sector. This will bring radical changes to the entire management of the sector. The energy market does not run away from the rule. In this way, virtual power players will be required to update their business models to introduce all the concepts that the context of smart grids imposes. Thus, in this article is proposed a method that aggregates distributed generation and consumers who belong to demand response programs. Optimized scheduling, resource aggregation and classification of possible new resources, rescheduling, and remuneration are the phases of the methodology proposed and presented in this article. The focus will be on classification phase and the main objective is to create rules, through a previously trained model, to be able to classify the new resources and help with the challenges that virtual power players may face. Thus, five classification methods were tested and compared: neural networks, Bayesian naïve classification, decision trees, k-nearest neighbor method, and lastly support vector machine method.
Cátia Silva; Pedro Faria; Zita Vale. Distributed Generation with Improved Remuneration. 2018 IEEE Symposium Series on Computational Intelligence (SSCI) 2018, 1639 -1644.
AMA StyleCátia Silva, Pedro Faria, Zita Vale. Distributed Generation with Improved Remuneration. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). 2018; ():1639-1644.
Chicago/Turabian StyleCátia Silva; Pedro Faria; Zita Vale. 2018. "Distributed Generation with Improved Remuneration." 2018 IEEE Symposium Series on Computational Intelligence (SSCI) , no. : 1639-1644.
The stakeholders that belong to the energy market will have to adapt to the changes that the implementation of the concept of Smart Grid imposes. This concept requires new business models that include the demand response programs, the use of distributed generation and especially the remuneration that will be made for their contribution. The exposed methodology can be presented as a solution for virtual power players in this new challenge. Throughout this article, this methodology was tested regarding the remuneration of aggregate groups of distributed generation. It will also be analyzed the meaning of this tariff for both sides - aggregator and producers.
Catia Silva; Pedro Faria; Zita Vale. Assessment of Distributed Generation Units Remuneration Using Different Clustering Methods for Aggregation. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) 2018, 1 -6.
AMA StyleCatia Silva, Pedro Faria, Zita Vale. Assessment of Distributed Generation Units Remuneration Using Different Clustering Methods for Aggregation. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). 2018; ():1-6.
Chicago/Turabian StyleCatia Silva; Pedro Faria; Zita Vale. 2018. "Assessment of Distributed Generation Units Remuneration Using Different Clustering Methods for Aggregation." 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) , no. : 1-6.
The electricity sector is fast moving towards a new era of clean generation devices dispersed along the network. On one hand, this will largely contribute to achieve the multi-national environment goals agreed via political means. On the other hand, network operators face new complexities and challenges regarding network planning due to the large uncertainties associated with renewable generation and electric vehicles integration. In addition, due to new technologies such as combined heat and power (CHP), the district heat demand is considered in the long-term planning problem. The 13-bus medium voltage network is evaluated considering the possibility of CHP units but also without. Results demonstrate that CHP, together with heat-only boiler units, can supply the district heat demand and contribute to network reliability. They can also reduce the expected energy not supplied and the power losses cost, avoiding the need to invest in new power lines for the considered lifetime project.
Bruno Canizes; João Soares; Mohammad Ali Fotouhi Ghazvini; Cátia Silva; Zita Vale; Juan M. Corchado. Long-Term Smart Grid Planning Under Uncertainty Considering Reliability Indexes. Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs 2018, 297 -335.
AMA StyleBruno Canizes, João Soares, Mohammad Ali Fotouhi Ghazvini, Cátia Silva, Zita Vale, Juan M. Corchado. Long-Term Smart Grid Planning Under Uncertainty Considering Reliability Indexes. Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs. 2018; ():297-335.
Chicago/Turabian StyleBruno Canizes; João Soares; Mohammad Ali Fotouhi Ghazvini; Cátia Silva; Zita Vale; Juan M. Corchado. 2018. "Long-Term Smart Grid Planning Under Uncertainty Considering Reliability Indexes." Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs , no. : 297-335.