Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs

The use of distributed generation and demand-response (DR) programs is needed for improving business models, namely concerning the remuneration of these resources in the context of smart grids. In this paper, a methodology is proposed in which a virtual power player aggregates several small-sized resources, including consumers participating in DR programs. The global operation costs resulting from the resource scheduling are minimized. After scheduling the resources in several operation scenarios, clustering tools are applied in order to obtain distinct resources’ groups. The remuneration structure that better fits the aggregator goals is then determined. Two clustering algorithms are compared: 1) hierarchical; nd 2) fuzzy c-means clustering. The remuneration of small resources and consumers that are aggregated is made considering the maximum tariff in each group. The implemented case study considers 2592 operation scenarios based on a real Portuguese distribution network with 548 distributed generators and 20 310 consumers.info:eu-repo/semantics/publishedVersio

Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs

This article belongs to the Special Issue Distributed Energy Resources Management 2018Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K-means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliersThis work has received funding from the following projects: SIMOCE Project (ANI | P2020); and from FEDER Funds through the COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. This work was also supported by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement 641794–DREAM-GO Project.info:eu-repo/semantics/publishedVersio

Application of distinct demand response program during the ramping and sustained response period

The environmental concerns around energy, namely electricity, have driven attention to innovative approaches to fostering consumers participation in the whole energy system management. Accordingly, the concept of demand response provides incentives and signals no consumers to change the normal consumption patterns to increase the use of renewables, for example. The problem is that such response of consumers has a large amount of uncertainty. This paper proposes a methodology in which different demand response programs are activated and deactivated during an event to cover the demand response deviations from the target. Even after achieving the response target, if the actual response of consumers is reduced to a critical level, additional programs are activated. The proposed approach considers consumers participating in an aggregate way, supported by an aggregator. The case study in this paper accommodates three demand response programs, showing how different consumers are activated and remunerated for the provision of consumption reduction. It has been seen that the proposed methodology is flexible as desired to accommodate the uncertainty of consumers’ responses.This work has received funding from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project COLORS (PTDC/EEI-EEE/28967/2017). The work has been done also in the scope of projects UIDB/00760/2020, and CEECIND/02887/2017, financed by FEDER Funds through COMPETE program and from National Funds through (FCT) . The authors would like to acknowledge the contribution of Omid Abrishambaf to this workinfo:eu-repo/semantics/publishedVersio

An Aggregation Model for Energy Resources Management and Market Negotiations

Currently the use of distributed energy resources, especially renewable generation, and demand response programs are widely discussed in scientific contexts, since they are a reality in nowadays electricity markets and distribution networks. In order to benefit from these concepts, an efficient energy management system is needed to prevent energy wasting and increase profits. In this paper, an optimization based aggregation model is presented for distributed energy resources and demand response program management. This aggregation model allows different types of customers to participate in electricity market through several tariffs based demand response programs. The optimization algorithm is a mixed-integer linear problem, which focuses on minimizing operational costs of the aggregator. Moreover, the aggregation process has been done via K-Means clustering algorithm, which obtains the aggregated costs and energy of resources for remuneration. By this way, the aggregator is aware of energy available and minimum selling price in order to participate in the market with profit. A realistic low voltage distribution network has been proposed as a case study in order to test and validate the proposed methodology. This distribution network consists of 25 distributed generation units, including photovoltaic, wind and biomass generation, and 20 consumers, including residential, commercial, and industrial buildings.This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO). This work also received funding from the following projects: NETEFFICITY Project (ANI | P2020 – 18015); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.info:eu-repo/semantics/publishedVersio

Discussing Different Clustering Methods for the Aggregation of Demand Response and Distributed Generation

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.The present work was done and funded in the scope of the following projects: CONTEST Project (P2020-23575), and UID/EEA/00760/2013 funded by FEDER Funds through, COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response

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 VPPThe present work was done and funded in the scope of Project GREEDI (ANI|P2020-17822) co-funded by Portugal 2020 "Fundo Europeu de Desenvolvimento Regional" (FEDER) through POCI, and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Definition of Remuneration in an Aggregator Using Clustering Algorithms

Currently, the use of demand response programs and renewable energy resource are a reality in the power distribution network. Therefore, an efficient and optimal energy resource management is required for fully benefit from these new concepts of power system as well as avoiding energy wasting. In this paper, a methodologyis represented in order to support the aggregator activities, with the aim of participation in the electricity market negotiations using aggregated distributed energy resources and demand response programs. Moreover, the presented model demonstrates the benefits of aggregator participation while promoting their inclusion. Additionally, a case study will test and validate the proposed methodology, which considers a university campus distribution network as aggregator network including 20 consumers and 26 renewable producers.This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO) and from FEDER Funds through COMPETE program and from National Funds through FCT, under the project UID/EEA/00760/2013.N/

Definition of Remuneration in an Aggregator Using Clustering Algorithms

Currently, the use of demand response programs and renewable energy resource are a reality in the power distribution network. Therefore, an efficient and optimal energy resource management is required for fully benefit from these new concepts of power system as well as avoiding energy wasting. In this paper, a methodology is represented in order to support the aggregator activities, with the aim of participation in the electricity market negotiations using aggregated distributed energy resources and demand response programs. Moreover, the presented model demonstrates the benefits of aggregator participation while promoting their inclusion. Additionally, a case study will test and validate the proposed methodology, which considers a university campus distribution network as aggregator network including 20 consumers and 26 renewable producers

Combining real-time and fixed tariffs in the demand response aggregation and remuneration

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.The present work was done and funded in the scope of the following projects: European Union's Horizon 2020 project DOMINOES (grant agreement No 771066), and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Demand Response and Distributed Generation Remuneration Approach Considering Planning and Operation Stages

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.The present work was done and funded in the scope of the following projects: European Union's Horizon 2020 project DOMINOES (grant agreement No 771066), and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio