A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Energy Resource Scheduling with Multiple Iterations for the Validation of Demand Response Aggregation
Flexibility aggregators are becoming a trend in European energy markets, joining several consumers and small-size distributed generators to their portfolio, enabling market participation. Also, the interest growth in clean energy resources and in smart grid concepts such as demand response and communication infrastructures, has led to a facilitation in the integration of these flexibility resources. In this paper, it is proposed a methodology that supports the aggregator in its energy management and resources scheduling. The work focuses on a rescheduling method that uses aggregation and remuneration processes to define new tariffs for consumers participating in a load curtailment demand response program. Aggregation is performed using the clustering algorithm, k-means, while the remuneration process defines a tariff per group formed by computing the arithmetic average of the consumer's prices belonging to each group. ; This work has been developed under the EUREKA - ITEA2 Project FUSE-IT (ITEA-13023), Project GREEDI (ANI|P2020 17822), and has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013
Energy Resource Scheduling with Multiple Iterations for the Validation of Demand Response Aggregation
Flexibility aggregators are becoming a trend in European energy markets, joining several consumers and small-size distributed generators to their portfolio, enabling market participation. Also, the interest growth in clean energy resources and in smart grid concepts such as demand response and communication infrastructures, has led to a facilitation in the integration of these flexibility resources. In this paper, it is proposed a methodology that supports the aggregator in its energy management and resources scheduling. The work focuses on a rescheduling method that uses aggregation and remuneration processes to define new tariffs for consumers participating in a load curtailment demand response program. Aggregation is performed using the clustering algorithm, k-means, while the remuneration process defines a tariff per group formed by computing the arithmetic average of the consumer's prices belonging to each group. ; This work has been developed under the EUREKA - ITEA2 Project FUSE-IT (ITEA-13023), Project GREEDI (ANI|P2020 17822), and has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013
Energy Resource Scheduling with Multiple Iterations for the Validation of Demand Response Aggregation
João Spinola (author) / Pedro Faria (author) / Zita Vale (author)
2018-08-23
Conference paper
Electronic Resource
English
DDC:
690
| BASE | 2018
| BASE | 2018
Distributed Energy Resource Scheduling with Focus on Demand Response Complex Contracts
| DOAJ | 2021
Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
| BASE | 2018
Scheduling of Battery Energy Storage and Demand Response Resource in Balancing Ancillary Service
| BASE | 2020