Dispatch of Distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Faria, P (Author) Other; Soares, T (Author) Other; Pinto, T (Author) Other; Sousa, TM (Author) Other; Soares, J (Author) Other; Zita Vale (Author) Other; Morais, H (Author) Other

Conference proceedings International

Title: 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE APPLICATIONS IN SMART GRID (CIASG)

Pages: 51-58

IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)

Singapore, SINGAPORE, APR 16-19, 2013

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-008-JFK

DOI: 10.1109/ciasg.2013.6611498

Abstract (EN): The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8