Day-ahead optimal operation of active distribution networks with distributed generation and energy storage

Author:

Feroldi Diego12ORCID,Rullo Pablo13

Affiliation:

1. CIFASIS-CONICET-UNR , Rosario , Argentina

2. Department of Computer Sciences , FCEIA-UNR , Rosario , Argentina

3. Centro de Investigación y Transferencia San Nicolás (CONICET – UTN FRSN) , San Nicolás , Argentina

Abstract

Abstract In this work we address the optimal operation in active distribution networks (ADNs) with high penetration of renewable energies and energy storage. The optimal performance of ADNs can include two different optimization problems: Unit Commitment (UC) and Economic Dispatch (ED). The UC problem determines the start-up and shutdown planning of all the dispatchable generation units to supply the electricity demand, minimizing the total cost of operation, while the ED problem determines the active output power of each of the committed units for each hour of the planning horizon. Both problems have the objectives of minimizing the total cost, supplying the demand and complying with the restrictions of the main network. Here the two problems are solved together to achieve the day-ahead optimal operation of active distribution networks with distributed generation and energy storage. A test system based on the IEEE 33-bus distribution network was proposed. The optimal operation problem presented here is analyzed using four scenarios with different renewable generation and load conditions and a time-varying profile for the purchase price of energy from the network. The results reveal that the proposed network together with the optimization methodology can face diverse and highly demanding load situations, with the full use of renewable energies and complying with all the restrictions imposed. The proposed methodology is suitable for use in other optimization problems such as determining the sizing of storage units and distributed generation.

Publisher

Walter de Gruyter GmbH

Subject

Energy Engineering and Power Technology

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