Risk-Averse Optimal Energy and Reserve Scheduling for Virtual Power Plants Incorporating Demand Response Programs

• Type: Article in International Scientific Journal
• Date: 2021

Authors

Mostafa Vahedipour-Dahraie (Author) Other; Homa Rashidizadeh-Kermani (Author) Other; Miadreza Shafie-Khah (Author) Other; João P. S. Catalão (Author) FEUP

Journal

Title: IEEE Transactions on Smart Grid

Vol. 12

Pages: 1405-1415

ISSN: 1949-3053

Publisher: IEEE

Indexing

ISI Web of Knowledge - 57 Citations

Scopus - 74 Citations

Other information

Authenticus ID: P-00T-JA5

DOI: 10.1109/tsg.2020.3026971

Abstract (EN): This article addresses the optimal bidding strategy problem of a virtual power plant (VPP) participating in the day-ahead (DA), real-time (RT) and spinning reserve (SR) markets (SRMs). The VPP comprises a number of dispatchable energy resources (DERs), renewable energy resources (RESs), energy storage systems (ESSs) and a number of customers with flexible demand. A two-stage risk-constrained stochastic problem is formulated for the VPP scheduling, where the uncertainty lies in the energy and reserve prices, RESs production, load consumption, as well as calls for reserve services. Based on this model, the VPP bidding/offering strategy in the DA market (DAM), RT market (RTM) and SRM is decided aiming to maximize the VPP profit considering both supply and demand-sides (DS) capability for providing reserve services. On the other hand, customers participate in demand response (DR) programs by using load curtailment (LC) and load shifting (LS) options as well as by providing reserve service to minimize their consumption costs. The proposed model is implemented on a test VPP and the optimal decisions are investigated in detail through a numerical study. Numerical simulations demonstrate the effectiveness of the proposed scheduling strategy and its operational advantages and the computational effectiveness.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11