Optimal Bidding Strategy Considering Bilevel Approach and Multistage Process for a Renewable Energy Portfolio Manager Managing RESs With ESS


Cicek A., ERDİNÇ O.

IEEE SYSTEMS JOURNAL, cilt.16, sa.4, ss.6062-6073, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 4
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1109/jsyst.2021.3131138
  • Dergi Adı: IEEE SYSTEMS JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Sayfa Sayıları: ss.6062-6073
  • Anahtar Kelimeler: Optimization, Uncertainty, Portfolios, Renewable energy sources, Stochastic processes, Electricity supply industry, Contracts, Bilevel optimization, energy storage systems (ESSs), multistage process, optimal electricity market parti-cipation, renewable energy portfolio manager (REPM), WIND FARMS, OPERATION, UNCERTAINTY, SYSTEMS, MARKETS
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

This article presents a bilevel and multistage framework in which a renewable energy portfolio manager (REPM) manages renewable energy sources (RESs) integrated with an energy storage system (ESS) to reduce imbalances and joins in the day-ahead market and the balancing market, including bilateral contracts. The total REPM gain is maximized in the upper level, whereas the loss of income of each portfolio participant in the lower level is minimized taking into account the specified income value. In the multistage structure, different decisions are taken regarding energy trade according to the hours of the day. Generations and price uncertainties that need to be addressed in optimum bidding problems are eliminated with a stochastic approach. Besides, risk management is evaluated through the conditional value-at-risk method. Besides, the test is carried out using real data from Spain in order to verify the effectiveness of the proposed model. According to the results obtained from the study, it can be stated that RESs with ESS increase the portfolio profit by 2%, and even in the case of expected generation, it is 4.1%, by better managing the energy imbalance of participants.