Capturing Electricity Market Dynamics in Strategic Market Participation Using Neural Network Constrained Optimization
Author:
Affiliation:
1. University of Leuven, Divison of Applied Mechanics and Energy Conversion, Leuven, Belgium
2. Power Electrical Engineering, Polytechnic Faculty of University of Mons, Mons, Belgium
Funder
Strategic Basic Research
Research FoundationFlanders
University of Leuven's C2 Research Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology
Link
http://xplorestaging.ieee.org/ielx7/59/10375287/10037231.pdf?arnumber=10037231
Reference46 articles.
1. Market Structure and Equilibrium
2. Investment in Electricity Generation and Transmission
3. Deep Inverse Reinforcement Learning for Objective Function Identification in Bidding Models
4. Incorporating Non-Convex Operating Characteristics Into Bi-Level Optimization Electricity Market Models
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1. Efficient Embedding of Neural Network-Based Stability Constraints Into Power System Dispatch;IEEE Transactions on Power Systems;2024-05
2. Capturing Demand Response Dynamics in Market Equilibrium Using Mean-Field Theory;2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2);2023-12-15
3. Impacts of previous revenues on bidding strategies in electricity market: A quantitative analysis;Applied Energy;2023-09
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