Electricity Markets
Market design, cross-border mechanisms, short-term market behavior, price formation, and the rules that shape decisions.
Personal site
Building decision systems for electricity markets and energy assets
I work at the boundary of power-market research, market practice, and AI systems for energy operations. This site is my public layer for essays, research, publications, media links, and collaboration.
Research trainingTU Delft PhD
Market practiceFormer European power-market quantitative trader
Decision systemsFounder and operator
Public researchAdjunct researcher at Tsinghua EE Dept
Focus
What I work on
Energy AI
Forecasting, probabilistic modeling, optimization, reinforcement learning, and safe decision systems for energy operations.
Storage & Flexibility
Battery dispatch, flexibility strategy, and market participation under operational and regulatory constraints.
Research Translation
Turning strong methods into public writing, useful workflows, and decision systems that can be examined.
Current work
The decision layer for market-facing energy assets
Power markets are becoming more operational, more volatile, and more data-driven. Energy assets now need better ways to combine market rules, forecasts, strategy, execution, and risk review.
My work focuses on that decision layer: how market-facing energy assets can reason about prices, constraints, uncertainty, and accountability with support from research methods and AI systems.
Research detailsDecision systems
From market facts to accountable action
The public framing behind my current work: decision agents should help energy teams connect evidence, constraints, decisions, and review instead of only generating analysis.
- 01
Rules
Market design, tariffs, bidding constraints, asset limits, and operational boundaries.
- 02
Forecasts
Prices, uncertainty, renewable output, demand, flexibility, and scenario distributions.
- 03
Strategy
Dispatch logic, participation choices, risk appetite, and portfolio-level priorities.
- 04
Execution
Human-reviewed actions, operating receipts, exceptions, and traceable workflow states.
- 05
Risk control
Policy boundaries, anomaly checks, override paths, and failure-mode awareness.
- 06
Review
Post-event learning, model feedback, decision records, and accountable improvement.
Experience
Public background
The through-line is research training, market practice, AI decision-system building, and public writing.
Founder and operator
Building energy decision workflows and public-facing research translation around market operations.
European power-market practice
Former European power-market quantitative trader, with practical exposure to short-term markets and price behavior.
Research training
TU Delft PhD, with public research across energy systems, AI, optimization, and decision methods.
Academic role
Adjunct researcher at Tsinghua, with public work connected to energy AI and electricity-market decisions.
Selected work
Publications and writing
Representative public research and long-form writing on energy systems, storage, and decision methods.
Publications
RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks
Energy and AI, 2025.
Safe Imitation Learning-based Optimal Energy Storage Systems Dispatch in Distribution Networks
arXiv, 2024.
Contact
Open to public conversations around energy technology, power markets, and AI decision systems.
If your work touches electricity markets, storage, energy AI, speaking, or research translation, email is the cleanest starting point.
Contact Page