  In face of the pressing need of decarbonization in the power sector, the
re-design of electricity market is necessary as a Marco-level approach to
accommodate the high penetration of renewable generations, and to achieve power
system operation security, economic efficiency, and environmental friendliness.
However, existing market design methodologies suffer from the lack of
coordination among energy spot market (ESM), ancillary service market (ASM) and
financial market (FM), i.e., the "joint market", and the lack of reliable
simulation-based verification. To tackle these deficiencies, this two-part
paper develops a paradigmatic theory and detailed methods of the joint market
design using reinforcement-learning (RL)-based simulation. In Part 1, the
theory and framework of this novel market design philosophy are proposed.
First, the controversial market design options while designing the joint market
are summarized as the targeted research questions. Second, the Markov game
model is developed to describe the bidding game in the joint market,
incorporating the market design options to be determined. Third, a framework of
deploying multiple types of RL algorithms to simulate the market model is
developed. Finally, several market operation performance indicators are
proposed to validate the market design based on the simulation results.
