Optimal Scheduling of Demand Response Resources In Energy Markets For High Trading Revenue and Low Carbon Emissions

With the high penetration of distributed renewable energy resources on the user side, the main challenge to the safe operation of the superior power system is the gradual increase in insufficient local energy consumption rates.. The local energy trading market is now considered a silver bullet to address this issue. It optimizes the end-users electricity trading revenue and reduce gas emissions while improving the local energy consumption rate. However, the current research on local energy trading systems is inadequate. The uncertain outputs of distributed renewable energy make it difficult to guarantee locally generated energy delivery. The existing local energy market mechanisms cannot suppress the participants’ strategic bidding, which makes the market imperfectly competitive. Therefore, it is of great significance to collaboratively schedule various demand-side energy resources to further improve the local energy market performance and local energy consumption rate.

The main objectives of this Research Topic are:
1. Applying model-driven or data-driven methods to optimally schedule the demand-side energy resources;
2. Coordinating various types of demand-side resources (e.g., flexible load resources, distributed energy storage, micro gas turbines) to improve the local energy consumption rate.
3. Utilizing different types of demand-side resources to increase local energy market participants' profits and reduce gas emissions.
4. Using demand-side energy resources to neutralize fluctuations in distributed renewable energy generation outputs.
5. Developing novel trading mechanisms to suppress the market participants’ strategical behaviors.

Topics to be covered include, but are not limited to:
1. Local energy market design, operation, and control;
2. Demand-side resource optimal scheduling, including distributed energy generations, energy storages, and flexible loads;
3. Optimal configuration of energy storage on the user side;
4. Load regulation and forecasting;
5. Modeling and optimization of demand-side integrated energy system;
6. Modeling and optimization of low-carbon energy systems;
7. Collaborative operation between microgrids and distribution networks.