A dual-timescale dynamics model for evaluating long-term profiles of distributed energy resources under multi-market mechanisms

Abstract

Distributed energy resources (DER), encompassing distributed renewable resources and distributed energy storage systems, are progressively emancipating themselves from reliance on subsidies and engaging in the realms of energy, green certificate, and capacity markets. However, the long-term profile of DERs under multiple market conditions remains uncertain, and traditional methods are inadequate in addressing the challenges posed by the non-linearity and non-convexity of various factors that affect investment and bidding behavior. Additionally, the varying time scales of clearing models across different markets require a quantitative approach that combines long and short-term scales to determine DER profitability under various critical boundaries. To address these challenges, this paper proposes a dual-timescale dynamics model. Firstly, the system dynamics (SD) method is employed to establish the interplay among various market entities, simulating capacity investment of generation units on a long-term scale. Secondly, the stochastic unit commitment (SUC) is modeled to verify the operating constraints of the system while simultaneously calculating the short-term market clearing results. These results are then fed back to the long-term simulation loop to evaluate the further profitability of DERs. Lastly, a price adjustment mechanism was devised to simulate the frequent occurrence of negative energy prices in high-proportion renewable energy systems, thereby enhancing the fidelity of simulated price data to real-world environments. Through a 20-year simulation, the proposed model quantitatively analyzes the impact of market mechanisms on DER profitability and the influence of DERs on market clearing results. The model has the potential to provide valuable analytical support for the design of DER-related market mechanisms and policy decisions.