### Contribution and Paper Organization  
In the context of a smart gird, this paper proposed a transactive DR framework for high renewable penetrated multi-energy prosumer aggregators based on a flexibility potential evaluation. Table 1 summarizes the differences in the typical works. The contributions are summarized as follows:  
(1) While some previous literature [14; 15; 16] assumes that all flexible resources are equipotent and equally willing to participate in the DR program, some previous literature [5; 6] has tended towards one-time market clearing. These frameworks cannot practically exploit the inherent flexibility of prosumer aggregators. Instead of relying on highly susceptible unperfect forecasting in off-line DR schemes [9; 10; 11; 12], a transactive DR framework is proposed to enable the multi-time-scale proactive participation of demand-side flexible multi-energy resources. Under such a framework, diverse flexible multi-energy resources are aggregated as prosumer aggregators to participate in the multi-time-scale transactive interactions, thereby cost-effectively providing additional auxiliary services and accommodating the high penetration of renewable energy.  
(2) While previous literature [22; 26] has developed various indicators to evaluate the DR flexibility potential based on the operational mechanism or external characteristic, a flexibility potential quantification method is developed to evaluate the positive and negative flexibility of prosumer aggregators from the aspects of flexible time and power. Such a quantification evaluation of the DR flexibility potential can not only improve the  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**References**} & \multirow{2}{*}{**100\% Renewable**} & \multirow{2}{*}{**Multi-Energy**} & \multirow{2}{*}{**Time Scale**} & \multicolumn{2}{c}{**Flexibility Potential Evaluation**} \\ \cline{3-6}  & & & & & **Quantification** & **Pricing** \\ \hline
[5; 6] & ✓ & ✓ & Day-ahead & ✗ & ✗ \\
[4; 9] & ✓ & ✗ & Day-ahead & ✗ & ✗ \\
[10; 13] & No renewable & ✗ & Day-ahead & ✗ & ✗ \\
[11] & No renewable & ✗ & Day-ahead & ✗ & ✗ \\
[12] & ✗ & ✗ & Day-ahead & ✗ & ✗ \\
[7; 8; 14] & ✓ & ✗ & Real-time & ✗ & ✗ \\
[15; 19] & ✗ & ✗ & Real-time & ✗ & ✗ \\
[16] & ✓ & ✓ & Multi-time-scale & ✗ & ✗ \\
[17] & ✗ & ✓ & Multi-time-scale & ✗ & ✗ \\
[20; 23] & No renewable & ✗ & Real-time & Quantitative & ✗ \\
[22] & No renewable & ✗ & Real-time & Quantitative & ✗ \\
[24] & No renewable & ✗ & Day-ahead & Quantitative & ✗ \\
[25; 26] & ✗ & ✓ & Day-ahead & Quantitative & ✓ \\
[27] & ✓ & ✗ & Day-ahead & Quantitative & ✗ \\ Proposed & ✓ & ✓ & Multi-time-scale & Quantitative & ✓ \\ \hline \hline \end{tabular}
\end{table}
Table 1: Differences in the proposed approach.  
utilization rate of various generation devices, but also promote the accommodation of renewable energy.  
(3) Instead of using the incentives [5; 6] and constant time-of-use/real-time prices [7; 8], a flexibility potential pricing mechanism is introduced to comprehensively consider the overall supply-demand level and prosumer-operator interactions. The economically optimal guaranteed flexibility that the prosumer aggregators must provide is obtained to achieve a break-even cost for the ancillary service, showing better practicability.  
The remainder of this paper is structured as follows: Section 2 presents the proposed transactive DR framework using the flexibility potential evaluation method (including flexibility potential quantification and pricing). The detailed implementation process is then presented in Section 3. The case study and conclusions are presented in Sections 4 and 5.