# Hybrid Energy Routing Approach for Energy Internet
## 8 Conclusions and Future Work  
With the expanded use of renewable energy sources in EI, the centralized energy supply mode has shifted to a multi-source and multi path mode leading to the peer-to-peer energy trading market. The energy routing process is one of the major problems faced in EI. To solve this problem, we proposed a solution to the three issues: subscriber matching, energy-efficient path and transmission scheduling. For this purpose, we developed a centralized peer-to-peer energy trading scheme that uses a central broker and novel energy routing approach. The energy routing approach is based on meta-heuristic method to achieve a P2P energy trading with an efficient routing in the EI with respect to the energy routing constraints and congestion. The main objective of the proposed approach is to reduce the energy cost and losses while satisfying the consumers request. The use of a meta-heuristic method reduces the execution time. In fact, the energy routing approach is composed of three algorithms, the first one is the subscriber matching mechanism that determines the producer-consumer pairs with the minimization of the cost and losses of energy for both mono and multi-source consumers. The non-congestion energy minimum loss path between producer-consumer pairs is generated by the IACO-ERP. In the case of multi-source consumers such as EVs where none of the existing producers can provide the required energy, two or more producers should be selected to supply the requested amount of power. For that, the _EPSOA_ determines the appropriate producers to achieve the lowest energy cost and losses. The effectiveness of the proposed approach, in terms of cost, power losses and congestion management, is verified by different cases analysis. The overlapping time provides a better utilization of network power lines with more power \begin{table}
\begin{tabular}{l c c c} \hline \hline  & **Reproduced** & **Reproduced** & \\
**Criteria** & **from [20],** & **from [21],** & **Our Proposed Approach** \\  & **2017** & **2018** & \\ \hline Subscriber matching & & & ✓ \\ Energy efficient path & ✓ & ✓ & ✓ \\ Transmission scheduling & ✓ & ✓ & ✓ \\ Mono-source consumer & ✓ & ✓ & ✓ \\ Multi-source consumer & ✓ & & ✓ \\ Power loss & ✓ & ✓ & ✓ \\ Cost & & & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 24: Proposed approach vs. previous works. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Case 1** & **Mono-Consumer** & **Mono-Consumer** \\ \cline{2-4}  & \(D4\to D7\) & \(D2\to D7\) & **(30 Nodes)** & **(50 Nodes)** \\ \hline
[20] & 0.48 s & 0.50 s & 36.38 s & 52 s \\ IACO-ERP & 0.67 s & 0.84 s & 3.51 s & 6 s \\ \hline \hline \end{tabular}
\end{table} 
Table 25: Execution time for IACO-ERP vs Reproduced from [20], IEEE: 2017.  
losses compared to the non-overlapping time. In addition, the use of the broker decreases the number of messages exchanged in the network. By comparison to the work in [20], our proposed approach has improved the execution time for both mono- and multi-sources cases in small and large systems by 7 min. The proposed approach can be used to match prosumers in the local energy market, provide alternative transmission paths when the efficient path is disrupted, and manage congestion on distribution links. In the future, we plan to explore the possibility of applying additional bio-inspired methods, and we aim to explore to apply our solution to real life applications. The specific contributions made by each author are shown as follows: conceptualization, D.M. ; formal analysis, S.H. ([PERSON]); methodology, S.H. ([PERSON]); software, S.H. ([PERSON]); supervision, S.H. ([PERSON]); visualization, M.D. ; writing--original draft, S.H. ([PERSON]); writing--review and editing, D.M. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. No new data were created or analyzed in this study. Data sharing is not applicable to this article. The authors declare no conflict of interest.