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Background
The Campus Energy Trading System is based on our AEBiS project. Our latest work focus on the expansion & upgrade of its security part, involving both software and hardware platform. For software part, we will take advantage of the existing function and UI of battery charge prediction, which is based on conventional local training and federated learning schemes in Python. For hardware part, to develop the AI-Enabled secure system, our research base on existing AI-chip inference model.
Base on their type, the information in trading system could be divided into: status & parameters of EVs, detail of demand and price, orders and confirmation; base on the direction of information flow, mainly two parts are within control of the campus system: with EV and with energy exchange. Different encryption methods shall be taken according to data's feature and importance. Of the important trading confirmation and order we plan to take private or hybrid blockchain as protection.
Motivaiton
To cut down carbon emissions and build sustainable society, the concept of smart grid and VPP has been introduced as reform of conventional power grid. And internet-connected smart grid is emerging as an innovative approach to efficiently integrate green technologies and renewable energy. So we plan to design a internet-connected smart grid for campus sharing electric vehicles. To begin with, we identify the significant security challenges of smart grid scenarios that can be addressed by internal and external factors. Meanwhile, blockchain turn out to be an immutable type of distributed ledger that is capable of storing data without relying on any third party, whose application in smart grid for cybersecurity attracted significant interest in research areas. So we shall also conduct a specific survey on blockchain paradigm for cybersecurity in a smart grid.
| Date | Task |
| ☑️Mar 11 - Mar 31,2021 | Figure out the mechanism of conventional power market |
| ☑️Apr 1st - Apr 21,2021 | Expand the proposed market system to more scenarios |
| ☑️Apr 22 - Apr 30, 2021 | |
| ☑️May 1st - May 10, 2021 | Design secure (mainly Blockchain part) working mechanism & logic of trading system in campus |
| ☑️May 10 - May 30, 2021 | Discuss & optimize the planned BC parts |
| ☑️May 31 - Jun 14, 2021 | Propose Blockchain channels within campus for energy bidding & mechanism for EV selection |
| ☑️Jun 15 - Jun 23, 2021 | Creat dataset & Requests Selection algorithm |
| ☑️Jun 24 - Jul 5, 2021 | Conduct simulation experiment for request selection & energy trading system |
| ☑️Jul 6 - Jul 17, 2021 | Research on the existing tools & application of consortium blockchain |
| ☑️Jul 18 - Jul 27, 2021 | Propose applications of consortium blockchain in planned security scenarios |
| ☑️Jul 28 - Aug 15, 2021 | |
| ☑️Aug 16 - Sep 31, 2021 | Deploy consortium BC on energy trading by Hyperledger Fabric 2.3 with shell |
| ☑️Sep 1st - Oct 20, 2021 | Set valuation goals for the BC part and make relating adjustments |
| Oct 21 - Nov 11, 2021 | Tansform the python algorithm with golang into haincode to apply the Fabric system |
| Oct 21 - Nov 11, 2021 | Tansform the python algorithm with golang into chaincode to apply the Fabric system |
| Nov 12 - Nov 30, 2021 | Valuate the performance of the chaincode and channel on the energy trading |
| Dec 1st - Dec 31, 2021 | Draft a journal paper on the ground of the preliminary work and submit |
| Jan 1st - Jan 31, 2022 | Implement & optimize planned system's predicting part with AI |
| Feb 1st - Feb 14, 2022 | Work on emergency prevention for smart power trading system |
| Feb 15 - Mar 11, 2022 | Enable efficient peak-cut and demand response according to AI |
| Mar 12 - Mar 31, 2022 | Optimize current power trading system in a placid way of merging renewable powers in |
| Apr 1 - Apr 30, 2022 | Optimize the algorithm for system scalability & real-timing |
