To achieve the net-zero target, extremely high penetration of renewable energy resources (RES) will be integrated into the grid. The inherent uncertainty and intermittency of RES could threaten power system security by causing power imbalance, voltage violation, frequency fluctuation, and eventually a large-scale blackout, which may prevent the achievement of the net-zero target. Demand-side management (DSM) is regarded as a silver bullet to enhance the power system operational flexibility for boosting the accommodation of RES in a cost-effective manner. DSM refers to the techniques that can dynamically adjust the customer's power and energy demand based on market signals for enhancing the reliability, resilience, sustainability, security, and economics of local power systems. While the value of DSM to provide multi-provision service across the whole operation timeline, including balancing service, renewable support, network support, frequency response provision, voltage regulation provision, and capacity market, has been widely quantified, the actual implementation to achieve such value by simultaneously managing large-scale heterogeneous demand in a sustainable, privacy-preserved, and secure manner still requires further investigation.
Under most of the existing schemes, DSM is performed by a remote centralized aggregator's cloud computing facility. Therefore, the onsite captured demand data has to traverse through a long physical distance to the aggregator's cloud. Although cloud computing is powerful, mature, and ubiquitous, its centralized nature suffers from the bandwidth and time delay requirement of DSM due to the massive heterogeneous data transmission through shared infrastructure. Furthermore, some industries and houses are located in the energy-poor area with less-developed infrastructure. Therefore, their data are not reachable over reliable network connections, which prevents their participation in DSM schemes. The inequality of rich and poor communities could be exacerbated by using the DSM since rich communities will better benefits from DSM. In addition, centralized computing could result in privacy concerns as each consumer is required to submit its proprietary demand data to the central aggregator's cloud center. In this context, the existing cloud computing should be expanded across multi-sites and networks for timely data processes while ensuring efficiency and robustness.

This project solves the mentioned challenges by using advanced digitalization technologies. First, we investigate various frameworks for cloud-edge coordination under DSM application, which can intelligently and dynamically assign different tasks to the cloud and edge centers based on different types of service provision, the availability/capability of edge, and the choice of consumers. Second, we investigate the application of blockchain for data management and service performance evaluation for local processors, which guarantee that data authenticity and integrity are guaranteed without extra investment in hardware. As a result, even less-developed industries and houses can ensure that the stored data is secure. Moreover, the smart contract can be employed to evaluate the performance of the service provided by the demand. Finally, we propose a secure communication framework using blockchain in the wireless communication environment. A novel dynamic data integrity system combining hash, digital signature, and asymmetric encryption will be investigated to protect and transmit data for end-to-end secure interaction across the entire system, from smart meters to cloud centers. The communication framework is specially optimized for the current wireless communication network provided by the LTE and 5G base stations.