| Challenge | Ref. # | Solution | Advantage / Disadvantage |
|---|---|---|---|
| Security | [63] | A regulatory framework equivalent to Health Insurance Portability and Accountability Act (HIPPA) for smart grid privacy and consumer fraud problems | Would provide clear legislative and legal avenues should problems occur / Bureaucracy would not solve some of the problems provided |
| [64] | A distributed incremental aggregation framework for smart meters to protect users’ privacy by using homomorphic encryption | Unidirectional functionality not allowing for passing information back to a specific unit; Time delay of communication in possible real time operations; Does not look into malicious or fraudulent data acquisition. | |
| [65] | Using a battery connected between the home and the grid so that anyone looking at the power usage will see a battery charging and not the current profiles of the actual items using power | Makes power usage indistinguishable from one day to the next; Overhead of installation and usage and wear and tear costs of a battery system in a home; Difficult to hide high power usage items such as AC, washer, dryer, etc. | |
| [66] | Privacy vs utility: How to get the best of both worlds without sacrificing too much on either side. | Balanced framework / Gives up privacy information of high power item usage as well as the price of the battery | |
| [67] | Targeted attacks vs random attacks to smart grid: Building faster and more resilient networks to fend off attacks through the communication networks | Faster networks would entail creating a faster protocol to transfer information; Faster connections mean less encryption or protections increasing privacy and attacker problems. | |
| [69] | Load Redistribution (LR) attacks: Using Multi-start Benders decomposition to find the most damaging immediate attack. | Good attack prevention strategy for this specific type of attack | |
| [70] | Proposing strategies to detect and localize malicious attacks | Capable of detecting attacks on multiple locations / The number of locations being attacked expands computation. | |
| Quality | [75] | The data mining-based and the state estimation-based electricity consumption outlier data detection methods | Data mining algorithms are faster and better at detecting outliers than traditional methods / Does not account for missing or redundant data. |
| [82] | Developing a data mining prototype system (RMINE) for fault diagnosis or system malfunction detection | Capable of obtaining the minimal diagnostic rule set to derive a logical decision in assisting maintenance engineers to diagnose faults | |
| [86] | Introducing a new class of attacks, called false data injection attacks against monitoring of PMUs or smart grid sensors for state estimation | N/A | |
| Processing location | [88] | Using embedded neural networks to analyze edge-based load information. | Offers privacy concerns by identifying what is being used in a specific area. |
| [89] | Creating a micro grid out of a smart home | Makes a good framework out of the smart home / Lack of intelligent connections to the grid makes it unusable. | |
| [90] | Applying edge computing in the Power Internet of Things (PIOT), such as in monitoring transmission lines, managing smart homes, etc. | Bandwidth issues, locational solutions |