Provision of security involves protecting lives and properties, and properties in this context include data and services. This paper investigates the impact of cyber-attacks on load scheduling applications by simulating various possible modes for these attacks while observing possible effects on the users. The attack modes used are in the form of denial of service (DoS) and phishing attacks whereby the attacker is able to interfere with data intake to the Home Energy Management Systems (HEMS) or a modification of critical data to the HEMS. The dynamic pricing information and load profile data is the target here although other types of data utilized by the central controller for load scheduling purposes can also be targeted. The test-bed uses load scheduling applications based on genetic algorithm optimization. Results show the impact on optimized load profiles and how they can discourage active demand response participation if such attacks are not properly managed.
Among the key objectives of the smart grid technology are to foster the grid integration of renewable energy as well as market participation of domestic energy consumers through demand response program. Energy storage remains a key component of the smart grid. Past works on integration of energy storage at the domestic side of the electricity grid has identified the electric vehicle technology (EV) and the embedded energy storage (EES) technology, etc. However, it was difficult to compare between these technologies in terms of business incentives and technical performance. This was investigated in this work, and the results are presented. It was propose to use percentage difference to compare between VPP with EES and VPP with EV. The results shows that the difference in prosumers incentives between VPP with EES and VPP with EV is very low. It is approximately 0.89%. However, the percentage difference in VPP operator profit between VPP with EES and VPP with EV is very high. It is approximately 85.3%. The VPP makes very high profit in the VPP EES case compared to VPP EV case. The same also applies to the VPP cumulative performance where the percentage difference in the VPP cumulative performance between VPP with EES and VPP with EV is approximately 10.9%. This has implication on the storage mechanism to be integrated in to a VPP at the domestic level as well the business model to be adopted.
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