A novel real-time demand side management scheme for the addition of electrical vechicles to the future grid

• Main Author: Zareen, Naila
• Format: Thesis
• Language: English
• Published: 2016
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/78817/1/NailaZareenPFKE2016.pdf; http://eprints.utm.my/id/eprint/78817/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:105980

Electric Vehicles (EVs) as the alternative to the current fossil fuel vehicles represent the most promising green approach to the electrification of a significant portion of the transportation sector. Taking the randomness of EVs’ charging/ discharging characteristics into consideration, a significant uncertainty will be added to the grid. Consequently, charging/discharging management of EVs in the presence of large scale intermittent Renewable Energy Resources is considered as the most significant challenge for the future smart grid. Tackling the challenges of stable operation, this thesis proposes a novel approach of micro-grid stability by exploiting the demand side management. In this context, a comprehensive interactive hierarchical based architecture for the electricity supply and demand interaction in a smart grid environment is proposed to encourage the high participation of residential customers in a new deregulated electricity market. A novel market-oriented energy imbalance management scheme is also proposed for the seamless integration of EVs to the grid in the presence of intermittent resources. The proposed scheme which, unlike previous works, utilizes the grid’s operating characteristics model within the signaling gametheoretic approach for the successful operation of electricity market. Optimal decision strategies for both EV owners and utility are devised by capturing the conflicting economic interests of players together under load/generation uncertainties. Thus, this thesis presents a planning tool for electric utilities that can provide an insight into the implementation of demand response at the end-user level in an automated way to bridge the gap between scheduling EVs and its benefits. The efficacy of the proposed approach in reducing peak loads while satisfying customers’ needs are demonstrated and compared with other schemes. Results show that the proposed methodology can successfully alleviate more than 53% of the peaks caused by the mass adoption of EVs with the better utilization of intermittent resources and substantial amount of profit.