Macquarie University
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Energy management systems for prosumers integrated with electric vehicles and distributed energy resources

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posted on 2023-07-19, 02:52 authored by Sohaib RafiqueSohaib Rafique

Increased electri?cation of transport sector will result in rising energy demand, while the uncoordinated charging of EVs can result in unpredictable peaks in the distribution network. On the other hand, increased penetration of distributed energy resources (DERs) at the demand side, especially the grid integration of intermittent renewable energy sources (RESs) can jeopardize demand-supply balance. Nevertheless, the capacity issues of the grid to meet the additional energy needs, manage the peak load demand and intermittency of the integrated RESs, can be mitigated by e?ectively managing the energy resources. This necessitates a comprehensive energy management system (EMS) to ensure optimal utilization of energy resources. This dissertation presents four innovative contributions towards developing the EMSs for the prosumers belonging to different typologies that are integrated with EVs and RESs, to minimize the cost of electricity for the prosumers while managing peak demand for the grid operator.

The first contribution of this research is to develop and compare two energy management schemes for high density residential apartment buildings integrated with RES and EVs. The proposed study will assist in evaluating and comparing the centralized and the decentralized energy management schemes, in terms of cost savings and reduction in energy consumption for the prosumers.

The second contribution is the development of a comprehensive EMS for optimal charge-discharge scheduling of EVs in a low voltage residential network to minimize the cost of electricity for energy prosumers and manage the peak power demand to avoid the overloading issue of the grid. The proposed EMS will facilitate the integration of EVs into residential networks and effectively utilise demand-side flexibility for addressing local grid capacity issues.

This third contribution of this research is to establish a novel two-stage multiobjective stochastic optimization-based EMS for the E-bus depot operator. The proposed EMS will ensure that the energy demand of the E-bus depot does not exceed the grid capacity limits at any time while minimizing the cost of electricity for the depot operator by optimal utilization of energy resources.

The final contribution of this research is to design an extensive energy management framework to minimize the cost of electricity for E-bus depot operators by utilizing the energy-arbitrage flexibility of stationary batteries and the batteries installed in E-buses. The proposed EMS will establish all energy needs are met for an E-bus depot with constrained power supply from grid by optimal utilization of available energy resources while minimizing the cost for the depot operator.

Extensive case studies are conducted considering load profiles, solar PV generations, EV travel patterns, E-bus run schedules, and energy tariffs for prosumers (i.e., residential EV owners and E-bus depot operators). Detailed analyses of the results are presented, and the performance of the proposed methodologies are compared with the state-of-the-art methods. The results indicate the efficacy of the proposed methodologies for the effective utilisation of demand-side flexibility for mitigating local grid issues. The results also indicate that the proposed EMSs offer significant cost savings for energy prosumers without affecting their energy utilization routine.


Table of Contents

1. Introduction -- 2. Literature Review -- 3. Energy management systems for residential buildings with electric vehicles and distributed energy resources -- 4. EV Scheduling framework for peak demand management in LV residential networks -- 5. A two-stage multi-objective stochastic optimization strategy for electric bus depot operator to minimize cost -- 6. Stochastic approach to minimize the cost of electricity for depot operator with constrained grid supply -- 7. Conclusions and Recommendations for Future Work -- References

Awarding Institution

Macquarie University

Degree Type

Thesis PhD

Department, Centre or School

School of Engineering

Year of Award


Principal Supervisor

Subhas Mukhopadhyay

Additional Supervisor 1

Jahangir Hossain

Additional Supervisor 2

Graham Town


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220 pages