Tertiary level control of multi-microgrid using hybrid methods considering consumer participation

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: Tertiary level control of multi-microgrid using hybrid methods considering consumer participation

ارائه دهنده: Provider: Reza Rashidi

اساتید راهنما: Supervisors: Dr.Alireza Hatami

اساتید مشاور: Advisory Professors: Dr.Mohammad Abedini

اساتید ممتحن یا داور: Examining professors or referees: Dr.Mohammad Hasan Moradi, Dr.Abas Fatahi, Dr.Hamdi Abdi

زمان و تاریخ ارائه: Time and date of presentation: Time: 14 to 16 / 19.2021.OCT

مکان ارائه: Place of presentation:

چکیده: Abstract: Abstract: In this thesis, Multi-Microgrid (MMG) energy management with the aim of optimizing operating costs and increasing their sustainability is considered. This management is under a 24-hour period. Each MG has its own complex controls because, despite load fluctuations, renewable energy resources (RERs) have limited capacity. In control plans for these small grids, economic and sustainability goals must be met simultaneously, which complicates their operation. Considering load and generation uncertainties and the presence of RERs with their own behavior and capacities, control methods for MGs have been proposed. Formation of MGs close to each other and far from the utility grid, allows the formation of MMG and power exchange with each other. This thesis uses tertiary-level control (TLC) as the highest level of hierarchical control to control MMG. In the proposed control model, the primary level controls the local controllers and the secondary level controls all the local controllers in each MG, and finally at the tertiary level controls all the MG secondary controllers simultaneously with the aim of maintaining stability and reducing operating costs. In this study, the TLC is shown as the preferred control model in a MMG and evaluates the performance of the proposed control model by considering new factors that have a direct relationship with the useful life of power generators. Thus, the multi-objective function is formed by the challenge between its factors. Here, using uncertainty prediction models, both in generation and in consumption, it forms a structure that is consistent with reality. In this structure, real data from wind and solar farms are used for maximum adaptation to reality, and this is the same model of Adaptive Model Predictive Control (AMPC). Here, due to the large volume of uncertainties, Information Gap Decision Theory (IGDT) method is used to increase the probability of uncertainties. To evaluate the proposed control model in the mentioned structure, MATLAB and DigSilent software have been used simultaneously. MATLAB uses the Tunicate Swarm Algorithm (TSA) to determine the best model for connecting MGs as well as the setpoints of the central controllers of each MG, and after determining, it will be provided to DigSilent software for optimal load dispatch and its results will be provided to MATLAB again. This process continues until it reaches the optimal point of operation. These determinate points are executed every hour for MGs and the results show the effectiveness of the proposed control method.

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