Abstract

Battery storage (BS) sizing problems for grid-connected microgrids (GCμGs) commonly use stochastic scenarios to represent uncertain natures of renewable energy and load demand in the GCμG. Though taking a large number of stochastic scenarios into consideration can deliver a relatively accurate optimal result, it can also highly deteriorate the computational efficiency of the sizing problem. To make an accuracy-efficiency trade-off, a computationally efficient optimization method to optimize the BS capacities based on the power exchanging process of the GCμG is proposed in this paper. According to the imbalanced power of the GCμG, this paper investigates the power exchanging process between the GCμG, BS and external grid. Motivated by the BS dynamics, a forward/backward sweep-based energy management scheme is proposed based on the power exchanging process. A heuristic two-level optimization model is developed with sizing BS as the upper-level problem and optimizing the operational cost of the GCμG as the lower-level problem. The lower-level problem is solved by the proposed energy management scheme and the objective function of the upper-level is minimized by the pattern search (PS) algorithm. To validate the accuracy and computational efficiency of the proposed method, the numerical results are compared with the mixed integer linear programming (MILP) method. The comparison shows that the proposed method shares similar accuracy but is much more time-efficient than the MILP method.

Highlights

  • As one of the well-recognized approaches to mitigate climate change and restructure the global energy mix, microgrids integrate various types of distributed generation sources, such as photovoltaics (PV) and wind turbines (WT), to supply local loads effectively and economically [1,2]

  • We investigate the power exchanging process of the GCμG with the Battery storage (BS) and the external grid and propose a forward/backward sweep-based energy management scheme

  • A heuristic two-level optimization method is established using the proposed energy management scheme and the pattern search (PS) algorithm to determine the optimal capacities of the BS efficiently

Read more

Summary

Introduction

As one of the well-recognized approaches to mitigate climate change and restructure the global energy mix, microgrids integrate various types of distributed generation sources, such as photovoltaics (PV) and wind turbines (WT), to supply local loads effectively and economically [1,2]. From the model point of view, it is the energy management optimization problem that needs to consider a large number of stochastic scenarios in order to represent uncertain natures of renewable energy and load demand in microgrids For those algorithms adopting the similar optimization framework, the dilemma of balancing accuracy and efficiency is still an open question to be answered. To address this problem, instead of solving the BS sizing problem directly via mathematic tools, this paper starts from the perspective of imbalanced power of renewable energy and load demand to study the power exchanging process of the GCμG with the BS and the external grid.

Section followed scheme proposed in in Section
Battery Storage
Dedicated Transformer
Upper Level
Lower Level
Quantification of Power Exchanging Process
The forward to sweep is conducted to initialize the BS preferentially consume
Forward Sweep
Backward Sweep
The maximum energy that the BS needs to
As shown in Figure
Correction Step
Solution Algorithm
Simulation Setup
Proposed Method
Efficiency Comparison
MILP Method
Impact of Two-part Tariff Schemes
Conclusions

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.