Application of Model Predictive Control to BESS for  Microgrid Control

Nguyen, Thai-Thanh; Yoo, Hyeong-Jun; Kim, Hak-Man

doi:10.3390/en8088798

Cited by 36 publications

(25 citation statements)

References 33 publications

(44 reference statements)

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“…The MPC controller, sometimes known as the generalised predictive control and receding horizon control, is a time horizon optimisation model that determines a series of optimal control decisions over a specific future time period [23,24]. In the first control action, the MPC controller computes the decision for the first-time period based on the demand forecast and updates of other variables.…”

Section: Model Predictive Control (Mpc) Controllermentioning

confidence: 99%

Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems

et al. 2017

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This article presents a study of optimal control strategies for an energy storage system connected to a network of electrified Rubber Tyre Gantry (RTG) cranes. The study aims to design optimal control strategies for the power flows associated with the energy storage device, considering the highly volatile nature of RTG crane demand and difficulties in prediction. Deterministic optimal energy management controller and a Model Predictive Controller (MPC) are proposed as potentially suitable approaches to minimise the electric energy costs associated with the real-time electricity price and maximise the peak demand reduction, under given energy storage system parameters and network specifications. A specific case study is presented in to test the proposed optimal strategies and compares them to a set-point controller. The proposed models used in the study are validated using data collected from an instrumented RTG crane at the Port of Felixstowe, UK and are compared to a standard set-point controller. The results of the proposed control strategies show a significant reduction in the potential electricity costs and peak power demand from the RTG cranes.

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Section: Model Predictive Control (Mpc) Controllermentioning

confidence: 99%

Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems

et al. 2017

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“…In grid-connected mode, the battery shuts down, but the two PV DERs and the fuel cell DER continued to operate in active-reactive power (P-Q) control mode [26][27][28][29]. When operation of the microgrid changed from grid-connected to autonomous mode at 5 s, the battery DER discharged to maintain power balance in the microgrid [30][31][32][33]…”

Section: System Components Parametersmentioning

confidence: 99%

A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids

et al. 2016

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This paper proposes a novel protection method for single line-to-ground (SLG) faults in ungrounded low-inertia microgrids. The proposed method includes microgrid interface protection and unit protection. The microgrid interface protection is based on the difference between the zero-sequence voltage angle and the zero-sequence current angle at the microgrid interconnection transformer for fast selection of the faulty feeder. The microgrid unit protection is based on a comparison of the three zero-sequence current phase directions at each junction point of load or distributed energy resources. Methods are also included to locate the minimum fault section. The fault section location technology operates according to the coordination of microgrid unit protection. The proposed method responds to SLG faults that may occur in both the grid and the microgrid. Simulations of an ungrounded low-inertia microgrid with a relay model were carried out using Power System Computer Aided Design (PSCAD)/Electromagnetic Transients including DC (EMTDC).

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“…Detailed modeling of the wear of an EESS thus leads to complex and hard to solve models. On the other hand, most applications of an EESS within an electricity distribution grid require fast control to cope with either real-time fluctuations in the power flow [16,19] or to ensure scalability to many concurrent systems [1]. Furthermore, as a large number of different storage devices are to be expected in the (future) grid, we pursue solutions that are applicable to many different systems.…”

Section: Introductionmentioning

confidence: 99%

Scheduling of Electricity Storage for Peak Shaving with Minimal Device Wear

2016

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Abstract:In this work, we investigate scheduling problems for electrical energy storage systems and formulate an algorithm that finds an optimal solution with minimal charging cycles in the case of a single device. For the considered problems, the storage system is used to reduce the peaks of the production and consumption within (part of) the electricity distribution grid, while minimizing device wear. The presented mathematical model of the storage systems captures the general characteristic of electrical energy storage devices while omitting the details of the specific technology used to store the energy. In this way, the model can be applied to a wide range of settings. Within the model, the wear of the storage devices is modeled by either: (1) the total energy throughput; or (2) the number of switches between charging and discharging, the so-called charging cycles. For the first case, where the energy throughput determines the device wear, a linear programming formulation is given. For the case where charging cycles are considered, an NP-hardness proof is given for instances with multiple storage devices. Furthermore, several observations about the structure of the problem are given when considering a single device. Using these observations, we develop a polynomial time algorithm of low complexity that determines an optimal solution. Furthermore, the solutions produced by this algorithm also minimize the throughput, next to the charging cycles, of the device. Due to the low complexity, the algorithm can be applied in various decentralized smart grid applications within future electricity distribution grids.

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Application of Model Predictive Control to BESS for Microgrid Control

Cited by 36 publications

References 33 publications

Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems

Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems

A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids

Scheduling of Electricity Storage for Peak Shaving with Minimal Device Wear

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