Optimal sizing of Battery Energy Storage Systems for dynamic frequency control in an islanded microgrid: A case study of Flinders Island, Australia

El-Bidairi, Kutaiba S.; Nguyen, Hung D.; Mahmoud, Thair S.; Jayasinghe, Shantha Gamini; Guerrero, Josep M.

doi:10.1016/j.energy.2020.117059

Cited by 120 publications

(51 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instead of considering a perfect power equilibrium, dynamical studies aim to achieve power quality criteria at short timescales thanks to primary reserves (fossil generators and battery systems) whilst ensuring the continuity of load supply at longer timescales thanks to secondary and tertiary reserves (33). The role of energy storage systems in the frequency regulation paradigm has been extensively studied for large systems (34) as well as smaller isolated grids (35). In this study, only primary regulation is addressed.…”

Section: Application Of Power System Theory To Hybrid Systemsmentioning

confidence: 99%

On the relationship between battery power capacity sizing and solar variability scenarios for industrial off-grid power plants

Polleux

Schuhler²,

Guérassimoff³

et al. 2021

Applied Energy

View full text Add to dashboard Cite

Due to its high short-term variability, solar-photovoltaic power in isolated industrial grids faces a challenge of grid reliability. Storage systems can provide grid support but come at a high cost that requires carefully evaluating power capacity needs. Battery sizing methodologies are now the focus of many studies, with a global upward trend in detailed modelling and complex optimization. However, although solar variability can be the source of uncertainties and battery oversizing, it rarely features as an input in scenarios. This study proposes several solar variability scenarios thanks to the wavelet-variability model and two variability metrics. These scenarios are employed as inputs in two sizing methodologies to compare the resulting battery capacity and draw conclusions on the role of modelling complexity and scenario identification. Results show that neglecting the photovoltaic power plant smoothing effect leads to an overestimation of the battery power support of 51%. In the other hand, complex dynamic modelling may reduce the battery power capacity by 25%. The economic analysis shows that a proper combination of variability scenario and battery sizing methodology may reduce the levelized costs of electricity by 3%. Highlights• Modelling photovoltaic plant geographical smoothing avoids over-investments.• Identifying variability scenarios is crucial to ensure continuity of supply.• Combining ramp-detection and variability index spares the use of day-long timeseries.

show abstract

Section: Application Of Power System Theory To Hybrid Systemsmentioning

confidence: 99%

On the relationship between battery power capacity sizing and solar variability scenarios for industrial off-grid power plants

Polleux

Schuhler²,

Guérassimoff³

et al. 2021

Applied Energy

View full text Add to dashboard Cite

show abstract

“…This is attributed to the singular variable characteristic of system frequency, unlike voltage, which is closely related to reactive power-sharing accuracy and could have many values across the network. The minimization of the frequency deviations problem in DCIMG was tackled from the perspective of BESS and FESS availability to cover for non-dispatchable renewable generation shortfalls [56,175]. Likewise, optimal frequency regulation was handled by the employment of PV-FC energy systems [32], allocation of DG units [108], and utilization of demand response (DR) programs [165].…”

Section: Frequency Regulation Objectivesmentioning

confidence: 99%

“…Another fundamental variable that is gaining popularity in recent years is the ESS charge/discharge power rate [79][80][81][86][87][88][89][90]125,[128][129][130][131]133,137,[144][145][146]150,151,163,164], as well as the discharge rate coefficients for BESS [33,35]. Furthermore, in planning studies, the number of required ESS is another variable of interest [103], while capacity (in Ah) [96,97,99,112,121,172,175], power rating (in kW) [121,172,175], type (such as LABESS, VRBESS, FESS, HESS) [96,99], and location of ESS [96][97][98][99]112] are also core variables for storage allocation studies in DCIMG.…”

Section: Ess Variablesmentioning

confidence: 99%

Optimal Allocation and Operation of Droop-Controlled Islanded Microgrids: A Review

Kreishan

Zobaa

2021

Energies

View full text Add to dashboard Cite

This review paper provides a critical interpretation and analysis of almost 150 dedicated optimization research papers in the field of droop-controlled islanded microgrids. The significance of optimal microgrid allocation and operation studies comes from their importance for further deployment of renewable energy, reliable and stable autonomous operation on a larger scale, and the electrification of rural and isolated communities. Additionally, a comprehensive overview of islanded microgrids in terms of structure, type, and hierarchical control strategy was presented. Furthermore, a larger emphasis was given to the main optimization problems faced by droop-controlled islanded microgrids such as allocation, scheduling and dispatch, reconfiguration, control, and energy management systems. The main outcome of this review in relation to optimization problem components is the classification of objective functions, constraints, and decision variables into 10, 9, and 6 distinctive categories, respectively, taking into consideration the multi-criteria decision problems as well as the optimization with uncertainty problems in the classification criterion. Additionally, the optimization techniques used were investigated and identified as classical and artificial intelligence algorithms with the latter gaining popularity in recent years. Lastly, some future trends for research were put forward and explained based on the critical analysis of the selected papers.

show abstract

“…It is also possible to combine wind production with storage systems, like batteries, fuel cells, and/or hydrogen storage. In this way, it becomes possible to instantaneously inject power into the grid and back up the conventional generation systems [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Day-Ahead MPC Energy Management System for an Island Wind/Storage Hybrid Power Plant

et al. 2021

View full text Add to dashboard Cite

This paper presents a multi-objective energy management system (EMS) to manage the power dispatch of a hybrid power plant (HPP), consisting of a grid-connected wind farm and a Li-ION battery storage system on the island of Guadeloupe’s electrical grid. Via a controller based on Model Predictive Control (MPC), the EMS solves the problem of optimization by considering the production forecast data and managing several operation rules, which ensures meet energy targets considered for a sustainable power dispatching plan. The proposed strategy is tested in a PowerFactory/MATLAB co-simulation environment.

show abstract

Optimal sizing of Battery Energy Storage Systems for dynamic frequency control in an islanded microgrid: A case study of Flinders Island, Australia

Cited by 120 publications

References 44 publications

On the relationship between battery power capacity sizing and solar variability scenarios for industrial off-grid power plants

On the relationship between battery power capacity sizing and solar variability scenarios for industrial off-grid power plants

Optimal Allocation and Operation of Droop-Controlled Islanded Microgrids: A Review

Day-Ahead MPC Energy Management System for an Island Wind/Storage Hybrid Power Plant

Contact Info

Product

Resources

About