Optimal sizing of battery energy storage system in smart microgrid considering virtual energy storage system and high photovoltaic penetration

Xie, Changhong; Wang, Dongxiao; Lai, Chun Sing; Wu, Runji; Wang, Xiaomei

doi:10.1016/j.jclepro.2020.125308

Cited by 66 publications

(20 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Genetic/Evolutionary Algorithm [48] Analog ensemble [106] Bat algorithm-modified [23] Bird-mating optimization [23,139,169,184] Differential evolution algorithm [180] Evolutionary predator and prey [54,89] Exchange market algorithm [29,63,97,102] Genetic algorithm [100] Harmony search algorithm [31] Krill herd algorithm-modified [47,138] NSGA-II [76,122] Rule-based/custom algorithm [87] Symbiotic organism search algorithm [143] Whale optimization algorithm In summary, Figure 10 shows the number of articles that use each type of optimization algorithm and their shares.…”

Section: Referencementioning

confidence: 99%

“…Correlation Technique [141] Copulas [166] Gaussian mixture model [44] Heuristic moment matching [52,85] Modified PEM [60,93,108,160,169,170] Multivariable scenarios/profiles [121,168] Taguchi factorial design [123] Unscented transform Table 14. Linearization techniques employed in the DGS literature.…”

Section: Referencesmentioning

confidence: 99%

“…Especially load (Section 4.1.2), which even with demand response programs will be highly uncertain [188]. Dynamic tariffs are still prevalent [217], and it is in fact an incentive for the use of energy storage (e.g., using arbitrage [169]); therefore, it is expected that they will keep being applied in the following years. However, the SoU that is expected to grow the most is EVs.…”

Section: About the Future Of Dealing With Uncertaintymentioning

confidence: 99%

See 2 more Smart Citations

Optimization Models under Uncertainty in Distributed Generation Systems: A Review

et al. 2022

View full text Add to dashboard Cite

Distributed generation systems (DGSs) are one of the key developments enabling the energy transition. DGSs provide users with increased control over their energy use and generation, but entail greater complexity in their design and operation. Traditionally, optimization models have been used to overcome this complexity, and currently, research is focusing on integrating uncertainties on them. This review attempts to analyze, classify and discuss 170 articles dealing with optimization of DGSs under uncertainty. A survey has been performed to identify the selected manuscripts and the strengths and weaknesses of previous reviews. As a result, an innovative classification has been designed and the distinct elements of optimization models in DGSs have been highlighted: microgrid architecture, sources of uncertainty, uncertainty addressing methods, problem types and formulations, objective functions, optimization algorithms and additional features. Each part is detailed thoroughly to provide an instructive overview of the research output in the area. Subsequently, several aspects of interest are discussed in depth: the future of dealing with uncertainty, the main contributions and trends, and the relative importance of the field. It is expected that this review will be of use to both experts and lay people to learn more about the current state of optimization models in DGSs and provide insights into how to further develop this field.

show abstract

Section: Referencementioning

confidence: 99%

Section: Referencesmentioning

confidence: 99%

Section: About the Future Of Dealing With Uncertaintymentioning

confidence: 99%

See 1 more Smart Citation

Optimization Models under Uncertainty in Distributed Generation Systems: A Review

et al. 2022

View full text Add to dashboard Cite

show abstract

“…At present, researchers have started to study virtual energy storage technology. A virtual energy storage system is defined as a system of controllable loads with energy storage characteristics [50,51]. Combining virtual energy storage with conventional electrical energy storage to form a new hybrid energy storage system is a promising trend.…”

Section: Virtual Energy Storage System Current Research and Developmentmentioning

confidence: 99%

A Review on Thermal Energy Modelling for Optimal Microgrids Management

Yan

Wang

Lai

et al. 2021

Thermo

Self Cite

View full text Add to dashboard Cite

Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.

show abstract

“…In general, microgrids can keep the system stable operation and minimize blackout. Reference [14] applied the mean-variance Markowitz theory and value-at-risk to assess the risk of system cost variability due to the presence of high penetration of renewables such as PV. The risk of system cost can further be reduced through energy storage participation.…”

Section: Related Work and Research Gapmentioning

confidence: 99%

Augmented Power Dispatch for Resilient Operation through Controllable Series Compensation and N-1-1 Contingency Assessment

Huang

Lai

et al. 2021

Energies

Self Cite

View full text Add to dashboard Cite

Research on enhancing power system resilience against extreme events is attracting significant attention and becoming a top global agenda. In this paper, a preventive augmented power dispatch model is proposed to provide a resilient operation. In the proposed model, a new N-1-1 security criterion is proposed to select disruptive N-1-1 contingency cases that might trigger cascading blackouts, and an iterative contingency assessment process based on the line outage distribution factor is proposed to deal with security constraints. In terms of optimization objectives, two objectives related to power flow on the transmission line are considered to reduce the possibility of overload outages. Controllable series compensation devices are also considered in the model to improve the power flow distribution. Case studies conducted on the modified IEEE 30-bus, 118-bus and Polish 2382-bus systems show that the power flow solution of the proposed power dispatch model can avoid some branches from undertaking excessively heavy loads, especially lines forecasted to be affected by extreme events. The results of blackout simulations through a hidden failure cascading outage simulation model show that the average power losses of the proposed model are reduced by around 40% in some cases as compared to the classical economic dispatch model.

show abstract

Optimal sizing of battery energy storage system in smart microgrid considering virtual energy storage system and high photovoltaic penetration

Cited by 66 publications

References 44 publications

Optimization Models under Uncertainty in Distributed Generation Systems: A Review

Optimization Models under Uncertainty in Distributed Generation Systems: A Review

A Review on Thermal Energy Modelling for Optimal Microgrids Management

Augmented Power Dispatch for Resilient Operation through Controllable Series Compensation and N-1-1 Contingency Assessment

Contact Info

Product

Resources

About