Energy Storage Systems Architecture Optimization for Grid Resilience With High Penetration of Distributed Photovoltaic Generation

Confrey, John; Etemadi, Amir H.; Stuban, Steven M. F.; Eveleigh, Timothy

doi:10.1109/jsyst.2019.2918273

Cited by 36 publications

(10 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A multi-objective function of DG size and allocation optimization was considered regarding the operating, capital, environmental, wind, and light abandonment costs, which were subjected to voltage, current, equation flow, (Confrey et al, 2020).…”

Section: Optimized Dg Allocationmentioning

confidence: 99%

Recent Trends in the Optimization of Renewable Distrib-uted Generation: A Review

2022

View full text Add to dashboard Cite

Distributed energy resources, or distributed generation (DG), are the mainstay of modern power systems aiming towards green energy generation via the effective integration of renewable energy sources. DG involvement in traditional power systems comprises the enhancement of power quality parameters, the utilization of renewable sources, cost optimization, and stable and reliable energy generation. The advantages of such a revolutionary approach can be achieved with the optimal sizing and allocation of DG by means of adequate optimization techniques, constraints, and optimized parameters. In this study, a comprehensive review of DG optimization is presented in light of recent developments, and a comparison is carried out based on the adopted optimization techniques, test system, enhanced parameters, and outcome evaluations.

show abstract

Section: Optimized Dg Allocationmentioning

confidence: 99%

Recent Trends in the Optimization of Renewable Distrib-uted Generation: A Review

2022

View full text Add to dashboard Cite

show abstract

“…For instance, many focus on civilian microgrid infrastructure where deliberate attack is not taken into account and often instead focuses on adverse weather events [26][27][28] or on recovery actions that may not be practical during a deliberate attack [29]. Other research does not define critical loads in a manner that is applicable to the military [30].…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Analyzing Mission Impact of Military Installations Microgrid for Resilience

Peterson

Bossuyt

Giachetti

et al. 2021

Systems

View full text Add to dashboard Cite

This article develops a method to model, analyze, and design military microgrids with the objective to improve their resilience in the face of disconnections from the larger electrical grid. Military microgrids provide power to installation and base facilities to enable base mission objective accomplishments that are related to national security. Previous research, tools, and methods for microgrid design and assessment do not adequately address resilience in terms of accomplishing mission objectives and instead primarily focus on economic outcomes. This article proposes a novel metric to quantify microgrid resilience in terms of its ability to minimize the impact of power disruption on missions supported by the microgrid. The metric is used in a novel design method to ensure an islanded military microgrid can continue operations while disconnected for a two-week duration. Our model examines the ability to continue mission operations subject to various microgrid disruptions as well as equipment reliability.

show abstract

“…Equation (1) suggests that five parameters are required to be predicted for the accurate modeling of PV cells. These are photon current (I Ph ), reverse saturation current (I O ), diode ideality factor (n), series resistance (R Se ), and shunt resistance (R Sh ).…”

Section: Solar Photovoltaic Cellmentioning

confidence: 99%

Probabilistic screening and behavior of solar cells under Gaussian parametric uncertainty using polynomial chaos representation model

Samadhiya

Namrata

2021

Complex Intell. Syst.

View full text Add to dashboard Cite

The paper presents a hierarchical polynomial chaos expansion-based probabilistic approach to analyze the single diode solar cell model under Gaussian parametric uncertainty. It is important to analyze single diode solar cell model response under random events or factors due to uncertainty propagation. The optimal values of five electrical parameters associated with the single diode model are estimated using six deterministic optimization techniques through the root-mean-square minimization approach. Values corresponding to the best objective function response are further utilized to describe the probabilistic design space of each random electrical parameter under uncertainty. Adequate samples of each parameter corresponding Gaussian uncertain distribution are generated using Latin hypercube sampling. Furthermore, a multistage probabilistic approach is adopted to evaluate the model response using low-cost polynomial chaos series expansion and perform global sensitivity analysis under specified Gaussian distribution. Coefficients of polynomial basis functions are calculated using least square and least angle regression techniques. Unlike the highly non-linear and complex single diode representation of solar cells, the polynomial chaos expansion model provides a low computational burden and reduced complexity. To ensure reproducibility, probabilistic output response computed using proposed polynomial chaos expansion model is compared with the true model response. Finally, a multidimensional sensitivity analysis is performed through Sobol decomposition of polynomial chaos series representation to quantify the contribution of each parameter to the variance of the probabilistic response. The validation and assessment result shows that the output probabilistic response of the solar cell under Gaussian parametric uncertainty correlates to a Rayleigh probability distribution function. Output response is characterized by a mean value of 0.0060 and 0.0760 for RTC France and Solarex MSX83 solar cells, respectively. The standard deviation of $$ \pm $$ ± 0.0034 and $$ \pm $$ ± 0.0052 was observed in the probabilistic response for RTC France and Solarex MSX83 solar cells, respectively.

show abstract

Energy Storage Systems Architecture Optimization for Grid Resilience With High Penetration of Distributed Photovoltaic Generation

Cited by 36 publications

References 42 publications

Recent Trends in the Optimization of Renewable Distrib-uted Generation: A Review

Recent Trends in the Optimization of Renewable Distrib-uted Generation: A Review

Analyzing Mission Impact of Military Installations Microgrid for Resilience

Probabilistic screening and behavior of solar cells under Gaussian parametric uncertainty using polynomial chaos representation model

Contact Info

Product

Resources

About