Microgrids with energy storage systems as a means to increase power resilience: An application to office buildings

Rosales-Asensio, Enrique; Simón-Martín, Miguel de; Borge-Díez, David; Blanes‐Peiró, Jorge Juan; Colmenar‐Santos, Antonio

doi:10.1016/j.energy.2019.02.043

Cited by 97 publications

(38 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this paper only considers the operations of AC MGs in gridconnected mode. In [9], the size and operation of renewable energy (e.g. PV) with BESSs are optimized to minimize energy costs and increase the resilience of an AC MG.…”

Section: Ac(dc) Side Variables ∆Ementioning

confidence: 99%

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

2020

View full text Add to dashboard Cite

High-impact and low-probability extreme events can cause severe damage to power systems, especially for distribution systems. Microgrids (MGs) with distributed generation resources provide a viable solution for local load survivability via islanding schemes during extreme events. Recently, much research has focused on resilience-driven modeling and operations of MGs. In this paper, a resiliencedriven operational model incorporating two operational modes (grid-connected and islanded) and detailed technical characteristics, such as voltage-related operational constraints, is developed for the resilience enhancement of a hybrid AC/DC MG. A detailed AC optimal power flow (OPF) algorithm is employed to model operational constraints and the power exchange between AC and DC subgrids. Preventive power importing is utilized for better preparedness before extreme events and demand response is employed to reduce load shedding during emergency mode. Existing literature on resilience assessment is reviewed and a modified multi-phase curve is proposed to fully represent the influence of limited generation resources and uncertain event duration on resilience. Extensive case studies capturing the distinction of critical loads and non-critical loads and two types of contingencies (multiple line faults and interrupted connection between AC subgrid and DC subgrid) are conducted to demonstrate the effectiveness of the proposed resilience strategy on protecting critical loads and reducing total load shedding. Particularly, a sensitivity analysis considering different event occurrence time has been simulated to capture, in a simple but rather effective way, the effect of the uncertainty surrounding event occurrence.

show abstract

Section: Ac(dc) Side Variables ∆Ementioning

confidence: 99%

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

2020

View full text Add to dashboard Cite

show abstract

“…Recent studies, for this reason, have called for engineering greater resilience in microgrids [11,12]. This study explicitly addresses the resilience of DPG in the context of islanding.…”

Section: Introductionmentioning

confidence: 99%

A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network

et al. 2020

View full text Add to dashboard Cite

Finding an appropriate technique to detect an islanding issue is one of the major challenges associated with the design of a resilient grid-linked photovoltaic-based distributed power generation (PV-DPG) system. In general, the technique used for islanding detection must be able to sense the disruptions from the electric grid and quickly disconnect PV-DPG from the grid. The quick disconnection of PV-DPG mostly avoids power quality problems, damage to power assets, voltage stability issues, and frequency instability. In this paper, a new islanding detection technique that is based on tunable Q-factor wavelet transform (TQWT) and an artificial neural network (ANN) is proposed for PV-DPG. The proposed approach consists of two steps: in the first step, the vital detection parameters are computed by performing simulations considering all possible switching transients, islanding events, and faults from the grid side. Then, the decomposition of obtained signals is done using TQWT on different levels. Using the obtained coefficients, at each level, features such as range, minimum, mean, standard deviation, maximum, energy, and log energy entropy are computed. The optimal feature set was selected as the input for the second step. The classification of the non-islanding and islanding states for PV-DPG is made using the ANN classifier in the second step, which achieved an accuracy of 98%. The results representing the efficiency of the proposed approach in noisy and non-noisy environments are also explained. Overall, it is understood that the proposed islanding detection technique would provide suitable insights to detect an islanding issue.

show abstract

“…Battery energy storages (BESs) and traditional generators both can play the role of back-up energy sources in energy systems. Moreover, during electricity disruptions, both BES and TG can be considered as available energy sources for consumers [17,18]. TGs are fossil fuel-based energy resources which are usually utilized by conventional energy consumers.…”

Section: Introductionmentioning

confidence: 99%

“…BESs are mostly embedded in RES-based MGs, and consequently, are independent of fossil fuels [19]. Due to the development of BESs, more applications of them have been suggested in recent studies as back-up energy resources [17], and it has been expected to study more on BESs in resilient energy systems in the future. For this reason, this paper compares two different back-up energy sources in different aspects-techno-economic and environmental.…”

Section: Introductionmentioning

confidence: 99%

“…In [23], the authors studied the optimal BES and backup generator sizing problem which considered the stochastic event occurrence duration on the grid-tied MG under off-grid operation. Authors in [17] utilized a methodology to quantify the resilience PV/BES benefits. In addition, a case study was performed, and results showed that the MG cost of energy (COE) was decreased for a grid-connected mode.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Comparative Study between Traditional Backup Generator Systems and Renewable Energy Based Microgrids for Power Resilience Enhancement of a Local Clinic

et al. 2019

View full text Add to dashboard Cite

Extreme weather events lead to electrical network failures, damages, and long-lasting blackouts. Therefore, enhancement of the resiliency of electrical systems during emergency situations is essential. By using the concept of standby redundancy, this paper proposes two different energy systems for increasing load resiliency during a random blackout. The main contribution of this paper is the techno-economic and environmental comparison of two different resilient energy systems. The first energy system utilizes a typical traditional generator (TG) as a standby component for providing electricity during the blackouts and the second energy system is a grid-connected microgrid consisting of photovoltaic (PV) and battery energy storage (BES) as a standby component. Sensitivity analyses are conducted to investigate the survivability of both energy systems during the blackouts. The objective function minimizes total net present cost (NPC) and cost of energy (COE) by considering the defined constraints of the system for increasing the resiliency. Simulations are performed by HOMER, and results show that for having almost the same resilience enhancement in both systems, the second system, which is a grid-connected microgrid, indicates lower NPC and COE compared to the first system. More comparison details are shown in this paper to highlight the effectiveness and weakness of each resilient energy system.

show abstract

Microgrids with energy storage systems as a means to increase power resilience: An application to office buildings

Cited by 97 publications

References 23 publications

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network

A Comparative Study between Traditional Backup Generator Systems and Renewable Energy Based Microgrids for Power Resilience Enhancement of a Local Clinic

Contact Info

Product

Resources

About