Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations

Zia, Muhammad Fahad; Elbouchikhi, Elhoussin; Benbouzid, Mohamed

doi:10.1016/j.apenergy.2019.01.040

Cited by 142 publications

(68 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the distribution system operator (DSO) encourages prosumers to achieve benefits and reduction in maintenance and expansion cost of equipment. In the U.S. and some European countries, the development of this kind of market has led to achieving a great balance between supplies and demand as well [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources

et al. 2020

Self Cite

View full text Add to dashboard Cite

In recent years, taking advantage of renewable energy sources (RESs) has increased considerably due to their unique capabilities, such as a flexible nature and sustainable energy production. Prosumers, who are defined as proactive users of RESs and energy storage systems (ESSs), are deploying economic opportunities related to RESs in the electricity market. The prosumers are contracted to provide specific power for consumers in a neighborhood during daytime. This study presents optimal scheduling and operation of a prosumer owns RESs and two different types of ESSs, namely stationary battery (SB) and plugged-in electric vehicle (PHEV). Due to the intermittent nature of RESs and their dependency on weather conditions, this study introduces a weather prediction module in the energy management system (EMS) by the use of a feed-forward artificial neural network (FF-ANN). Linear regression results for predicted and real weather data have achieved 0.96, 0.988, and 0.230 for solar irradiance, temperature, and wind speed, respectively. Besides, this study considers the depreciation cost of ESSs in an objective function based on the depth of charge (DOD) reduction. To investigate the effectiveness of the proposed strategy, predicted output and the real power of RESs are deployed, and a mixed-integer linear programming (MILP) model is used to solve the presented day-ahead optimization problem. Based on the obtained results, the predicted output of RESs yields a desirable operation cost with a minor difference (US$0.031) compared to the operation cost of the system using real weather data, which shows the effectiveness of the proposed EMS in this study. Furthermore, optimum scheduling with regard to ESSs depreciation term has resulted in the reduction of operation cost of the prosumer and depreciation cost of ESS in the objective function has improved the daily operation cost of the prosumer by $0.8647.

show abstract

Section: Introductionmentioning

confidence: 99%

Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…A case study showed the operational principles of FESS and the possibilities offered by this kind of energy storage devices. The uses of FESS at domestic level include, but are not limited to: With the development of smart grid technology [3,35], FESS are intended to play a key role, especially for high cycling and fast dynamics applications. It is a promising alternative to battery energy storage systems in the near future.…”

Section: Discussionmentioning

confidence: 99%

A Lab-scale Flywheel Energy Storage System: Control Strategy and Domestic Applications

et al. 2020

Self Cite

View full text Add to dashboard Cite

Flywheel is a promising energy storage system for domestic application, uninterruptible power supply, traction applications, electric vehicle charging stations, and even for smart grids. In fact, recent developments in materials, electrical machines, power electronics, magnetic bearings, and microprocessors offer the possibility to consider flywheels as a competitive option for electric energy storage, which can be of great interest for domestic applications in the near future. In this paper, a grid-tied flywheel-based energy storage system (FESS) for domestic application is investigated with special focus on the associated power electronics control and energy management. In particular, the overall PMSM-based flywheel configuration is reviewed and a controlling strategy was experimentally implemented using DS1104 controller board from dSPACE. Two case studies were considered for power peak shaving and power backup at domestic level. A lab-scale prototype was built to validate the proposal. The achieved results are presented and discussed to demonstrate the possibilities offered by such an energy storage system for domestic application.

show abstract

“…Detailed ESS degradation is a complex process affected by many factors (e.g., temperature, depth of discharge, state of charge, charging/discharging rate, ESS application, type of ESS, manufacture of ESS, etc.) [35]. Nevertheless, the ESS degradation cost can be approximately formulated as a linear function of the charged and discharged energy [11], [36].…”

Section: B Microgrid Scheduling With Resiliency Constraintsmentioning

confidence: 99%

Robust Microgrid Scheduling With Resiliency Considerations

et al. 2020

View full text Add to dashboard Cite

A new microgrid scheduling model with resiliency guaranteed under the risk of both utility failure and prevailing uncertainties of renewable generation and load is proposed in this paper. The proposed model minimizes the overall operating cost of the microgrid by efficiently coordinating the power supply from local distributed energy resources and the main grid. The resiliency is ensured by maintaining certain amount of flexibility in local distributed energy resources, which can be quickly deployed to keep the power supply uninterrupted whenever the utility grid suddenly goes down. In addition, the uncertainties of renewable generation and load are captured with the proposed two-stage robust optimization model. By solving the proposed optimization, the solution not only guarantees the resiliency of the microgrid by supporting possible islanding incidents without load interruption, but also ensures robustness against the randomness of renewable generation and load. Results of case studies on a typical microgrid demonstrate the effectiveness of the presented robust microgrid scheduling model. INDEX TERMS Distributed generation, microgrid scheduling, resiliency, robust optimization, unintentional islanding. NOMENCLATURE The term (k) in the upper right position stands for the value of the symbol's k-th iteration. A bold symbol stands for its corresponding vector.

show abstract

Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations

Cited by 142 publications

References 44 publications

Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources

Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources

A Lab-scale Flywheel Energy Storage System: Control Strategy and Domestic Applications

Robust Microgrid Scheduling With Resiliency Considerations

Contact Info

Product

Resources

About