Rule-based Energy Management System in an Experimental Microgrid with the Presence of Time of Use Tariffs

Moghimi, Mojtaba; Leskarac, Domagoj; Bennett, Christopher J.; Lu, Junwei; Stegen, Sascha

doi:10.1051/matecconf/20167010011

Cited by 13 publications

(11 citation statements)

References 14 publications

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“…The rule-based EMS determines the charge/discharge of energy storage system. The details of EMS are explained in [41]. Considering Time of Use (ToU) tariffs, load level and State of Charge (SOC) of battery, EMS decides during one day when the best time to charge and discharge is.…”

Section: 243mentioning

confidence: 99%

“…The peak shaving algorithm provides maximum benefits of energy storage scheduling. The discharge algorithm follows three steps as mentioned in [41]:…”

Section: 243mentioning

confidence: 99%

“…The modeling and simulation of EMS are based on the real data extracted from the H-MG via communication and monitoring system. A Rule-based scheduling algorithm developed in [41] has been explained in previous sections. This algorithm is employed as the basis for the tertiary control simulation in this section.…”

Section: Simulation Of H-mg Testing Facility Control and Management Smentioning

confidence: 99%

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Hybrid AC/DC Microgrid testing facility for energy management in commercial buildings

Leskarac

Moghimi

Liu

et al. 2018

Energy and Buildings

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With ever increasing energy generation diversity and energy storage becoming affordable, distribution networks are becoming more complex than ever before. This complexity can be utilized to benefit the distribution networks as well as end consumers in the form of controlled Microgrids. Microgrids are not simply distributed generation and energy storage systems; solar systems and battery banks, rather a complete design of hardware and software for specific uses and users. All the different elements need to be designed to work together to provide stable, efficient and sustainable power delivery to the end user. An experimental Hybrid-Microgrid testing facility is presented in this paper that implements highefficiency distribution architectures combining both AC and DC networks. This testing facility provides a research testbed for investigating different aspects of Microgrid systems, employing a total of 15.5 kW of reconfigurable Solar PV and 80 kWh of lithium energy storage on a 145 kVA commercial building load located at Griffith University. Implementation results along with control system simulation results are presented in this paper for distributed renewable generation, Static Synchronous Compensators, advanced control methodologies and forecasting methods for energy management purposes.

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Section: 243mentioning

confidence: 99%

“…The peak shaving algorithm provides maximum benefits of energy storage scheduling. The discharge algorithm follows three steps as mentioned in [41]:…”

Section: 243mentioning

confidence: 99%

Section: Simulation Of H-mg Testing Facility Control and Management Smentioning

confidence: 99%

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Hybrid AC/DC Microgrid testing facility for energy management in commercial buildings

Leskarac

Moghimi

Liu

et al. 2018

Energy and Buildings

Self Cite

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“…These supervisory controllers are often referred to as energy management systems (EMS), see e.g. [29]. The EMS then relies on low-level controllers that actually control the producers and energy distribution in the MES.…”

Section: Introductionmentioning

confidence: 99%

Progressive hedging for stochastic energy management systems

et al. 2020

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Energy systems have increased in complexity in the past years due to the everincreasing integration of intermittent renewable energy sources such as solar thermal or wind power. Modern energy systems comprise different energy domains such as electrical power, heating and cooling which renders their control even more challenging. Employing supervisory controllers, so-called energy management systems (EMSs), can help to handle this complexity and to ensure the energy-efficient and cost-efficient operation of the energy system. One promising approach are

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“…However, to achieve the full benefits of energy storage system, an EMS, which is a forecasting and scheduling algorithm, should be utilized [33]. Thus, the EMS plays a significant role in smoothing the power fluctuation in grid-connected household nano-grid system and optimizing power dispatch of energy storage system.…”

Section: Energy Storage Systemmentioning

confidence: 99%

Energy Management Strategy of PV Grid-Connected Household Nano-Grid System

Ding¹

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This thesis investigates the long-term optimal scheduling algorithm proposed for the energy storage system, to better organize charging/discharging action of battery for the economic operation in a PV grid-connected household nano-grid system. To fulfill this goal, the household nano-grid is modeled, including PV module, energy storage system, DC/AC inverter and their corresponding controllers. Battery is used to execute the optimal power command scheduled by long-term optimal scheduling algorithm. The optimal power scheduling algorithm is based on the rolling optimization method, which can realize the minimum operational cost of the PV nano-grid system. Moreover, a smoothing function is introduced to alleviate the power fluctuation of the exchanging power between PV nanogrid system and the main power grid caused by PV and residential loads. The validity of the proposed energy management strategy in upper Energy Management System (EMS) has been examined using simulations in MATLAB/Simpower. iii Acknowledgements I would first like to express my sincere gratitude to my Professor Xiaoyu Wang for his suggestion, instruction and guidance of my Master study and research. His invaluable guidance, constant encouragement inspires me a lot when I was troubled with difficulties. Without his continuous support and care, it would have not been possible to complete this thesis. I would also show my warm thank to the colleagues in my research group:

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Rule-based Energy Management System in an Experimental Microgrid with the Presence of Time of Use Tariffs

Cited by 13 publications

References 14 publications

Hybrid AC/DC Microgrid testing facility for energy management in commercial buildings

Hybrid AC/DC Microgrid testing facility for energy management in commercial buildings

Progressive hedging for stochastic energy management systems

Energy Management Strategy of PV Grid-Connected Household Nano-Grid System

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