Optimal scheduling of microgrid operation considering the time-of-use price of electricity

Mahmoodi, Mostafa; Shamsi, Pourya; Fahimi, Babak

doi:10.1109/iecon.2013.6699460

Cited by 12 publications

(6 citation statements)

References 19 publications

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“…To order to demonstrate the effectiveness of the presented power scheduling operation, the proposed work was implemented in python programming language on a personal computer , [29] and [26], respectively. The power service territory of the IoE is separated into three geographical regions that mimicked three types of population distribution in the real world.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…, ℎ and , , ℎ represent the battery degradation cost owing to charging/discharging operation [25]. Binary values of , stands for the Time-of-Use (ToU) [26] electricity cost charged for the prosumers at the ith microgrid in real time. and ρ stand for the off-peak electricity price and the weighting factor of the peak-hour electricity purchase cost of the prosumers at the ith microgrid, respectively.…”

Section: (Iii)mentioning

confidence: 99%

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An Emission-Aware Day-Ahead Power Scheduling System for Internet of Energy

2019

KSII TIIS

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As a subset of the Internet of Things, the Internet of Energy (IoE) is expected to tackle the problems faced by the current smart grid framework. Notably, the conventional day-ahead power scheduling of the smart grid should be redesigned in the IoE architecture to take into consideration the intermittence of scattered renewable generations, large amounts of power consumption data, and the uncertainty of the arrival time of electric vehicles (EVs).Accordingly, a day-ahead power scheduling system for the future IoE is proposed in this research to maximize the usage of distributed renewables and reduce carbon emission caused by the traditional power generation. Meanwhile, flexible charging mechanism of EVs is employed to provide preferred charging options for moving EVs and flatten the load profile simultaneously. The simulation results revealed that the proposed power scheduling mechanism not only achieves emission reduction and balances power load and supply effectively, but also fits each individual EV user's preference.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Section: (Iii)mentioning

confidence: 99%

An Emission-Aware Day-Ahead Power Scheduling System for Internet of Energy

2019

KSII TIIS

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“…There are 900 houses/buildings in the third region, in which 810 residents have renewables, EVs, and battery storage systems. Notably, time of use (ToU) is adopted to determine the real‐time electricity price in this work. ToU is broken into three structures or groupings with various names in reference to peak, off peak, and the time of moderate use referred to as shoulder time or mid‐peak.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

An emission‐aware real‐time power scheduling system for the Internet of Energy

Huang

Liu

2019

Int Trans Electr Energ Syst

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Summary In the recent literature, the architecture of the Internet of Energy (IoE) has been proposed to replace the current smart grid in the future. However, the large volume of energy produced, the copious amounts of accompanying consumption data, and the uncertainties germane to intermittent energy sources will result in the real‐time energy management of the IoE in the future being much more difficult to deal with than that of traditional centralized‐controlled power generation systems. In this work, a real‐time power scheduling system based on the architecture of the IoE is proposed to tackle the complicated real‐time energy management problems. We divide the whole power network into different geographical regional grids under a hierarchical framework, and the scheduling process is activated at the regional grid if a power shortage is estimated to happen during a fixed time period ahead. After electricity consumption data and renewable generation data are collected at the prosumer level, the governing regional grid schedules the usage of electricity for the prosumers by considering the efficiency of the use of distributed renewables and the peak shaving of the electricity load. Excess electricity generated in a regional grid is allowed to be allocated to others facing power supply shortages, whereby a reduction of emissions during peak load periods and the maximal utilization of distributed renewables can be achieved. Notably, the charging management of moving electric vehicles is also included in the proposed power scheduling mechanism. The simulation results reveal that the proposed real‐time power scheduling system for the IoE can efficiently utilize renewable generation, lessen the demand of traditional power, and balance peak and off‐peak period loads in an electricity market in real time.

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“…The authors used the popular Hybrid Optimization Model for Electric Renewable (HOMER) software version 3.13.3 for comprehensive net present cost modeling, simulation, and optimization, encompassing both traditional and renewable power sources, energy storage systems, and loads. Similarly, the authors in [99] proposed a scheduling technique for dispatching energy storage units in MGs, incorporating real-time electricity pricing into the model. Their strategy also accounted for the initial stored energy levels as a variable in the optimization process, rather than a predetermined value.…”

Section: Time-of-use (Tou) Pricingmentioning

confidence: 99%

Interconnected Smart Transactive Microgrids—A Survey on Trading, Energy Management Systems, and Optimisation Approaches

Machele,

Onumanyi,

Abu-Mahfouz

et al. 2024

JSAN

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The deployment of isolated microgrids has witnessed exponential growth globally, especially in the light of prevailing challenges faced by many larger power grids. However, these isolated microgrids remain separate entities, thus limiting their potential to significantly impact and improve the stability, efficiency, and reliability of the broader electrical power system. Thus, to address this gap, the concept of interconnected smart transactive microgrids (ISTMGs) has arisen, facilitating the interconnection of these isolated microgrids, each with its unique attributes aimed at enhancing the performance of the broader power grid system. Furthermore, ISTMGs are expected to create more robust and resilient energy networks that enable innovative and efficient mechanisms for energy trading and sharing between individual microgrids and the centralized power grid. This paradigm shift has sparked a surge in research aimed at developing effective ISTMG networks and mechanisms. Thus, in this paper, we present a review of the current state-of-the-art in ISTMGs with a focus on energy trading, energy management systems (EMS), and optimization techniques for effective energy management in ISTMGs. We discuss various types of trading, architectures, platforms, and stakeholders involved in ISTMGs. We proceed to elucidate the suitable applications of EMS within such ISTMG frameworks, emphasizing its utility in various domains. This includes an examination of optimization tools and methodologies for deploying EMS in ISTMGs. Subsequently, we conduct an analysis of current techniques and their constraints, and delineate prospects for future research to advance the establishment and utilization of ISTMGs.

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Optimal scheduling of microgrid operation considering the time-of-use price of electricity

Cited by 12 publications

References 19 publications

An Emission-Aware Day-Ahead Power Scheduling System for Internet of Energy

An Emission-Aware Day-Ahead Power Scheduling System for Internet of Energy

An emission‐aware real‐time power scheduling system for the Internet of Energy

Interconnected Smart Transactive Microgrids—A Survey on Trading, Energy Management Systems, and Optimisation Approaches

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