Microgrid Energy Management Combining Sensitivities, Interval and Probabilistic Uncertainties of Renewable Generation and Loads

Mohan, Vivek; Suresh, R.; Singh, Jai Govind; Ongsakul, Weerakorn; Madhu, Nimal

doi:10.1109/jetcas.2017.2679030

Cited by 54 publications

(30 citation statements)

References 20 publications

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“…However, in some peak load intervals, even though all DG units are set at the maximum values, the power supply cannot fulfill the load amount. Some load is shed to maintain the power balance in the MG system (intervals [18][19][20][21][22][23]. Figure 13 represents the response of all components when the MG switches to the islanded mode.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Moreover, due to the influence of uncertain factors such as intermittent fluctuations in renewable energy sources (RESs) and faults [17,18], these equipment may connect/disconnect to/from the MG system. In these cases, EMSs could not automatically update the device characteristics, or adjust operation algorithms to adapt to new operation mode [16,19].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System

2017

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Monitoring the status of existing devices and identification of newly added devices is required in microgrids to adjust the operation schedule followed by any event or integration of a new device. Therefore, in this paper, automatic reconfiguration of microgrids is considered after the addition of a new device or change in the operation status of an existing device by using a multiagent system. This capability of the microgrid is named as auto-configuration function, which is performed by the auto-configurator agent. In case of addition of a new device, the auto-configurator agent is responsible for authorization and registration of the newly added device. In case of change in status of any existing device, the status information is updated. After integration of a new device or change in status of an existing device, re-optimization is carried out by the energy management system (EMS) agent. Agent communication language (ACL) is used to develop a modified contract net protocol (MCNP) for communication among different agents. EMS agent and auto-configurator agent exchange information for economic rescheduling of the microgrid components. Simulation results have shown that the proposed method can be used for optimal operation of microgrids when the configuration changes due to the addition/removal of a device.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System

2017

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“…Meanwhile, output power from renewable energy resources are shown in Fig. 6 [34]. For the selected operating condition, the heaviest net demand day is chosen to ensure that the sizing is adequate for other less loaded conditions.…”

Section: Case Studiesmentioning

confidence: 99%

Sizing battery storage for islanded microgrid systems to enhance robustness against attacks on energy sources

Lai

Wang

Shi

et al. 2019

J. Mod. Power Syst. Clean Energy

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Power system security against attacks is drawing increasing attention in recent years. Battery energy storage systems (BESSs) are effective in providing emergency support. Although the benefits of BESSs have been extensively studied earlier to improve the system economics, their role in enhancing the system robustness in overcoming attacks has not been adequately investigated. This paper addresses the gap by proposing a new battery storage sizing algorithm for microgrids to limit load shedding when the energy sources are attacked. Four participants are considered in a framework involving interactions between a robustness-oriented economic dispatch model and a bilevel attacker-defender model. The proposed method is tested with the data from a microgrid system in Kasabonika Lake of Canada. Comprehensive case studies are carried out to demonstrate the effectiveness and merits of the proposed approach.

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“…The outputs of the wind power and photovoltaics could be estimated within a range by the PDF equations shown in (5) and (7) at a specified confidence level [32]. It is assumed that the error between the estimated and actual outputs follows the normal distribution [33].…”

Section: Modeling Of Uncertaintiesmentioning

confidence: 99%

Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading

Liu

Zheng

et al. 2018

Energies

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Abstract:The implementation of demand response (DR) could contribute to significant economic benefits meanwhile simultaneously enhancing the security of the concerned power system. A well-designed carbon emission trading mechanism provides an efficient way to achieve emission reduction targets. Given this background, a virtual power plant (VPP) including demand response resources, gas turbines, wind power and photovoltaics with participation in carbon emission trading is examined in this work, and an optimal dispatching model of the VPP presented. First, the carbon emission trading mechanism is briefly described, and the framework of optimal dispatching in the VPP discussed. Then, probabilistic models are utilized to address the uncertainties in the predicted generation outputs of wind power and photovoltaics. Demand side management (DSM) is next implemented by modeling flexible loads such as the chilled water thermal storage air conditioning systems (CSACSs) and electric vehicles (EVs). On this basis, a mixed integer linear programming (MILP) model for the optimal dispatching problem in the VPP is established, with an objective of maximizing the total profit of the VPP considering the costs of power generation and carbon emission trading as well as charging/discharging of EVs. Finally, the developed dispatching model is solved by the commercial CPLEX solver based on the YALMIP/MATLAB (version 8.4) toolbox, and sample examples are served for demonstrating the essential features of the proposed method.

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Microgrid Energy Management Combining Sensitivities, Interval and Probabilistic Uncertainties of Renewable Generation and Loads

Cited by 54 publications

References 20 publications

Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System

Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System

Sizing battery storage for islanded microgrid systems to enhance robustness against attacks on energy sources

Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading

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