Steady-State Security Region of Energy Hub: Modeling, Calculation, and Applications

Yong, Pei; Wang, Yi; Capuder, Tomislav; Tan, Zhenfei; Zhang, Ning; Chen, Kang

doi:10.46855/2020.05.02.05.43.191753

Cited by 1 publication

(3 citation statements)

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“…Voltage magnitude limits are satisfied by (15) and (16) at the MMG operator level and each MG, respectively. The power flow limits of the electrical lines at the MMG operator level and each MG are expressed by (17) and (18), respectively.…”

Section: Electrical Network Constraintsmentioning

confidence: 99%

“…Although system security alongside its optimal operation in MCES is discussed in [9][10][11][12][13][14][15][16][17][18][19][20][21][22], these methods have been proposed for implementation in conventional power systems in the presence of energy hubs. In other words, these methods are not suitable for the optimal and secure operation of an MCMMG.…”

Section: Introductionmentioning

confidence: 99%

“…In [16], a two‐time scale model is presented to determine the steady‐state security region. In [17], a security region is defined for the safe operation of an MCES based on the steady‐state operational and security constraints. A security‐constrained model is proposed in [18] for the optimal operation of integrated electricity and NG networks.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized risk‐based security‐constrained optimal power flow in interconnected multi‐carrier microgrids

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The security of energy systems has always been one of the most important issues of energy systems operation. The multi-carrier multi-microgrid (MCMMG) is one of the novel structures in the power system. High penetration of renewable resources and their uncertainty, their ability to operate in isolation mode, and the presence of energy hubs in MCMMG systems increase the importance of security assessment in this type of system. This paper presents a decentralized risk-based security-constrained optimal power flow model for an MCMMG system. The stochastic nature of wind energy, photovoltaic generation, and electrical and heating loads are considered in the proposed model. In the model, the risk level of the system is determined by considering both the electrical and natural gas (NG) networks' contingencies. The proposed model is decomposed into three types of subproblems with the augmented Lagrangian relaxation (ALR) method: The subproblem related to the multi-microgrid operator level, the NG network subproblem, and the individual microgrid level subproblem. The decomposed problem is solved using MATLAB software. According to the results, the proposed model can secure the system from high costs that may impose on the system due to the contingency occurrence.

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