Energy and Frequency Hierarchical Management System Using Information Gap Decision Theory for Islanded Microgrids

Rezaei, Navid; Ahmadi, Abdollah; Khazali, Amirhossein; Guerrero, Josep M.

doi:10.1109/tie.2018.2798616

Cited by 84 publications

(40 citation statements)

References 28 publications

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“…It should be note that, the proposed model is a day‐ahead energy and reserve scheduling, it is assumed that all the transients and oscillatory modes are damped. Indeed, the frequency of the multi‐MGs system is settled into a steady‐state equilibrium point which is associated with the hourly frequency 41…”

Section: Resultsmentioning

confidence: 99%

A stochastic frequency security constrained optimization model for day‐ahead energy and reserve scheduling of islanded multi‐microgrids systems

Sarcheshmeh

Taher

Mazidi

2020

Int Trans Electr Energ Syst

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Summary Small size of microgrids (MGs), low inertia, and small scale of distributed generations, and high intermittent energy delivery of renewable generations, make the frequency security an important issue in the islanded multi‐microgrids (IMMG) systems which should be considered subject to the techno‐economic constraints of MGs. Motivated by this need, this article proposes a two‐stage stochastic optimization model for day‐ahead energy and reserve scheduling of IMMG systems. The objective of the proposed model is to minimize total operation cost of IMMG while the frequency security of system is preserved within a predefined range. To this end, the hierarchical frequency structure of IMMG system including primary, secondary, and tertiary control levels are precisely formulated in mixed‐integer linear programming format which can be efficiently solved by optimization software package. Meanwhile, to promote the proposed model, responsive loads and energy storage systems are considered in the energy and reserve scheduling problem. The proposed model is applied to a typical IMMG system to optimize energy and reserve scheduling over 24‐hr horizon. The obtained results verify that through the proposed model, the operation costs of MGs are minimized while frequency security of the system is preserved in a cost‐effective manner.

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Section: Resultsmentioning

confidence: 99%

A stochastic frequency security constrained optimization model for day‐ahead energy and reserve scheduling of islanded multi‐microgrids systems

Sarcheshmeh

Taher

Mazidi

2020

Int Trans Electr Energ Syst

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“…The approach covers MGs attitude toward risk for upstream grid price uncertainty modeling. Rezaei et al [32] presented a MILP framework to manage frequency excursions produced from load and renewable generation fluctuations. They firstly formulate the frequency-dependent behavior of the distributed energy resources and, then, utilize the IGDT to handle MGs uncertainties in a robust way.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust bi-level risk-based optimal scheduling of microgrid operation against uncertainty

2020

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The model introduced in this paper is the first to propose a decentralized robust optimal scheduling of MG operation under uncertainty and risk. The power trading of the MG with the main grid is the first stage variable and power generation of DGs and power charging/discharging of the battery are the second stage variables. The uncertain term of the initial objective function is transformed into a constraint using robust optimization approach. Addressing the Decision Maker’s (DMs) risk aversion level through Conditional Value at Risk (CVaR) leads to a bi-level programming problem using a data-driven approach. The model is then transformed into a robust single-level using Karush–Kahn–Tucker (KKT) conditions. To investigate the effectiveness of the model and its solution methodology, it is applied on a MG. The results clearly demonstrate the robustness of the model and indicate a strong almost linear relationship between cost and the DMs various levels of risk aversion. The analysis also outlines original characterization of the cost and the MGs behavior using three well-known goodness-of-fit tests on various Probability Distribution Functions (PDFs), Beta, Gumbel Max, Normal, Weibull, and Cauchy. The Gumbel Max and Normal PDFs, respectively, exhibit the most promising goodness-of-fit for the cost, while the power purchased from the grid are well fitted by Weibull, Beta, and Normal PDFs, respectively. At the same time, the power sold to the grid is well fitted by the Cauchy PDF.

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“…Load uncertainty problem is investigated in [78] in which risk-based expansion planning of transmission line has been evaluated under uncertain behavior of load. In [79], a novel optimization framework has been presented for uncertainty-based energy management of an islanded microgrid in which IGDT methodology has been implemented to consider the un-certainties of renewable units generation and energy demand. In [80], uncertainty modeling of transmission line overload has been assessed using IGDT in which robust performance of power system has been obtained for the cases line experiences overload.…”

Section: • Transmission and Distribution Sectormentioning

confidence: 99%

Application of information gap decision theory in practical energy problems: A comprehensive review

2019

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The uncertainty and risk modeling is a hot topic in operation and planning of energy systems. The system operators and planners are decision makers that need to handle the uncertainty of input data of their models. As an example, energy consumption has always been a critical problem for operators since the forecasted values, and the actual consumption is never expected to be the same. The penetration of renewable energy resources is continuously increasing in recent and upcoming years.These technologies are not dispatch-able and are highly dependent on natural resources. This would make the real-time energy balancing more complicated. Another source of uncertainty is related to energy market prices which are determined by the market participants' behaviors. To consider these issues, the uncertainty modeling should be performed. Various approaches have been previously utilized to model the uncertainty of these parameters such as probabilistic approaches, possibilistic approaches, hybrid possibilisticprobabilistic approach, information gap decision theory, robust and interval optimization techniques. This paper reviews the research works that used information gap decision theory for uncertainty modeling in energy and power systems.

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Energy and Frequency Hierarchical Management System Using Information Gap Decision Theory for Islanded Microgrids

Cited by 84 publications

References 28 publications

A stochastic frequency security constrained optimization model for day‐ahead energy and reserve scheduling of islanded multi‐microgrids systems

A stochastic frequency security constrained optimization model for day‐ahead energy and reserve scheduling of islanded multi‐microgrids systems

Robust bi-level risk-based optimal scheduling of microgrid operation against uncertainty

Application of information gap decision theory in practical energy problems: A comprehensive review

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