Two-Stage Robust Optimization for Resilient Operation of Microgrids Considering Hierarchical Frequency Control Structure

Mohiti, Maryam; Monsef, Hassan; Anvari‐Moghaddam, Amjad; Lesani, Hamid

doi:10.1109/tie.2019.2956417

Cited by 57 publications

(39 citation statements)

References 27 publications

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“…then decide the best way to achieve these points, according to controllers from their own manufacturers. The power generated by the Renewable Energy Sources (RESs) and the power demanded are the two major disturbances (sources of uncertainty) that operate on a micro-grid that could positively impact its EMS and economic performances [8], [9]. The challenges emerge from the inherent intermittent nature of renewable energy sources and the criteria for satisfying the variable demand for energy.…”

Section: A Background and Motivationmentioning

confidence: 99%

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Impact of Incorporating Disturbance Prediction on the Performance of Energy Management Systems in Micro-Grid

Gbadega

Saha

2020

IEEE Access

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The design and implementation of appropriate advanced control strategies is a key factor for the effective integration of micro-grids into the electrical network. In view of this, the study proposes an Adaptive Model-Based Horizon Control technique in the bid to addressing issues related to the Energy Management System in micro-grid operations. The main objective of the energy management system is to balance energy generation and demand through energy storage, so as to optimize the operation of the microgrid with high penetrations of renewable energy sources. This paper further investigates the impacts of considering the prediction of disturbances on the performance of the Energy Management System based on the adaptive model predictive control algorithm in order to improve the operating costs of the micro-grid with hybrid-energy storage systems. The adaptive model predictive control algorithm solves the energy optimization problem in a renewable energy-based micro-grid with various types of energy storage systems that exchange energy with the host grid. More so, this optimization problem is resolved at each sampling period in order to determine the minimum running costs while satisfying demand and taking into account technical and physical constraints. The simulation results under different conditions have demonstrated how the use of an adaptive model predictive control based energy management system can enhance micro-grid operation, provided there is effective forecasting, and consequently minimized the running operating costs of micro-grid. More so, it is evident in the cost function, , obtained from the three scenarios conducted, that the perfect knowledge of the disturbance prediction is essential for effective micro-grid operations.

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Section: A Background and Motivationmentioning

confidence: 99%

“…Considering temperature variations, an improved equation to describe the saturation current is obtained from Equations (9) and (10), which admits expression as [54]:…”

Section: A Photovoltaic System Modelingmentioning

confidence: 99%

Impact of Incorporating Disturbance Prediction on the Performance of Energy Management Systems in Micro-Grid

Gbadega

Saha

2020

IEEE Access

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“…In this paper, it can be transformed into a max-max problem by dual theory. Let θ ik , μ ik , λ ik 1 , λ ik 2 , π ik 1 , π ik 2 , γ i , e ik 1 , e ik 2 , v ik , ϕ i jk 1 , ϕ i jk 2 , ϕ i jk 3 , l ik 1 , l ik 2 , ξ ik be dual variables for constraints (1), (2), (13), (14), (17), (20), (22), (27) and (29). Dual constraints can be obtained as follows:…”

Section: Appendixmentioning

confidence: 99%

“…Thus, in NI-TRO-ES, the items related to the energy transaction between MGs in the optimisation objective (35) and constraints (19)- (22) are deleted. The unchanged items are omitted and the changed items of NI-TRO-ES are shown below: (i) Power balance of every MG in NI-TRO-ES The other constraints (1)-(4), (7)-(9), (12)- (17), (24), (25), (27), (28) and the uncertainty sets U remain unchanged.…”

Section: Appendixmentioning

confidence: 99%

Two‐stage robust optimal scheduling of cooperative microgrids based on expected scenarios

Sang

Zhang

Liu

et al. 2020

IET gener. transm. distrib.

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Cooperative microgrids (CMGs) can effectively solve the energy interaction between microgrids (MGs) while increasing the penetration rate of renewable energy systems (RESs) and reducing the interaction frequency with the grid. However, the uncertainty of RESs will bring new challenges to the energy management and economic dispatch of CMGs, especially in increasing the number of MGs connected to the grid. Taking into account this uncertainty, it is extremely unlikely that the forecast uncertainty information will be at the worst values in every period, and this forecast uncertainty information is near the expected values in most cases. Therefore, a two-stage robust optimal model under expected scenarios for CMGs is proposed in this study to improve the conservatism of traditional models and minimise the daily cost. In this model, the firststage decision results (FDRs) are determined by minimising the daily cost of CMGs under the expected scenarios. The proposed model is transformed based on two-stage zero-sum game theory and dual theory, a column and constraint generation algorithm is first used to test the robust feasibility of the FDR, and the second-stage decision results can be obtained without changing the FDR. Case studies verify that the proposed model can effectively solve energy transactions between MGs while mitigating the uncertainty disturbances in the operation of CMGs. − k, i fluctuating power that MG i sells to grid at time k

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“…The authors tried to manage the active power reserve in the isolated MGs. In [6], the resilient operation of MGs is investigated by two‐stage robust optimisation considering the uncertainty of loads and renewable generation (RG). The proposed model optimises the cost of MG while preventing load shedding under the worst‐case condition.…”

Section: Introductionmentioning

confidence: 99%

Optimal hierarchical energy management scheme for networked microgrids considering uncertainties, demand response, and adjustable power

Movahednia

Karimi

Jadid

2020

IET Generation, Transmission & Distribution

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Two-Stage Robust Optimization for Resilient Operation of Microgrids Considering Hierarchical Frequency Control Structure

Cited by 57 publications

References 27 publications

Impact of Incorporating Disturbance Prediction on the Performance of Energy Management Systems in Micro-Grid

Impact of Incorporating Disturbance Prediction on the Performance of Energy Management Systems in Micro-Grid

Two‐stage robust optimal scheduling of cooperative microgrids based on expected scenarios

Optimal hierarchical energy management scheme for networked microgrids considering uncertainties, demand response, and adjustable power

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