Microgrids: Enhancing the Resilience of the European Megagrid

Štrbac, Goran; Hatziargyriou, Nikos D.; Lopes, Jorge; Moreira, Carlos; Dimeas, Aris; Papadaskalopoulos, Dimitrios

doi:10.1109/mpe.2015.2397336

Cited by 134 publications

(95 citation statements)

References 2 publications

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“…By taking local control actions within the MG, the operational burden on the transmission system can be reduced. At the same time, grid resiliency can be increased, as the MG can ensure reliable power supply to local loads during faults in the main utility grid [8]. Due to these and other features, MGs have been identified as a promising approach to integrate large shares of renewable generation units and are foreseen to be essential components of future smart grids [8]- [11].…”

mentioning

confidence: 99%

Modeling, Analysis, and Experimental Validation of Clock Drift Effects in Low-Inertia Power Systems

Schiffer

Hans

Kral³

et al. 2017

IEEE Trans. Ind. Electron.

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Abstract-Clock drift in digital controllers is of great relevance in many applications. Since almost all real clocks exhibit drifts, this applies in particular to networks composed of several individual units, each of which being operated with its individual clock. In the present work, we demonstrate via extensive experiments on a microgrid in the megawatt-range that clock drifts may impair frequency synchronisation in low-inertia power systems. The experiments also show that-in the absence of a common clockthe standard model of an inverter as an ideal voltage source does not capture this phenomenon. As a consequence, we derive a suitably modified model of an inverter-interfaced unit that incorporates the phenomenon of clock drifts. By using the derived model, we investigate the effects of clock drifts on the performance of droop-controlled grid-forming inverters with regard to frequency synchronisation and active power sharing. The modelling and analysis is validated via extensive experiments on a microgrid in the megawattrange.Index Terms-Smart grid applications, low-inertia power systems, microgrids, grid-forming inverters, droop control, power sharing.

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mentioning

confidence: 99%

Modeling, Analysis, and Experimental Validation of Clock Drift Effects in Low-Inertia Power Systems

Schiffer

Hans

Kral³

et al. 2017

IEEE Trans. Ind. Electron.

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“…Since fossil-fueled power generation substantially contributes to greenhouse gas emissions, increasing efforts towards the exploration of renewable energy sources (RES) are being made. For example, the EU governments aim at achieving an emission reduction of at least 80% by 2050 [1]. As most of these renewable sources are small-scale distributed generation (DG) units, they are often connected at the low and medium voltage levels, rather than directly to the transmission system.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, there is an increasing amount of generation capacity present in the distribution network [2]. The efficient and reliable integration of these units requires the development of new operation concepts, amongst which the microgrid has been identified as one of the most promising [1]- [4].…”

Section: Introductionmentioning

confidence: 99%

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Towards a time-domain modeling framework for small-signal analysis of unbalanced microgrids

Ojo

Schiffer

2017

2017 IEEE Manchester PowerTech

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Abstract-Small-signal analysis is one of the most frequently used techniques to assess the operating conditions of power systems. Typically, this analysis is conducted by employing a phasorbased model of the power network derived under the assumption of balanced operating conditions. However, distribution networks and, amongst these, microgrids are often unbalanced. Hence, their analysis requires the development of tools and methods valid under such conditions. Motivated by this, we propose a modeling approach for generic nonlinear and unbalanced threephase microgrids, which allows to derive a small-signal model in a standard fashion. The approach is based on a time-domain decomposition of the electrical waveforms in positive and negative synchronous reference frames. The efficacy of the approach is demonstrated via application to an exemplary unbalanced microgrid.

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“…storage units, in order to support the economic operation of the future low-carbon power system [1]- [2]. However, the large number, small individual size and inherent stochasticity characterizing these DER have complicated system scheduling and market coordination.…”

mentioning

confidence: 99%

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2019

IEEE Trans. Sustain. Energy

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Abstract--The operation of aggregators of distributed energy resources (DER) is highly complex, since it entails the optimal coordination of a diverse portfolio of DER under multiple sources of uncertainty. The large number of possible stochastic realizations that arise, can lead to complex operational models that become problematic in real-time market environments. Previous stochastic programming approaches resort to two-stage uncertainty models and scenario reduction techniques to preserve the tractability of the problem. However, two-stage models cannot fully capture the evolution of uncertain processes and the a priori scenario selection can lead to suboptimal decisions. In this context, this paper develops a novel stochastic dual dynamic programming (SDDP) approach which does not require discretization of either the state space or the uncertain variables and can be efficiently applied to a multi-stage uncertainty model. Temporal dependencies of the uncertain variables as well as dependencies among different uncertain variables can be captured through the integration of any linear multidimensional stochastic model, and it is showcased for a porder vector autoregressive (VAR) model. The proposed approach is compared against a traditional scenario-tree-based approach through a Monte-Carlo validation process, and is demonstrated to achieve a better trade-off between solution efficiency and computational effort.Index Terms--Aggregator, distributed energy resources, multidimensional uncertainty, stochastic dual dynamic programming, vector autoregressive modeling. I. NOMENCLATURE A. IndexesIndex of time periods, running from 1 to . Index of energy storage (ES) units, running from 1 to . Index of flexible loads (FL), running from 1 to . Index of wind turbines (WT), running from 1 to . Index of micro-generators, running from 1 to . B. ParametersEnergy market price at period . Operating cost of micro-generator . Cost of demand shedding. C. VariablesPower sold to (positive)/bought from (negative) the market at period . ,Power output of micro-generator at period . Demand shed at period ., Energy level of ES unit at period . ,Power input (positive) / output (negative) of ES unit at period . , ℎChange of demand of FL at period due to load shifting. ,Demand of FL at period after load shifting., Dispatched wind power output of WT at period . II. INTRODUCTIONA. Background FUNDAMENTAL feature of the emerging Smart Grid paradigm involves the integration of a large number of distributed energy resources (DER) storage units, in order to support the economic operation of the future low-carbon power system [1]- [2]. However, the large number, small individual size and inherent stochasticity characterizing these DER have complicated system scheduling and market coordination. Furthermore, driven by the wide integration of renewable generation in power systems, there is a general consensus to move energy trading as close as possible to real-time [3]- [4], which intensifies the complexity of DER coordination. These challenges have...

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Microgrids: Enhancing the Resilience of the European Megagrid

Cited by 134 publications

References 2 publications

Modeling, Analysis, and Experimental Validation of Clock Drift Effects in Low-Inertia Power Systems

Modeling, Analysis, and Experimental Validation of Clock Drift Effects in Low-Inertia Power Systems

Towards a time-domain modeling framework for small-signal analysis of unbalanced microgrids

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

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