A survey of modelling and smart management tools for power grids with prolific distributed generation

Dkhili, Nouha; Eynard, Julien; Thil, Stéphane; Grieu, Stéphane

doi:10.1016/j.segan.2019.100284

Cited by 71 publications

(38 citation statements)

References 136 publications

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“…In fact, the decentralisation of power generation has made compliance with voltage constraints, current levels and voltage drop gradients increasingly difficult and has spawned a multitude of stability, quality and safety issues. The intermittency of solar power is poorly accounted for by conventional planning strategies for the daily operation of power grids and increases the complication of voltage regulation [1]. Therefore, grid stability has become dependent upon the successful compensation of supply/demand variation.…”

Section: Introductionmentioning

confidence: 99%

Multi-Horizon Forecasting of Global Horizontal Irradiance Using Online Gaussian Process Regression: A Kernel Study

et al. 2020

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In the present paper, global horizontal irradiance (GHI) is modelled and forecasted at time horizons ranging from 30 min to 48 h, thus covering intrahour, intraday and intraweek cases, using online Gaussian process regression (OGPR) and online sparse Gaussian process regression (OSGPR). The covariance function, also known as the kernel, is a key element that deeply influences forecasting accuracy. As a consequence, a comparative study of OGPR and OSGPR models based on simple kernels or combined kernels defined as sums or products of simple kernels has been carried out. The classic persistence model is included in the comparative study. Thanks to two datasets composed of GHI measurements (45 days), we have been able to show that OGPR models based on quasiperiodic kernels outperform the persistence model as well as OGPR models based on simple kernels, including the squared exponential kernel, which is widely used for GHI forecasting. Indeed, although all OGPR models give good results when the forecast horizon is short-term, when the horizon increases, the superiority of quasiperiodic kernels becomes apparent. A simple online sparse GPR (OSGPR) approach has also been assessed. This approach gives less precise results than standard GPR, but the training computation time is decreased to a great extent. Even though the lack of data hinders the training process, the results still show the superiority of GPR models based on quasiperiodic kernels for GHI forecasting.

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Section: Introductionmentioning

confidence: 99%

Multi-Horizon Forecasting of Global Horizontal Irradiance Using Online Gaussian Process Regression: A Kernel Study

et al. 2020

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“…where V WG represents gust wind speed (m/s), G max is the maximum wind speed (m/s) for gusts, T 1G is the start time for gusts (s), and T G represents the gust cycle (s) [14,27].…”

Section: Normal Wind Speedmentioning

confidence: 99%

“…Moreover, the output characteristics of wind power and its impact on grid power flow nodes after grid connection have been analyzed [13]. Voltage oscillation, power prediction, and other wind energy conversion system (WECS) control theories caused by wind power grid connection are hot topics [14]. In [15], the authors used a standard energy cost analysis method and presented the value cost analysis method to perform technical power generation assessments on six small, medium, and large WECSs with rated powers of 20, 35, 275, 500, 1000, and 2000 kW.…”

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confidence: 99%

Comparison of Small-Scale Wind Energy Conversion Systems: Economic Indexes

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Wind energy is considered as one of the most prominent sources of energy for sustainable development. This technology is of interest owing to its capability to produce clean, eco-friendly, and cost-effective energy for small-scale users and rural areas where grid power availability is insufficient. Wind power generation has developed rapidly in the past decade and is expected to play a vital role in the economic development of countries. Therefore, studying dominant economic factors is crucial to properly approach public and private financing for this emerging technology, as industrial growth and energy demands may outpace further economic studies earlier than expected. In this study, a strategy-focused method for performing economic analysis on wind energy based on financial net present value, levelized cost of energy, internal rate of return, and investment recovery period is presented. Numerical and simulation results depict the most optimal and economical system from a 3 and a 10 kW wind energy conversion system (WECS). Moreover, the aforementioned criteria are used to determine which WECS range is the most suitable investment with the shortest payback period. Finally, an economically viable and profitable wind energy system is recommended.

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“…A deep insight was provided on EMS secondary control to achieve economic benefits from MGs in Reference 16. An overview of several modelling aspects and control of smart power grids to analyse optimal power flow is presented in Reference 17. In Reference 18, various short‐term forecasting algorithms for power generation as well as load demand are reviewed to build an intelligent dispatch strategy for MGs.…”

Section: Introductionmentioning

confidence: 99%

Recent trends in power management strategies for optimal operation of distributed energy resources in microgrids: A comprehensive review

et al. 2020

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The current era in sustainable development is focused on the rapid integration of renewable energy sources driven by a wide range of socioeconomic objectives. Due to the inherent property of time-varying weather conditions, the intermittent sources, that is, Solar PV and Wind Energy, are considered as variable energy resources. The uncertainty and variability problem of these sources has brought many complications to distributed network operators to operate and control the complex or multi-microgrids with limited fast-ramping resources in order to maintain the power system flexibility. It led many researchers to find an alternative strategy since the conventional approaches are no longer adequate to handle the economic implications of operational decision making. At first, the brief review of various deterministic and probabilistic approaches, stochastic programming and robust optimisation strategies to address the uncertainty of variable energy resources are discussed. Furthermore, in the energy management point of view, the optimal scheduling problem of distributed sources of the microgrid is considered, and a brief review of optimisation models, advanced control strategies and demand response strategies to maximise economic benefits of microgrids are also elaborately presented. Finally, the multiagent-based distributed and decentralised control strategies for seamless integration of distributed generator units are reviewed under various configurations of the power grid along with communication network topologies.

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A survey of modelling and smart management tools for power grids with prolific distributed generation

Cited by 71 publications

References 136 publications

Multi-Horizon Forecasting of Global Horizontal Irradiance Using Online Gaussian Process Regression: A Kernel Study

Multi-Horizon Forecasting of Global Horizontal Irradiance Using Online Gaussian Process Regression: A Kernel Study

Comparison of Small-Scale Wind Energy Conversion Systems: Economic Indexes

Recent trends in power management strategies for optimal operation of distributed energy resources in microgrids: A comprehensive review

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