A Hybrid Technique for Day-Ahead PV Generation Forecasting Using Clear-Sky Models or Ensemble of Artificial Neural Networks According to a Decision Tree Approach

Massucco, S.; Mosaico, Gabriele; Saviozzi, M.; Silvestro, F.

doi:10.3390/en12071298

Cited by 37 publications

(19 citation statements)

References 49 publications

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“…Real measurements of local solar irradiance (in a time span 2005-2014) are used and converted into the expected PV power production according to [20]:…”

Section: B Inputsmentioning

confidence: 99%

An Efficiency-Based Power Management Strategy for an Isolated Microgrid Project

Conte¹,

D’Agostino²,

Grillo³

et al. 2022

Preprint

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The microgrids design for remote locations represents one of the most important and critical applications of the microgrid concept. It requires the correct sizing and the proper utilization of the different sources to guarantee the economical feasibility and the reliability of the supply. This study illustrates an efficiency-based power management strategy, designed for an undergoing microgrid project, where the sizing process of the resources (diesel generators, battery energy storage system, and PV plant) is obtained using a mixed-integer optimization algorithm. The proposed power management strategy guarantees the efficient exploitation of the power sources, which is one of the key elements of the optimal sizing process, being naturally included in the definition of the energy cost functions. The effectiveness of the power control strategy is validated by means of quasi-dynamic simulations on the complete microgrid model, where sources are defined by the optimal problem solution, while the cabling (size and length) and the main switchboards location reflect the expected system layout. Results obtained from the simulation of the microgrid electrical system include losses, and allow to verify and to highlight the desired quantities, such as the quality of supply at each busbar (voltage magnitude), and the state of charge of the energy storage system.

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“…Real measurements of local solar irradiance (in a time span 2005-2014) are used and converted into the expected PV power production according to [20]:…”

Section: B Inputsmentioning

confidence: 99%

An Efficiency-Based Power Management Strategy for an Isolated Microgrid Project

Conte¹,

D’Agostino²,

Grillo³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…For this reason, the implemented PV load predictor consists of a clear sky irradiance estimator (incl. a physical model) and a pretrained neural network that uses the proposed logical structure of Reference 38. The estimator is implemented by a physical model, which predicts AC output power using PV panel solar irradiance (see Figure 3).…”

Section: Modular Microgrid Simulation Framework Conceptmentioning

confidence: 99%

Co‐simulation framework for calculating balancing energy needs of a microgrid with renewable energy penetration

et al. 2021

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Summary This paper introduces a unique simulation framework for testing and validating multiple operation issues of grid connected microgrids. The framework is widely adjustable and enables various control actions, for example, load shedding, demand response, power curtailment, and integration of battery energy storage systems (BESS). The microgrid operation framework runs several algorithms, providing data for the optimization of the actors at different time scales. In the first part of the paper, the framework, three predictor algorithms, and the network topology used for the tests are presented in detail. Balancing power requirements of microgrids are dominantly determined by uncertainties of intermittent renewable energy‐based generation and changes in consumption. Beyond the environment development, the aim of the present research is to quantify the temporal change of balancing needs between certain confidence intervals. Accordingly, in the second part of the paper, possible approaches to determine the balancing power needs are presented, including the stochastic approach of the new System Operation Guideline (SO GL). The last part of the paper presents error characteristics of the predictor algorithms and balancing power needs are calculated in the context of the European balancing market terminology. Daily and seasonal temporality of errors is examined. The authors recognized that in transition to a more flexible distribution grid operation, the importance of possible microgrid market value propositions is increasingly appreciated. Future research perspectives include physical demonstration and validation of possible ancillary service strategy planning for microgrids.

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“…However, this is changing, and not only in Spain-solar energy generated by photovoltaic plants is being promoted more and more as an energy source, with the number of plants increasing globally [6]. These installations greatly improve issues related to the economy and the environment [7].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Soiling Losses from an Experimental Photovoltaic Plant Using Artificial Intelligence Techniques

2021

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Fossil fuels and their use to generate energy have multiple disadvantages, with renewable energies being presented as an alternative to this situation. Among them is photovoltaic solar energy, which requires solar installations that are capable of producing energy in an optimal way. These installations will have specific characteristics according to their location and meteorological variables of the place, one of these factors being soiling. Soiling generates energy losses, diminishing the plant’s performance, making it difficult to estimate the losses due to deposited soiling and to measure the amount of soiling if it is not done using very economically expensive devices, such as high-performance particle counters. In this work, these losses have been estimated with artificial intelligence techniques, using meteorological variables, commonly measured in a plant of these characteristics. The study consists of two tests, depending on whether or not the short circuit current (Isc) has been included, obtaining a maximum normalized root mean square error (nRMSE) lower than 7%, a correlation coefficient (R) higher than 0.9, as well as a practically zero normalized mean bias error (nMBE).

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A Hybrid Technique for Day-Ahead PV Generation Forecasting Using Clear-Sky Models or Ensemble of Artificial Neural Networks According to a Decision Tree Approach

Cited by 37 publications

References 49 publications

An Efficiency-Based Power Management Strategy for an Isolated Microgrid Project

An Efficiency-Based Power Management Strategy for an Isolated Microgrid Project

Co‐simulation framework for calculating balancing energy needs of a microgrid with renewable energy penetration

Estimation of Soiling Losses from an Experimental Photovoltaic Plant Using Artificial Intelligence Techniques

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