A Semi-Markov Model for Control of Energy Storage in Utility Grids and Microgrids With PV Generation

Barnes, Arthur K.; Balda, Juan Carlos; Escobar-Mejía, Andrés

doi:10.1109/tste.2015.2393353

Cited by 55 publications

(19 citation statements)

References 27 publications

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“…By providing such forecasts, nowcasting systems can help the power plant to fulfill these ramp rate regulations. Moreover, they help to optimize the required size and the operations of combined PV‐battery systems . Thus, optimized operations potentially increase the lifespan of electrical storages and auxiliary devices …”

Section: Introduction Aim and Approachmentioning

confidence: 99%

Validation of an all‐sky imager–based nowcasting system for industrial PV plants

Kuhn¹,

Nouri²,

Wilbert³

et al. 2017

Progress in Photovoltaics

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International audienceBecause of the cloud-induced variability of the solar resource, the growing contributions of photovoltaic plants to the overall power generation challenges the stability of electricity grids. To avoid blackouts, administrations started to define maximum negative ramp rates. Storages can be used to reduce the occurring ramps. Their required capacity, durability, and costs can be optimized by nowcasting systems. Nowcasting systems use the input of upward-facing cameras to predict future irradiances. Previously, many nowcasting systems were developed and validated. However, these validations did not consider aggregation effects, which are present in industrial-sized power plants. In this paper, we present the validation of nowcasted global horizontal irradiance (GHI) and direct normal irradiance maps derived from an example system consisting of 4 all-sky cameras (“WobaS-4cam”). The WobaS-4cam system is operational at 2 solar energy research centers and at a commercial 50-MW solar power plant. Besides its validation on 30 days, the working principle is briefly explained. The forecasting deviations are investigated with a focus on temporal and spatial aggregation effects. The validation found that spatial and temporal aggregations significantly improve forecast accuracies: Spatial aggregation reduces the relative root mean square error (GHI) from 30.9% (considering field sizes of 25 m2) to 23.5% (considering a field size of 4 km2) on a day with variable conditions for 1 minute averages and a lead time of 15 minutes. Over 30 days of validation, a relative root mean square error (GHI) of 20.4% for the next 15 minutes is observed at pixel basis (25 m2). Although the deviations of nowcasting systems strongly depend on the validation period and the specific weather conditions, the WobaS-4cam system is considered to be at least state of the art

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Section: Introduction Aim and Approachmentioning

confidence: 99%

Validation of an all‐sky imager–based nowcasting system for industrial PV plants

Kuhn¹,

Nouri²,

Wilbert³

et al. 2017

Progress in Photovoltaics

View full text Add to dashboard Cite

show abstract

“…In [109], a semi Markov model for control of energy storage is proposed in the case of high penetration of PV power in utility grid as well as microgrids. This model exhibits wide range of applications like utilization of PV in small and large timescales, short term forecasting of PV power and stochastic scheduling in coordination with ESDs and other resources including ultra-capacitors.…”

Section: Discussion and Future Research Directionsmentioning

confidence: 99%

A Review of Strategies to Increase PV Penetration Level in Smart Grids

Aleem

Hussain²,

Ustun³

2020

Energies

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Due to environmental concerns, power system generation is shifting from traditional fossil-fuel resources to renewable energy such as wind, solar and geothermal. Some of these technologies are very location specific while others require high upfront costs. Photovoltaic (PV) generation has become the rising star of this pack, thanks to its versatility. It can be implemented with very little upfront costs, e.g., small solar home systems, or large solar power plants can be developed to generate MWs of power. In contrast with wind or tidal generation, PV can be deployed all around the globe, albeit with varying potentials. These merits have made PV the renewable energy technology with highest installed capacity around the globe. However, PV penetration into the grid comes with its drawbacks. The inverter-interfaced nature of the PV systems significantly impacts the power system operation from protection, power flow and stability perspectives. There must be strategies to mitigate these negative impacts so that PV penetration into the grid can continue. This paper gives a thorough overview of such strategies from different research fields: such as communication, artificial intelligence, power electronics and electric vehicle charging coordination. In addition, possible research directions are given for future work.

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“…We model this problem as a FHMDP due to the following reasons： 1. The natural uncertainties and randomness of the load and PV can be described by Markov models as in numerous MGs and smart grid research [33][34][35][36].…”

Section: Mathematical Model and Optimization Methodsmentioning

confidence: 99%

Active Power Dispatch Optimization for a Grid-Connected Microgrid with Uncertain Multi-Type Loads

Tang²,

et al. 2016

Preprint

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An active power dispatch method for a microgrid (MG) with multi-type loads, renewable energy sources (RESs) and distributed energy storage devices (DESDs) is the focus of this paper. The MG operates in a grid-connected model, and distributed power sources contribute to the service for load demands. The outputs of multiple DESDs are controlled to optimize the active power dispatch. Our goal with optimization is to reduce the economic cost under time-of-use (TOU) price, and to adjust the excessively high or low load rate of distributed transformers (DTs) caused by the peak-valley demand and load uncertainties. To simulate a practical environment, the stochastic characteristics of multi-type loads are formulated. The transition matrix of system state is provided. Then, a finite-horizon Markov decision process (FHMDP) model is established to describe the dispatch optimization problem. A learning-based technique is adopted to search the optimal joint control policy of multiple DESDs. Finally, simulation experiments are performed to validate the effectiveness of the proposed method, and the fuzzification analysis of the method is presented. Keywords

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A Semi-Markov Model for Control of Energy Storage in Utility Grids and Microgrids With PV Generation

Cited by 55 publications

References 27 publications

Validation of an all‐sky imager–based nowcasting system for industrial PV plants

Validation of an all‐sky imager–based nowcasting system for industrial PV plants

A Review of Strategies to Increase PV Penetration Level in Smart Grids

Active Power Dispatch Optimization for a Grid-Connected Microgrid with Uncertain Multi-Type Loads

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