A case study of PV-wind-diesel-battery hybrid system

Uğurlu, Adem; Gökçöl, Cihan

doi:10.30521/jes.348335

Cited by 11 publications

(9 citation statements)

References 17 publications

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“…where E genh is the forecasting energy generation at each hour; and E bath is energy at the battery at each hour. Energy efficiencies η chgh and η dish are the ones defined in (5) and (6). An important point to take into account is that, in order to extend the battery life, charging and discharging cycles should not overpass certain SOC limits.…”

Section: A Cost Functionmentioning

confidence: 99%

“…The resulting curves for different power values (maximum external power value P extmax is 10 MW) are calculated based on (5) and (6), and the result is shown in Fig. 3.…”

Section: Case Studymentioning

confidence: 99%

“…Considering the production variability, hybrid combinations of these alternative sources can become complementary, and therefore improve the performance of the generation plant. As an example, a combination between wind and solar energy appears to be interesting for a hybrid renewable energy system (HRES) due to their greater development compared with less mature RESs [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

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Multi-objective Optimization of Production Scheduling Using Particle Swarm Optimization Algorithm for Hybrid Renewable Power Plants with Battery Energy Storage System

Martinez-Rico

Zulueta

Argandoña

et al. 2021

Journal of Modern Power Systems and Clean Energy

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Considering the increasing integration of renewable energies into the power grid, batteries are expected to play a key role in the challenge of compensating the stochastic and intermittent nature of these energy sources. Besides, the deployment of batteries can increase the benefits of a renewable power plant. One way to increase the profits with batteries studied in this paper is performing energy arbitrage. This strategy is based on storing energy at low electricity price moments and selling it when electricity price is high. In this paper, a hybrid renewable energy system consisting of wind and solar power with batteries is studied, and an optimization process is conducted in order to maximize the benefits regarding the dayahead production scheduling of the plant. A multi-objective cost function is proposed, which, on the one hand, maximizes the obtained profit, and, on the other hand, reduces the loss of value of the battery. A particle swarm optimization algorithm is developed and fitted in order to solve this non-linear multi-objective function. With the aim of analyzing the importance of considering both the energy efficiency of the battery and its loss of value, two more simplified cost functions are proposed. Results show the importance of including the energy efficiency in the cost function to optimize. Besides, it is proven that the battery lifetime increases substantially by using the multi-objective cost function, whereas the profitability is similar to the one obtained in case the loss of value is not considered. Finally, due to the small difference in price among hours in the analyzed Iberian electricity market, it is observed that low profits can be provided to the plant by using batteries just for arbitrage purposes in the day-ahead market.

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Section: A Cost Functionmentioning

confidence: 99%

“…The resulting curves for different power values (maximum external power value P extmax is 10 MW) are calculated based on (5) and (6), and the result is shown in Fig. 3.…”

Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-objective Optimization of Production Scheduling Using Particle Swarm Optimization Algorithm for Hybrid Renewable Power Plants with Battery Energy Storage System

Martinez-Rico

Zulueta

Argandoña

et al. 2021

Journal of Modern Power Systems and Clean Energy

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“…DC-DC power conversion is frequently used to achieve the desired DC voltage level in application areas such as renewable energy sources [1], network interfaces, electric vehicles, high voltage DC transmission system, and uninterruptible power supplies. Design of basic DC-DC power converter circuits and the development of switching elements in recent years provides higher-frequency switching in the larger power systems with the original circuit topologies.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the switching losses in DC-DC boost converters by various machine learning methods

Sabancı

Balci

Aslan

2020

Journal of Energy Systems

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DC-DC converter circuits are topologies commonly used in power electronics applications such as renewable energy sources, electric vehicles, uninterruptible power supplies and DC transmission systems. The most important factors affecting efficiency and thus performance is the choice of the power semiconductor switching element as well as the circuit design and types of these topologies. In this context, power semiconductors are determined according to the switching frequency and current-voltage parameters. However, due to other operating modes of the circuit and load variation during the power conversion, the losses of the switching elements do not remain constant. In this study, a parametric simulation is performed in a conventional DC-DC boost converter circuit using the parameters related to the Insulated-Gate Bipolar Transistor (IGBT) power-switching element selected at a certain current-voltage capacity. These parameters are switching frequency, duty ratio and load change of the converter. Finally, using the data obtained, the loss of switching losses are estimated by the Multilayer Perceptron (MLP), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Random Forest (RF) Machine Learning (ML) techniques.

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“…The paper [9] describes Wind -Photovoltaic -Diesel System with backup energy storage located in Turkey's Sakarya province. It is noted that if the wind speed is low, the optimal hybrid system is a Photovoltaic (PV) -Diesel -Battery System.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Power Plant with Storage System: University Research Station

Gubański¹,

Sobkowiak²,

Jasiński³

et al. 2019

Period. Polytech. Elec. Eng. Comp. Sci.

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The article presents a brief overview of renewable energy sources, microgrids and energy storage problems. The construction and utilisation of university research station to study the operation of a hybrid power plant with an energy storage unit has been described. The tested hybrid power plant consists of a photovoltaic panel and a wind turbine. There are two possible areas of research, one is when the microgrid is connected to the main grid and second when it functions independently as a stand-alone setup. In addition, the model allows to study the characteristics of photovoltaic cells, examine the dependence of generated power on the time, season and angle of the solar panel. In this article, the current-voltage characteristics and influence of solar azimuth angle on cell power, dependence of wind on power generated by the wind turbine, and study of off-grid work of power plant are presented.

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A case study of PV-wind-diesel-battery hybrid system

Cited by 11 publications

References 17 publications

Multi-objective Optimization of Production Scheduling Using Particle Swarm Optimization Algorithm for Hybrid Renewable Power Plants with Battery Energy Storage System

Multi-objective Optimization of Production Scheduling Using Particle Swarm Optimization Algorithm for Hybrid Renewable Power Plants with Battery Energy Storage System

Estimation of the switching losses in DC-DC boost converters by various machine learning methods

Hybrid Power Plant with Storage System: University Research Station

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