scholarly journals Renewable Energy Sources and Battery Forecasting Effects in Smart Power System Performance

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 373 ◽  
Author(s):  
Mehdi Bagheri ◽  
Venera Nurmanova ◽  
Oveis Abedinia ◽  
Mohammad Salay Naderi ◽  
Noradin Ghadimi ◽  
...  

In this study, the influence of using acid batteries as part of green energy sources, such as wind and solar electric power generators, is investigated. First, the power system is simulated in the presence of a lead–acid battery, with an independent solar system and wind power generator. In the next step, in order to estimate the output power of the solar and wind resources, a novel forecast model is proposed. Then, the forecasting task is carried out considering the conditions related to the state of charge (SOC) of the batteries. The optimization algorithm used in this model is honey bee mating optimization (HBMO), which operates based on selecting the best candidates and optimization of the prediction problem. Using this algorithm, the SOC of the batteries will be in an appropriate range, and the number of on-or-off switching’s of the wind turbines and photovoltaic (PV) modules will be reduced. In the proposed method, the appropriate capacity for the SOC of the batteries is chosen, and the number of battery on/off switches connected to the renewable energy sources is reduced. Finally, in order to validate the proposed method, the results are compared with several other methods.

2018 ◽  
Vol 7 (1.8) ◽  
pp. 201
Author(s):  
M Veda Swaroop ◽  
P Linga Reddy

The solar and wind renewable energy sources are gaining popularity to encourage green energy into the power system. The cost of generation of solar and wind energy sources are decreasing and competing with conventional coal-based generation. Therefore, it is very important to integrate these renewable sources into the power system. Integrating Solar and wind energy sources require to solve the uncertainty problem. Both the solar and wind energy generation is uncertain and not controllable. In this paper, sliding window optimal ARIMA forecasting algorithm is proposed to solve the uncertainty associated with solar and wind sources. The proposed forecasting method is used on the data collected from National Renewable Energy Laboratory website.  


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4270
Author(s):  
Gianpiero Colangelo ◽  
Gianluigi Spirto ◽  
Marco Milanese ◽  
Arturo de Risi

In the last years, a change in the power generation paradigm has been promoted by the increasing use of renewable energy sources combined with the need to reduce CO2 emissions. Small and distributed power generators are preferred to the classical centralized and sizeable ones. Accordingly, this fact led to a new way to think and design distributions grids. One of the challenges is to handle bidirectional power flow at the distribution substations transformer from and to the national transportation grid. The aim of this paper is to review and analyze the different mathematical methods to design the architecture of a distribution grid and the state of the art of the technologies used to produce and eventually store or convert, in different energy carriers, electricity produced by renewable energy sources, coping with the aleatory of these sources.


Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2862
Author(s):  
Mika Korkeakoski

Renewable Energy Sources (RES) have become increasingly desirable worldwide in the fight against global climate change. The sharp decrease in costs of especially wind and solar photovoltaics (PV) have created opportunities to move from dependency on conventional fossil fuel-based electricity production towards renewable energy sources. Renewables experience around 7% (in 2018) annual growth rate in the electricity production globally and the pace is expected to further increase in the near future. Cuba is no exception in this regard, the government has set an ambitious renewable energy target of 24% RES of electricity production by the year 2030. The article analyses renewable energy trajectories in Isla de la Juventud, Cuba, through different future energy scenarios utilizing EnergyPLAN tool. The goal is to identify the best fit and least cost options in transitioning towards 100% electric power systemin Isla de la Juventud, Cuba. The work is divided into analysis of (1) technical possibilities for five scenarios in the electricity production with a 40% increase of electricity consumption by 2030: Business As Usual (BAU 2030, with the current electric power system (EPS) setup), VISION 2030 (according to the Cuban government plan with 24% RES), Advanced Renewables (ARES, with 50% RES), High Renewables (HiRES, with 70% RES), and Fully Renewables (FullRES, with 100% RES based electricity system) scenarios and (2) defining least cost options for the five scenarios in Isla de la Juventud, Cuba. The results show that high penetration of renewables is technically possible even up to 100% RES although the best technological fit versus least cost options may not favor the 100% RES based systems with the current electric power system (EPS) setup. This is due to realities in access to resources, especially importation of state of the art technological equipment and biofuels, financial and investment resources, as well as the high costs of storage systems. The analysis shows the Cuban government vision of reaching 24% of RES in the electricity production by 2030 can be exceeded even up to 70% RES based systems with similar or even lower costs in the near future in Isla de la Juventud. However, overcoming critical challenges in the economic, political, and legal conditions are crucially important; how will the implementation of huge national capital investments and significant involvement of Foreign Direct Investments (FDI) actualize to support achievement of the Cuban government’s 2030 vision?


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