scholarly journals IMPACT AND COSTS OF THE CLOSURE OF COAL-FIRED POWER PLANTS IN THE IBERIAN PENINSULA

10.6036/10228 ◽  
2021 ◽  
Vol 96 (6) ◽  
pp. 564-564
Author(s):  
ANGEL ARCOS VARGAS ◽  
FERNANDO NUÑEZ ◽  
JUAN ANTONIO BALLESTEROS GALLARDO
Keyword(s):  
Iberian Peninsula ◽  
Power Plants ◽  
Electricity Sector ◽  
Renewable Power ◽  
Demographic Challenge ◽  
Ecological Transition

Scheduled closure of coal-fired power plants will halve emissions in the electricity sector, although prices will be increased by 12%. To compensate for this increase, the Ministry for Ecological Transition and the Demographic Challenge will promote new renewable power.

scholarly journals Electromechanical Design of Synchronous Power Controller in Grid Integration of Renewable Power Converters to Support Dynamic Stability

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2115
Author(s):  
Mostafa Abdollahi ◽  
Jose Ignacio Candela ◽  
Andres Tarraso ◽  
Mohamed Atef Elsaharty ◽  
Elyas Rakhshani
Keyword(s):  
Dynamic Stability ◽  
Power Plants ◽  
Power Converters ◽  
Power Grids ◽  
Synchronous Generators ◽  
Power Controller ◽  
Renewable Power ◽  
Grid Connection ◽  
Control Technologies ◽  
Control Layer

Nowadays, modern power converters installed in renewable power plants can provide flexible electromechanical characteristics that rely on the developed control technologies such as Synchronous Power Controller (SPC). Since high renewable penetrated power grids result in a low-inertia system, this electromechanical characteristic provides support to the dynamic stability of active power and frequency in the power generation area. This goal can be achieved through the proper tuning of virtual electromechanical parameters that are embedded in the control layers of power converters. In this paper, a novel mathematical pattern and strategy have been proposed to adjust dynamic parameters in Renewable Static Synchronous Generators controlled by SPC (RSSG-SPC). A detailed dynamic modeling was obtained for a feasible design of virtual damping coefficient and virtual moment of inertia in the electrometrical control layer of RSSG-SPC’s power converters. Mathematical solutions, modal analysis outcomes, time-domain simulation results, and real-time validations of the test in IEEE-14B benchmark confirm that the proposed method is an effective procedure for the dynamic design of RSSG-SPC to provide these dynamic stability supports in grid connection.

scholarly journals Portfolio optimization of power plants by using renewable energy in Iran

2020 ◽  
Author(s):  
Seyedeh Asra Ahmadi ◽  
Seyed Mojtaba Mirlohi ◽  
Mohammad Hossein Ahmadi ◽  
Majid Ameri
Keyword(s):  
Renewable Energy ◽  
Portfolio Optimization ◽  
Energy Supply ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Modern Society ◽  
Sustainable Growth ◽  
Electricity Sector ◽  
Capital Costs

Abstract Lack of investment in the electricity sector has created a huge bottleneck in the continuous flow of energy in the market, and this will create many problems for the sustainable growth and development of modern society. The main reason for this lack of investment is the investment risk in the electricity sector. One way to reduce portfolio risk is to diversify it. This study applies the concept of portfolio optimization to demonstrate the potential for greater use of renewable energy, which reduces the risk of investing in the electricity sector. Besides, it shows that investing in renewable energies can offset the risk associated with the total input costs. These costs stem from the volatility of associated prices, including fossil fuel, capital costs, maintenance, operation and environmental costs. This case study shows that Iran can theoretically supply ~33% of its electricity demand from renewable energy sources compared to its current 15% share. This case study confirms this finding and predicts that Iran, while reducing the risk of investing in electricity supply, can achieve a renewable energy supply of ~9% with an average increase in supply costs. Sensitivity analysis further shows that with a 10% change in input cost factors, the percentage of renewable energy supply is only partially affected, but basket costs change according to the scenario of 5–32%. Finally, suggestions are made that minimize risk rather than cost, which will bring about an increase in renewable energy supply.

scholarly journals Operational and financial performance of fossil fuel power plants within a high renewable energy mix

2017 ◽  
Vol 1 ◽  
pp. 2BIOTO ◽  
Author(s):  
Patrick Eser ◽  
Ndaona Chokani ◽  
Reza S. Abhari
Keyword(s):  
Renewable Energy ◽  
Financial Performance ◽  
Electricity Markets ◽  
Power Plants ◽  
Energy System ◽  
Renewable Power ◽  
High Penetration ◽  
Demand Models ◽  
Wide Range ◽  
Coal Power Plants

AbstractThe operation of conventional power plants in the 2030 high-renewable energy system of central Europe with high penetration of renewables is simulated in this work. Novel insights are gained in this work, since the generation, transmission and demand models have high geographic resolution, down to scale of individual units, with hourly temporal resolution. It is shown that the increases in the partload efficiency that optimize gas power plants’ financial performance in 2030 are highly dependent on the variability in power production of renewable power plants that are in close proximity to the gas power plants. While coal power plants are also cycled more, an increased baseload efficiency is more beneficial for their financial viability. Thus, there is a need for OEMs to offer a wide range of technology solutions to cover all customers’ needs in electricity markets with high penetrations of renewables. Therefore there is an increased investment risk for OEMs as they strive to match their customers’ future needs.

scholarly journals Machine Learning and Metaheuristic Methods for Renewable Power Forecasting: A Recent Review

2021 ◽  
Vol 3 ◽  
Author(s):  
Hanin Alkabbani ◽  
Ali Ahmadian ◽  
Qinqin Zhu ◽  
Ali Elkamel
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Wind Power ◽  
Solar Power ◽  
Electricity Sector ◽  
Support Vector ◽  
Renewable Power ◽  
Metaheuristic Methods ◽  
Metaheuristic Techniques ◽  
Power Forecasting

The global trend toward a green sustainable future encouraged the penetration of renewable energies into the electricity sector to satisfy various demands of the market. Successful and steady integrations of renewables into the microgrids necessitate building reliable, accurate wind and solar power forecasters adopting these renewables' stochastic behaviors. In a few reported literature studies, machine learning- (ML-) based forecasters have been widely utilized for wind power and solar power forecasting with promising and accurate results. The objective of this article is to provide a critical systematic review of existing wind power and solar power ML forecasters, namely artificial neural networks (ANNs), recurrent neural networks (RNNs), support vector machines (SVMs), and extreme learning machines (ELMs). In addition, special attention is paid to metaheuristics accompanied by these ML models. Detailed comparisons of the different ML methodologies and the metaheuristic techniques are performed. The significant drawn-out findings from the reviewed papers are also summarized based on the forecasting targets and horizons in tables. Finally, challenges and future directions for research on the ML solar and wind prediction methods are presented. This review can guide scientists and engineers in analyzing and selecting the appropriate prediction approaches based on the different circumstances and applications.

Probabilistic life-cycle cost analysis for renewable and non-renewable power plants

Energy ◽  
2016 ◽  
Vol 112 ◽  
pp. 774-787 ◽  
Author(s):  
Juan José Cartelle Barros ◽  
Manuel Lara Coira ◽  
María Pilar de la Cruz López ◽  
Alfredo del Caño Gochi
Keyword(s):  
Life Cycle ◽  
Cost Analysis ◽  
Life Cycle Cost ◽  
Power Plants ◽  
Life Cycle Cost Analysis ◽  
Renewable Power

A novel MCDM model for prioritizing the renewable power plants’ construction

2019 ◽  
Vol 30 (2) ◽  
pp. 383-399 ◽  
Author(s):  
Fatima Sedady ◽  
Mohammad Ali Beheshtinia
Keyword(s):  
Power Plants ◽  
Environmental Aspects ◽  
Tidal Power ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Renewable Power ◽  
Comparison Results ◽  
Criteria Weights ◽  
Analytic Hierarchy Process Method ◽  
Hierarchy Process

Purpose The purpose of this paper is to propose a new multi-criteria decision making (MCDM) technique to determine the priority of renewable power plants construction conceding technical, economic, social, political and environmental aspects. Design/methodology/approach First, a comprehensive set of 5 main criteria of technical, economic, social, political and environmental are considered for renewable power plants construction, each including 5 sub-criteria (a total of 25 sub-criteria). Then, the analytic hierarchy process method is used to determine the weight of the criteria. Finally, a new MCDM technique proposed to prioritize the construction of renewable power plants, named TOPKOR. To demonstrate the capability of the proposed method, a case study is conducted in which six types of renewable power plants are evaluated. Findings Comparison results of the main criteria weights show that the “economic” [0.403], “environmental” [0.296] and “technical” [0.17] aspects have the highest importance, respectively. The results also show that solar, hydroelectric and wave and tidal power plants have the highest priority for construction, respectively. Research limitations/implications The result of this research could be useful for related decision makers in construction of the renewable power plants to have a comprehensive set of criteria in technical, economic, social, political and environmental aspects in their decision process. Originality/value This research provides a comprehensive set of criteria and sub-criteria for prioritizing the renewable power plants. Moreover, a new hybrid MCDM technique is introduced for prioritizing the construction of power plants.

Hybrid power plants as an alternative to fit pumped-storage hydro in Brazilian electricity sector regulatory framework

2018 ◽  
Vol 42 (15) ◽  
pp. 4898-4908 ◽  
Author(s):  
Gustavo Henrique Duzzi Libanori ◽  
Vinícius de Carvalho Neiva Pinheiro ◽  
Alberto Luiz Francato
Keyword(s):  
Power Plants ◽  
Regulatory Framework ◽  
Electricity Sector ◽  
Hybrid Power ◽  
Pumped Storage

scholarly journals Analysis of the Potential for Renewable Utilization in Kosovo Power Sector

Environments ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 49
Author(s):  
Shpetim Lajqi ◽  
Bojan Đurin ◽  
Xhevat Berisha ◽  
Lucija Plantak
Keyword(s):  
Power Plants ◽  
Carbon Dioxide Emission ◽  
Electricity Sector ◽  
Solar Irradiation ◽  
Power Sector ◽  
Emission Reduction Potential ◽  
Average Water ◽  
High Pollution ◽  
Utilization Potential ◽  
Using Data

The reduction in greenhouse gas emissions and the decarbonization of the power sector through the utilization of available renewable technologies are challenging issues that Kosovo has to tackle right now, in order to fight the high pollution caused by a coal-based power system. Around 91.43% of installed capacities for electricity generation in Kosovo are based on coal-fired power plants. The aim of this paper is to show the potential for renewable utilization, using data measurements of wind, solar irradiation, biomass, and average water flows at different area locations to identify their utilization potential. Furthermore, a review on the currently available and future renewable energy projects integrated into the electricity sector is presented. A 54% carbon dioxide emission reduction potential was estimated in the power sector when considering maximum utilization potential of biomass, wind, solar renewable energies compared to a referent scenario. The results obtained from this review have shown the pathways for identifying the potential utilization of renewable as well as the actual and planned use of renewable implemented projects into the Kosovo Power Sector.

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