scholarly journals How to Develop Renewable Power in China? A Cost-Effective Perspective

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Rong-Gang Cong ◽  
Shaochuan Shen
Keyword(s):  
Learning Curve ◽  
Wind Power ◽  
Solar Power ◽  
Cost Effective ◽  
Chinese Government ◽  
Renewable Power ◽  
Investment Cost ◽  
Curve Model ◽  
Development Paths ◽  
Installed Capacity

To address the problems of climate change and energy security, Chinese government strived to develop renewable power as an important alternative of conventional electricity. In this paper, the learning curve model is employed to describe the decreasing unit investment cost due to accumulated installed capacity; the technology diffusion model is used to analyze the potential of renewable power. Combined with the investment cost, the technology potential, and scenario analysis of China social development in the future, we develop the Renewable Power Optimization Model (RPOM) to analyze the optimal development paths of three sources of renewable power from 2009 to 2020 in a cost-effective way. Results show that (1) the optimal accumulated installed capacities of wind power, solar power, and biomass power will reach 169000, 20000, and 30000 MW in 2020; (2) the developments of renewable power show the intermittent feature; (3) the unit investment costs of wind power, solar power, and biomass power will be 4500, 11500, and 5700 Yuan/KW in 2020; (4) the discounting effect dominates the learning curve effect for solar and biomass powers; (5) the rise of on-grid ratio of renewable power will first promote the development of wind power and then solar power and biomass power.

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.

Analysis Model of Wind Power Cost Based on Two-Factor Learning Curve

2012 ◽  
Vol 608-609 ◽  
pp. 611-614
Author(s):  
Jun Jie Kang ◽  
Wei Duan ◽  
Ming Tao Yao
Keyword(s):  
Power Generation ◽  
Learning Curve ◽  
Wind Power ◽  
Wind Power Generation ◽  
Future Price ◽  
Analysis Model ◽  
Power Cost ◽  
Curve Model

The components of wind power cost are analyzed firstly, which provide an intuitive explanation for understanding the composition of wind power generation. And then a two-factor learning curve model is developed for forecasting future price of wind power. We use the model for practical forecasting and simulating wind power cost from 2012 to 2020, the results obtained demonstrate the credibility and validity of the model.

Are Green Electricity Certificates the Way Forward for Renewable Energy? An Evaluation of the United Kingdom's Renewables Obligation in the Context of International Comparisons

2005 ◽  
Vol 23 (3) ◽  
pp. 361-374 ◽  
Author(s):  
Dave Toke
Keyword(s):  
Renewable Energy ◽  
Wind Power ◽  
International Comparisons ◽  
Cost Effective ◽  
Cultural Factors ◽  
Conventional Wisdom ◽  
The Other ◽  
Green Electricity ◽  
Fixed Price ◽  
Installed Capacity

The author analyses the performance of the United Kingdom's ‘Renewables Obligation’ (RO) in the context of other renewable energy procurement regimes. Prevailing wisdom suggests that market-based procurement regimes for renewable energy are more cost-effective than fixed-price (‘feed-in tariff’) arrangements. In addition, market-based regimes are thought to favour corporate, rather than locally owned, schemes. However, the analysis in this paper disputes these strands of conventional wisdom. An analysis of the returns to wind-power developers under the British market-based RO and the German ‘renewable energy feed-tariff’ (REFIT) reveals that financial returns per MW of installed capacity are much higher in the case of the market-based British RO than in the German REFIT. On the other hand, there is evidence that cultural factors are a bigger influence on the patterns of ownership of wind-power schemes than whether procurement systems are market based or fixed price.

Correlations Between Geographically Dispersed Concentrating Solar Power and Demand in the United States

2010 ◽  
Author(s):  
Matthew Mowers ◽  
Chris Helm ◽  
Nate Blair ◽  
Walter Short
Keyword(s):  
Wind Power ◽  
Solar Power ◽  
Thermal Power ◽  
The United States ◽  
Electricity Demand ◽  
Geographically Dispersed ◽  
Renewable Power ◽  
Hourly Data ◽  
High Renewable Penetration ◽  
Utility Scale

Correlations between the electricity generated by concentrating solar thermal power (CSP) plants, as well as cross-correlations between CSP, wind power and electricity demand, have significant impacts on decisions for how much and where to build utility-scale CSP capacity, the optimal amount of thermal storage in the CSP plants, reserve capacity needed to back-up the system, as well as the expected levels of curtailed renewable power. Accurately estimating these correlations is vital to performing detailed analyses of high renewable penetration scenarios. This study quantifies the degree of correlation between geographically dispersed CSP, as well as the correlation between CSP and wind power, and CSP and electricity demand in 356 discrete regions in the contiguous US. Correlations are calculated using hourly data on an annual basis. Maps of the correlations will be presented to illustrate the degree of correlation between solar power and the demand it is serving, as well as the synergies between the negatively-correlated wind power and solar power serving the same region.

Analyses on Integration of Wind Power into Gansu Power Grid

2012 ◽  
Vol 608-609 ◽  
pp. 569-572 ◽  
Author(s):  
Xi Chao Zhou ◽  
Fu Chao Liu ◽  
Jing Jing Zheng
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Transient Stability ◽  
Power Grid ◽  
Wind Farms ◽  
Chinese Government ◽  
Wind Power Integration ◽  
Grid Operation ◽  
Installed Capacity ◽  
The Impact

In recent years, wind power penetration into the grid has increased rapidly with abundant wind resources in Jiuquan, according to the policy of the Chinese government to “establish a ‘Hexi Wind Power Corridor’ and rebuild another Western ‘Terrestrial Three Gorges Dam’”. By the end of 2010, the total installed capacity of wind power in Jiuquan has reached 5160 MW. The wind farms are connected to 110 kV transmission network or above in Jiuquan, the studies of their impacts on the grid, in particular, the grid operation are becoming serious and urgent. Jiuquan is far away from the load center with a weak grid configuration, therefore issues such as transmission line overloading, local grid voltage fluctuation, and transient stability limitation are looming with large scale wind power integration. The power system dispatch and operation are influenced by the intermittent nature of the wind power, which should be regulated by the system reserves. This paper discusses the recent integration of wind power into the grid with a focus on the impact on the Gansu power grid operation. The paper also presents the measures to deal with these issues.

Greenko Plc1

2015 ◽  
pp. 1-42
Author(s):  
Sidharth Sinha
Keyword(s):  
Public Policy ◽  
Renewable Energy ◽  
Wind Power ◽  
Financial Institutions ◽  
Project Finance ◽  
Hydro Power ◽  
The Public ◽  
Renewable Power ◽  
Indian Banks ◽  
Installed Capacity

Greenko, a renewable power generating company investing in biomass, small and medium hydro power and wind power projects, had projected to achieve 1GW (Giga Watt = 1000 Mega Watt) of installed capacity by March 2015. The company had been financing its projects with debt from Indian banks and financial institutions on a project finance basis and it had to now decide whether to refinance the project finance debt with an international bond issue of USD 550 million. The case provides an opportunity to discuss the public policy and financing aspects of renewable energy in India.

scholarly journals How Do Stakeholders Perceive Barriers to Large-Scale Wind Power Diffusion? A Q-Method Case Study from Ceará State, Brazil

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2063
Author(s):  
Cláudio Albuquerque Frate ◽  
Christian Brannstrom
Keyword(s):  
Wind Power ◽  
Transmission Lines ◽  
Large Scale ◽  
Q Method ◽  
Predictive Capacity ◽  
Social Perspectives ◽  
Renewable Power ◽  
Policy Interventions ◽  
High Penetration ◽  
Installed Capacity

High penetration of renewable power requires technical, organizational, and political changes. We use Q-method, a qualitative–quantitative technique, to identify and analyze views held by key actors on challenges for large-scale diffusion of wind power in Ceará State, Brazil, an early leader in wind power with 2.05 GW installed capacity. Four quantitatively determined social perspectives were identified with regard to views on challenges for wind power expansion: (1) failing because of the grid; (2) environmental challenges; (3) planning for wind, and (4) participating in wind. Each social perspective emphasizes a different array of barriers, such as cost of new transmission lines, transformation of a hydro-thermal mental model, predictive capacity for wind energy, and the need for participatory forum. Understanding the subjective views of stakeholders is a key first step in eventually reducing these barriers to renewable power penetration through diverse policy interventions.

scholarly journals Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2539
Author(s):  
Zhengjie Li ◽  
Zhisheng Zhang
Keyword(s):  
Wind Power ◽  
Demand Response ◽  
Solar Power ◽  
Load Forecasting ◽  
Energy System ◽  
Optimal Scheduling ◽  
Scheduling Scheme ◽  
Load Power ◽  
Integrated Energy System ◽  
Operation Cost

At present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this problem, a day-ahead and intra-day optimal scheduling model of integrated energy system considering forecasting uncertainty is proposed in this paper, which takes the minimum operation cost of the system as the target, and different processing strategies are adopted for the model. In the day-ahead time scale, according to day-ahead load forecasting, an integrated demand response (IDR) strategy is formulated to adjust the load curve, and an optimal scheduling scheme is obtained. In the intra-day time scale, the predicted value of wind power, solar power and load power are represented by fuzzy parameters to participate in the optimal scheduling of the system, and the output of units is adjusted based on the day-ahead scheduling scheme according to the day-ahead forecasting results. The simulation of specific examples shows that the integrated demand response can effectively adjust the load demand and improve the economy and reliability of the system operation. At the same time, the operation cost of the system is related to the reliability of the accurate prediction of wind power, solar power and load power. Through this model, the optimal scheduling scheme can be determined under an acceptable prediction accuracy and confidence level.

Comparative Exploration of Mini Vertical Axis Breeze-Driven Generator

2014 ◽  
Vol 670-671 ◽  
pp. 964-967
Author(s):  
Shu Hua Bai ◽  
Hai Dong Yang
Keyword(s):  
Natural Gas ◽  
Wind Turbine ◽  
Wind Power ◽  
North Africa ◽  
Large Scale ◽  
Solar Power ◽  
Vertical Axis ◽  
Green Energy ◽  
Energy Crisis ◽  
Fossil Energy

Nowadays, energy crisis is becoming increasingly serious. Coal, petroleum, natural gas and other fossil energy tend to be exhausted due to the crazy exploration. In recent decades, several long lasting local wars broke out in large scale in Mideast and North Africa because of the fighting for the limited petroleum. The reusable green energy in our life like enormous wind power, solar power, etc is to become the essential energy. This article is to conduct a comparative exploration of mini wind turbine, with the purpose of finding a good way to effectively deal with the energy crisis.

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