scholarly journals Influence of wind power production on electricity market price

2020 ◽  
Vol 24 (1) ◽  
pp. 472-482
Author(s):  
Gunars Valdmanis ◽  
Gatis Bazbauers
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
System Analysis ◽  
Market Price ◽  
Power Market ◽  
Power Production ◽  
Energy System ◽  
Market Prices ◽  
Renewable Power ◽  
The Baltic

AbstractThe study looks for a correlation between the share of wind power and electricity wholesale prices in the selected regions of the Nordic Baltic power market “Nord Pool Spot”. The aim is to see if and how strong an impact of wind power production has on power market prices. This information would help to perform long-term energy system analysis considering growing wind energy penetration. The actual hourly wind production and power consumption data as well as electricity prices from the year 2019 were used in the analysis. Results of the study revealed that in the analysed dataset there is no correlation between the share of wind power and the power prices, i.e. R-squared value is 0.003 for the Baltic region and 0.0064 for both trading areas of Denmark. In contrast, the R-squared value was almost 0.6 for a positive correlation between power demand and prices. The results mean that expected loss of interest to invest due to falling power prices, as a share of renewable power increases, should be examined more carefully and may not fulfil forecasts of policy makers and industry experts.

scholarly journals High-Resolution Electricity Spot Price Forecast for the Danish Power Market

2020 ◽  
Vol 12 (10) ◽  
pp. 4267 ◽  
Author(s):  
Jannik Schütz Roungkvist ◽  
Peter Enevoldsen ◽  
George Xydis
Keyword(s):  
Electricity Market ◽  
Thermal Power ◽  
Power Market ◽  
Power Production ◽  
Spot Price ◽  
Price Forecasting ◽  
Learning Approaches ◽  
Electricity Prices ◽  
Price Forecast ◽  
Electricity Spot Price

Energy markets with a high penetration of renewables are more likely to be challenged by price variations or volatility, which is partly due to the stochastic nature of renewable energy. The Danish electricity market (DK1) is a great example of such a market, as 49% of the power production in DK1 is based on wind power, conclusively challenging the electricity spot price forecast for the Danish power market. The energy industry and academia have tried to find the best practices for spot price forecasting in Denmark, by introducing everything from linear models to sophisticated machine-learning approaches. This paper presents a linear model for price forecasting—based on electricity consumption, thermal power production, wind production and previous electricity prices—to estimate long-term electricity prices in electricity markets with a high wind penetration levels, to help utilities and asset owners to develop risk management strategies and for asset valuation.

scholarly journals Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 896
Author(s):  
Bin Ma ◽  
Shiping Geng ◽  
Caixia Tan ◽  
Dongxiao Niu ◽  
Zhijin He
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Joint Ventures ◽  
Market Competition ◽  
Power Market ◽  
Energy Output ◽  
Power Station ◽  
New Energy ◽  
Upper Level ◽  
Pumped Storage

The volatility of a new energy output leads to bidding bias when participating in the power market competition. A pumped storage power station is an ideal method of stabilizing new energy volatility. Therefore, wind power suppliers and pumped storage power stations first form wind storage joint ventures to participate in power market competition. At the same time, middlemen are introduced, constructing an upper-level game model (considering power producers and wind storage joint ventures) that forms equilibrium results of bidding competition in the wholesale and power distribution markets. Based on the equilibrium result of the upper-level model, a lower model is constructed to distribute the profits from wind storage joint ventures. The profits of each wind storage joint venture, wind power supplier, and pumped storage power station are obtained by the Nash negotiation and the Shapely value method. Finally, a case study is conducted. The results show that the wind storage joint ventures can improve the economics of the system. Further, the middlemen can smooth the rapid fluctuation of power price in the distribution and wholesale market, maintaining a smooth and efficient operation of the electricity market. These findings provide information for the design of an electricity market competition mechanism and the promotion of new energy power generation.

scholarly journals Wind Power Integration Peculiarities in the Electricity System of the Baltic States

2020 ◽  
Vol 76 (3) ◽  
pp. 6-15
Author(s):  
Giedrius Gecevičius ◽  
Mantas Marčiukaitis
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Turbines ◽  
Energy System ◽  
Utilization Efficiency ◽  
Baltic States ◽  
Wind Power Integration ◽  
Electricity System ◽  
The Baltic ◽  
Power Installations

Analysis of wind power utilization efficiency around the world and Europe has revealed the gap between feasible and factual power generation. The paper presents an investigation of wind power generation dynamics, penetration levels into the electricity system, and dependence of capacity factors on the hub height and the rotor diameter of wind turbines in the Baltic States. These factors are the main for the evaluation of wind power utilization efficiency. Wind power penetration levels show that possibilities of the energy system to accept more wind power installations in the Baltic States are far away from its limit. Besides, dependence of high wind turbines capacity factors’ on the hub height and the rotor diameter in the range of 20–120 m was revealed.

scholarly journals Impact of Financing Instruments and Strategies on the Wind Power Production Costs: A Case of Lithuania

2018 ◽  
Vol 55 (2) ◽  
pp. 11-27
Author(s):  
V. Bobinaite ◽  
I. Konstantinaviciute
Keyword(s):  
Venture Capital ◽  
Wind Power ◽  
Electricity Market ◽  
Power Production ◽  
Production Costs ◽  
Selling Price ◽  
Support Measures ◽  
Extended Approach ◽  
Investment Subsidy ◽  
Feed In Tariff

Abstract The paper aims at demonstrating the relevance of financing instruments, their terms and financing strategies in relation to the cost of wind power production and the ability of wind power plant (PP) to participate in the electricity market in Lithuania. The extended approach to the Levelized Cost of Energy (LCOE) is applied. The feature of the extended approach lies in considering the lifetime cost and revenue received from the support measures. The research results have substantiated the relevance of financing instruments, their terms and strategies in relation to their impact on the LCOE and competitiveness of wind PP. It has been found that financing of wind PP through the traditional financing instruments (simple shares and bank loans) makes use of venture capital and bonds coming even in the absence of any support. It has been estimated that strategies consisting of different proportions of hard and soft loans, bonds, own and venture capital result in the average LCOE of 5.1–5.7 EURct/kWh (2000 kW), when the expected electricity selling price is 5.4 EURct/kWh. The financing strategies with higher shares of equity could impact by around 6 % higher LCOE compared to the strategies encompassing higher shares of debt. However, seeking to motivate venture capitalists, bond holders or other new financiers entering the wind power sector, support measures (feed-in tariff or investment subsidy) are relevant in case of 250 kW wind PP. It has been estimated that under the unsupported financing strategies, the average LCOE of 250 kW wind PP will be 7.8–8.8 EURct/kWh, but it will reduce by around 50 % if feed-in tariff or 50 % investment subsidy is applied.

scholarly journals The smoother the better? A comparison of six post-processing methods to improve short-term offshore wind power forecasts in the Baltic Sea

2021 ◽  
Vol 6 (5) ◽  
pp. 1205-1226
Author(s):  
Christoffer Hallgren ◽  
Stefan Ivanell ◽  
Heiner Körnich ◽  
Ville Vakkari ◽  
Erik Sahlée
Keyword(s):  
Random Forest ◽  
Baltic Sea ◽  
Wind Power ◽  
Power Production ◽  
Offshore Wind ◽  
Post Processing ◽  
The Baltic Sea ◽  
Offshore Wind Power ◽  
The Baltic ◽  
Forecast Quality

Abstract. With a rapidly increasing capacity of electricity generation from wind power, the demand for accurate power production forecasts is growing. To date, most wind power installations have been onshore and thus most studies on production forecasts have focused on onshore conditions. However, as offshore wind power is becoming increasingly popular it is also important to assess forecast quality in offshore locations. In this study, forecasts from the high-resolution numerical weather prediction model AROME was used to analyze power production forecast performance for an offshore site in the Baltic Sea. To improve the AROME forecasts, six post-processing methods were investigated and their individual performance analyzed in general as well as for different wind speed ranges, boundary layer stratifications, synoptic situations and in low-level jet conditions. In general, AROME performed well in forecasting the power production, but applying smoothing or using a random forest algorithm increased forecast skill. Smoothing the forecast improved the performance at all wind speeds, all stratifications and for all synoptic weather classes, and the random forest method increased the forecast skill during low-level jets. To achieve the best performance, we recommend selecting which method to use based on the forecasted weather conditions. Combining forecasts from neighboring grid points, combining the recent forecast with the forecast from yesterday or applying linear regression to correct the forecast based on earlier performance were not fruitful methods to increase the overall forecast quality.

scholarly journals Additional measures on the development of the conditions of competition on the Russian electricity market

2019 ◽  
pp. 52-58
Author(s):  
V. Ya. Afanasev ◽  
V. V. Kuzmin
Keyword(s):  
Electric Power ◽  
Electricity Market ◽  
Current Model ◽  
Power Market ◽  
Power Production ◽  
Market Model ◽  
Electric Power Market ◽  
Electric Power Production ◽  
Further Development ◽  
Modern Russian

The issues of the organization of relations in the modern Russian electric power market have been considered. Based on the analysis of the characteristics and problems of the current model of the Russian electricity market, the conclusion has been made, that it is necessary to develop and implement an additional set of measures to develop this market in order to ensure acceptable conditions of competition, which allow through application of the competitive procedures and mechanisms to increase the efficiency of the electric power production, transmission and consumption process. The characteristic of the electric power market model, possessing the properties of modern markets with developed competition, has been given. The measures for the organizational and theoretical provision of the process of further development of the electric power market have been offered.

DEEPSO to predict wind power and electricity market prices series in the short-term

2016 ◽  
Author(s):  
J. N. D. L. Goncalves ◽  
G. J. Osorio ◽  
J. M. Lujano-Rojas ◽  
T. D. P. Mendes ◽  
J. P. S. Catalao
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Short Term ◽  
Market Prices
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