Electricity markets overview — Market participation possibilities for renewable and distributed energy resources

Pavić, Ivan; Beus, Mateo; Pandžić, Hrvoje; Capuder, Tomislav; Štritof, Ivona

doi:10.1109/eem.2017.7981917

Cited by 17 publications

(16 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the first 100 days of trading, only 100 GWh of electricity was traded over CROPEX, which means that its liquidity was less than 2% [15]. Figure 3 shows that on 4 October 2016, the liquidity of the CROPEX was only 0.84%.…”

Section: Cropex-day-ahead Marketmentioning

confidence: 99%

“…Demand level is indicated in MW on the left-hand side of Figure 3 with numbers 1300-2400. If we compare the liquidity of CROPEX with Nord Pool, which has liquidity beyond 90%, it is obvious that CROPEX is still not a well-functioning market and additional analyses and development strategies should be performed [15,33,34]. However, CROPEX is a small national power exchange, while Nord Pool represents a regional power exchange, which is one of the reasons for such a difference in liquidity between them.…”

Section: Cropex-day-ahead Marketmentioning

confidence: 99%

“…In 2013, the French wholesale market had an HHI index around 9000, while liquidity was around 12%, which is relatively low compared with 40% for Germany and 67% for Spain [14]. An interested reader is referred to [15] for European electricity markets' liquidity values for 2015.…”

Section: Relevant Workmentioning

confidence: 99%

See 2 more Smart Citations

Electricity Market Design in Croatia within the European Electricity Market—Recommendations for Further Development

et al. 2018

Self Cite

View full text Add to dashboard Cite

Abstract:One of the most important objectives of the European Union is the creation of an Internal Electricity Market (IEM) in Europe. Various national electricity market designs represent one of the major obstacles to the creation of IEM and it is necessary to coordinate national market designs among Member States in order to achieve that. Therefore, this paper gives a comprehensive overview of the electricity market design according to laws related to the electricity sector that are in force in Croatia. Additionally, the paper identifies key obstacles that hamper the development of a well-functioning electricity market in Croatia towards its further integration into the IEM. Since Croatian Power Exchange (CROPEX) is not coupled with any other power exchange, special attention was given to necessary prerequisites for market coupling with the Slovenian Power Exchange (BSP SouthPool) and with the Hungarian Power Exchange (HUPX).

show abstract

Section: Cropex-day-ahead Marketmentioning

confidence: 99%

Section: Cropex-day-ahead Marketmentioning

confidence: 99%

See 1 more Smart Citation

Electricity Market Design in Croatia within the European Electricity Market—Recommendations for Further Development

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Development of Distributed Energy Resource (DER) technologies enabled the owners of controllable energy assets to shape their wholesale market participation responsively and in a coordinated manner [1], [2]. To address the environmental and operational challenges, besides making the clean energy generation available and cheap, the question remains whether wholesale market prices could be inferred from the supply/demand mix on the grid and, then, used to create a feedback for "shaping" energy asset's production or consumption.…”

Section: Introductionmentioning

confidence: 99%

A Holistic Approach to Forecasting Wholesale Energy Market Prices

Radovanović

Nesti

Chen

2019

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

Electricity market price predictions enable energy market participants to shape their consumption or supply while meeting their economic and environmental objectives. By utilizing the basic properties of the supplydemand matching process performed by grid operators, known as Optimal Power Flow (OPF), we develop a methodology to recover energy market's structure and predict the resulting nodal prices by using only publicly available data, specifically grid-wide generation type mix, system load, and historical prices. Our methodology uses the latest advancements in statistical learning to cope with high dimensional and sparse real power grid topologies, as well as scarce, public market data, while exploiting structural characteristics of the underlying OPF mechanism. Rigorous validations using the Southwest Power Pool (SPP) market data reveal a strong correlation between the grid level mix and corresponding market prices, resulting in accurate day-ahead predictions of real time prices. The proposed approach demonstrates remarkable proximity to the stateof-the-art industry benchmark while assuming a fully decentralized, market-participant perspective. Finally, we recognize limitations of the proposed and other evaluated methodologies in predicting large price spike values.

show abstract

“…The futures market is normally used for risk hedging. In general, European wholesale markets are divided in day-ahead and intraday (or hour-ahead) sessions [35].…”

Section: Iberian Electricity Market-mibelmentioning

confidence: 99%

Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model

et al. 2017

View full text Add to dashboard Cite

Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 e/MWh for day-ahead market and a maximum value of 2.53 e/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions.

show abstract

Electricity markets overview — Market participation possibilities for renewable and distributed energy resources

Cited by 17 publications

References 0 publications

Electricity Market Design in Croatia within the European Electricity Market—Recommendations for Further Development

Electricity Market Design in Croatia within the European Electricity Market—Recommendations for Further Development

A Holistic Approach to Forecasting Wholesale Energy Market Prices

Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model

Contact Info

Product

Resources

About