Italian Power Market Research Articles

The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market

In this paper we investigate the role of Renewable Energy Sources (RES) on the Italian power exchange. The purpose of this analysis is to assess the impact of electricity generation from RES on the reduction of CO2 emissions and on the value of the power supply. The study is based on hourly zonal micro-data for 2018 from the Italian power market and identifies the amount of avoided carbon emissions related both to crowded-out thermal units and to potential “load-shedding” situations. Finally, the investigation leads to the assessment of both the economic value of RES penetration and to the economic value of the CO2 emissions avoided by renewable power generation. The results show that the annual savings of carbon emissions nationwide amount to nearly 22 Mt CO2 whereas the value of CO2 reduction is estimated at €348 million. The economic savings from large and small-scale wind and solar generation in 2018 account for nearly €19 billion and welfare is increased by 44%, thus confirming the net positive effect arising from RES promotion.

The Zonal and Seasonal CO2 Marginal Emissions Factors for the Italian Power Market

This paper estimates the seasonal and zonal \({\mathrm{CO}}_{2}\) marginal emissions factors (MEFs) from electricity production in the Italian electricity system. The inclusion of the zonal configuration of the Italian wholesale power market leads to a complete measurement of marginal emission factors which takes into account the heterogeneous distribution of RES power plants, their penetration rate and their variability within the zonal power generation mix. This article relies on a flexible econometric approach that includes the fractional cointegration methodology to incorporate the typical features of long-memory processes into the estimation of MEFs. We find high variability in annual MEFs estimated at the zonal level. Sardinia reports the highest MEF (0.7189 \({\mathrm{tCO}}_{2}\)/MWh), followed by the Center South (0.7022 \({\mathrm{tCO}}_{2}\)/MWh), the Center North (0.4236 \({\mathrm{tCO}}_{2}\)/MWh), the North (0.2018 \({\mathrm{tCO}}_{2}\)/MWh) and Sicily (0.146 \({\mathrm{tCO}}_{2}\)/MWh). The seasonal analysis also shows a large variability of MEFs in each zone across time. The heterogeneity of results leads us to recommend that policymakers consider the zonal configuration of the power market and the large seasonal variability related to carbon emissions and electricity generation when designing incentives for renewable energy sources expansion and for achieving emission reduction targets.

Measuring Demand Elasticity in the Italian Power Market: a Bayesian Experiment under dual pricing scheme

This study run experiment aiming to provide a flexible and analytically elegant framework to reliably estimate the price elasticity of electricity demand. Inference pertains to the demand at hourly level in the Italian wholesale electricity market and uses individual demand bid data. Individuals' bids represent the ex-ante willingness to pay and thus allows for constructing a market demand grounded in the consumer behavior theory, by exploiting the duality approach. Bayesian econometric estimation is applied, relaxing homoskedasticity assumptions of the traditional linear regression model. It allows to identify robust results, showing that elasticity varies significantly among hours of the day, zone segmentation as well as the level of equilibrium price. Bayesian inference provides also the opportunity to include prior information sourced from previous studies and the institutional struc- ture governing the agents' behavior. This prior information involves some degree of uncertainty, for this reason Bayesian approach assigns it a probability distribution. Using Bayes rule, prior information are then updated according to the observed data. Results validate the market reform designed to foster competition and increase wel- fare even through the time-varying pricing schemes that trigger the consumers' price reaction.

The long-run relationship between the Italian day-ahead and balancing electricity prices

We study the convergence of day-ahead and balancing prices for the Italian power market. The zonal time-series of the prices are evaluated, seasonally adjusted and tested to assess their long-run properties. We focus on the dynamic behavior of the four continental price zones of Italy (North, Central-North, Central-South and South). Using a sample of data that spans the last decade and applying the fractional cointegration methodology, we show the existence of long-run relationships. This signals the existence of convergence between prices in each zone but zone Central-South, where prices are divergent. We also measure the average price difference, and analyse how it evolves over time. Price differences dynamically reduce for all zones except for Central-South. We comment the results and provide an interpretation for the differences across zones. We also discuss policy consequences for both Italian and other markets.

Pricing reliability options under different electricity price regimes

Abstract Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first derived by means of closed-form pricing formulae, which are obtained under several assumptions about the dynamics of electricity prices and strike prices. Then, the value of the Reliability Option is simulated under a real-market calibration, using data of the Italian power market. We perform sensitivity analyses to highlight the role of the level and volatility of both power and strike price, of the mean reversion speeds and of the correlation coefficient on the Reliability Options' value. Finally, we calculate the parameter model risk to quantify the impact that a model misspecification has on the equilibrium value of the RO.

Pricing Reliability Options Under Different Electricity Prices’ Regimes

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first derived by means of closed-form pricing formulae, which are obtained under several assumptions about the dynamics of electricity prices and strike prices. Then, the value of the Reliability Option is simulated under a real-market calibration, using data of the Italian power market. We finally perform sensitivity analyses to highlight the impact of the level and volatility of both power and strike price, of the mean reversion speeds and of the correlation coefficient on the Reliability Options' value.

Renewable Generation and Network Congestion: An Empirical Analysis of the Italian Power Market

This article empirically investigates the impact of renewable production on congestion using a unique database on the Italian Power Market, where zonal pricing is implemented. We estimate two econometric models: a multinomial logit model, to assess whether renewables increase the occurrence of congestion, and a two stage least squares (2SLS) model to evaluate the impact of wind and photo-voltaics on congestion costs. Our analysis suggests that larger renewable supply in importing regions decreases the probability of congestion compared to the no congestion case, while the reverse occurs when renewable production is located in an exporting region. The 2SLS estimations reveal that the same mechanisms explain the level of congestion costs. Our results also highlight that the magnitude of the congestion effects, both in terms of probability and costs, is very sensitive to the location of the historical efficient production, mainly hydro power, and to the geographical configuration of the transmission network.

Impact of the phase out of French nuclear reactors on the Italian power sector

The present paper proposes an analysis concerning the impact of the reduction of the net electricity flow between France and Italy due to the phase out of French nuclear power plants. The analysis is performed by using a bid stack model which offers an approximate, but reliable representation of the Italian power system, as shown by extensive validation on historical data.The study takes into account sixteen scenarios given by the combination of different assumptions on the operating life of French nuclear reactors, fuel price, renewables development and demand level. Furthermore, a Business As Usual scenario is implemented as reference case.The results have shown that some scenarios determine tight conditions for the Italian power market and provoke an increase of the clean spark of 13 €/MWh with respect to the Business As Usual scenario. At the same time, an increase of the load factor of gas turbines from 0.5% to 4% is also detected. This situation requires substantial interventions in order to re-balance the system.On the contrary, scenarios which imply a more aggressive development of renewables and low increase of the demand, even in the case of a relevant phase out of nuclear capacity in France, do not determine tight conditions on the Italian power market, therefore it is not necessary to adopt particular measures.

Forecasting The Italian Day-Ahead Electricity Price Using Bootstrap Aggregation Method

Electricity price forecasting has become a crucial element for both private and public decision-making. This importance has been growing since the wave of deregulation and liberalization of the energy sector on a global scale since the late 1990s. Given these facts, this paper is an attempt to establish and demonstrate a precision based applicable forecasting model for wholesale electricity prices with respect to the Italian power market on an hourly basis. Artificial intelligence models such as neural networks and bagged regression trees are utilized, although they are rarely used to forecast electricity prices. After model calibration, bagged regression trees with exogenous variables comprised the final model. The selected model outperformed neural network and bagged regression with a single price used in this paper, it also outperformed other statistical and non-statistical models used in other studies. We also confirm certain theoretical specifications of the model. As a policy tool, this model could be used by energy traders, transmission system operators and energy regulators for an enhanced decision-making process.

Intermittent Renewable Generation and Network Congestion: An Empirical Analysis of Italian Power Market

The literature demonstrates the likely reduction of wholesale electricity prices due to a larger penetration of renewable energy sources (RES). When markets are organized as two or more inter-connected sub-markets within a larger power market the final impact of increasing RES production may be less straightforward given the presence of network constraints. We tests this phenomenon by analyzing the impact of RES production on the probability of congestion and on the size of congestion cost in Italy. Using a database with hourly observations for a five year period we estimate two econometric models on five zonal pairings: a multinomial logit model for the occurrence and direction of congestion and a three stage least square model for the size of congestion costs. The analysis suggests that the effect of a larger local wind and solar supply is to decrease the probability of suffering congestion in entry and to increase the probability of causing a congestion in exit compared to no congestion case. Increasing hydroelectric production has a similar effect. These results hold for both importing and exporting regions, but importing regions are less likely to cause congestion in exit, therefore the installation of new RES capacity in these zones may have a positive effects in terms of flow balance between regions. Concerning the cost level, a larger local RES supply seems to push the congestion cost towards negative values as it decreases the marginal cost for balancing the system. This is true for all zones in the case of explicit congestion cost, but it is only verified in importing regions in the case of implicit congestion cost. This result suggests that the increase of RES production should be promoted in importing zones, but the overall growth should be controlled in order to avoid congestion in the opposite direction.

The Impact of Solar Penetration on Solar and Gas Market Value: An Application to the Italian Power Market

We assess the impact of solar penetration in the Italian wholesale electricity market on the market value of solar with respect to gas sources, measured as the ratio between the relative price they respectively earn and the average daily electricity price (value factor). We find that, on average, an increase of solar generation has a negative impact on the price earned by solar producers, thus causing a marginal departure from the grid parity condition. The relation between solar production and its market value is not constant over the years, while it depends on the degree of solar penetration. It is positive for very low levels of solar production while, as production increases, its marginal impact on the solar market value decreases and eventually becomes negative. An opposite relation is found when looking at the Gas market value. As solar displaces gas mainly during the peak-price hours, an initial solar penetration reduces the gas market value. However, as the solar share further increases, gas producers adapt their biding strategies. They switch production from the peak to the off-peak hours, where they exploit their temporary market power to increase the off-peak price. As a result, the relative price earned by gas producers is higher than the average daily price, increasing their market value with respect to renewable sources.

The merit-order effect in the Italian power market: The impact of solar and wind generation on national wholesale electricity prices

Italy promoted one of the most generous renewable support schemes worldwide which resulted in a high increase of solar power generation. We analyze the Italian day-ahead wholesale electricity market, finding empirical evidence of the merit-order effect. Over the period 2005–2013 an increase of 1GWh in the hourly average of daily production from solar and wind sources has, on average, reduced wholesale electricity prices by respectively 2.3€/MWh and 4.2€/MWh and has amplified their volatility. The impact on prices has decreased over time in correspondence with the increase in solar and wind electricity production. We estimate that, over the period 2009–2013, solar production has generated higher monetary savings than wind production, mainly because the former is more prominent than the latter. However, in the solar case, monetary savings are not sufficient to compensate the cost of the related supporting schemes which are entirely internalized within end-user tariffs, causing a reduction of the consumer surplus, while the opposite occurs in the case of wind.