Italian Electricity Market Research Articles

Novel approaches to the energy load unbalance forecasting in the Italian electricity market

In the present paper we study the statistical properties of the Italian daily electricity load market, by mean of different statistical methods, such, e.g., the exponential smoothing model, the ARMA-ARIMA model and the ARIMA-GARCH model, also providing results about the goodness of each of the proposed approaches. Moreover, we show how the aforementioned models behave if exogenous regressors, as the day of the week or the temperature, are additionally taken into account. Analysed methods are then exploited to perform the one-day ahead energy load prediction, where the main focus is on guessing the right sign of the energy load unbalance.

Investments and cleaner energy production: A portfolio analysis in the Italian electricity market

The recent climate change, global warming, environmental disasters and the economic crisis are only the first signs of the failure of an economic system that, for too long, shows an uncontrolled utilization of the planet wealth. The Italian electricity market, which is strongly dependent on hydrocarbons, only in recent years has seen a first attempt to change towards renewable resources for electricity production aimed at self-consumption and for feeding into the grid. This paper presents an economic analysis whose purpose is to evaluate the profitability of investments in renewable technologies for the production of electricity. Each renewable source has its own profitability dependent on a number of factors and subject to market fluctuations, cost and frequent changes in the incentive policies. Applying Portfolio Theory is possible to select the right mix of renewable energy sources and simulate its evolution. Moreover the presented analysis can be useful for energy planners to select future green scenarios finalized to the reduction of emissions and energy imports through the increasing use of renewable energy.

Renewable Energy and Market Power in the Italian Electricity Market

The Italian electricity market has been characterized by a remarkable increase of renewable energy source (RES) supply since 2010, which has determined relevant structural changes in the electric system. Noticeably, during favorable weather conditions, such as sunny or windy hours, increasing supply of RES generation exerts a downward pressure to the formation of the equilibrium price in the market and at the same time forces an increase in line congestion. The aim of this paper is to investigate whether such RES increase has affected the exercise of market power in the Italian Power Exchange (IPEX), explicitly considering transmission line congestion. We employ our approach to construct the residual demand curve and to disentangle the measure of the unilateral market power from the congestion rent. We compute the zonal Lerner index during the period 2009 to 2013 for the main generators in the Italian day-ahead market and we analyze the correlation among market power, congestion and RES supply. In particular, we investigate whether RES development has affected congestion and firm's strategic behavior, empirically testing whether structural changes have occurred in market power or in congestion rent. Our results show that the exercise of market power has been considerably weakened during peak hours by the massive competition of RES, but it has been surprisingly reinforced in specific off-peak hours, in the absence of solar RES and in specific zones, where congestion yields market splitting. These findings support pro-competitive market regulation and reform strategies, and shed light on the impact of RES and congestion on market outcomes.

Optimal Price Design in the Wholesale Electricity Market

In this paper, we construct an optimal price design mechanism to determine the equilibrium in the day-ahead electricity market, specifically aimed at solving the uncomfortable conflict between conventional thermal sources (CTS) and renewable energy sources (RES). We find that the actual hourly market design is inadequate to achieve an efficient solution in the presence of a large and increasing share of RES. It is not conducive to catalyzing the correct price signal for future investments and does not take into account welfare considerations. Our proposal for a new market design is based on three main pillars. We state pro-competitive incentives to CTS participation in the market. We take into full account the opportunity cost of RES for society and propose correct price signals on the demand side through an optimal Ramsey pricing scheme. We show an empirical application to the Italian electricity market, using empirical measures of LCOE for RES and empirical estimation of heterogeneous buyers' behavior. The results show improvement in efficiency and welfare in the Italian electricity market with respect to the existing zonal market prices for suppliers and uniform price for buyers.

Market Power and Transmission Congestion in the Italian Electricity Market

Analysis of market power in electricity markets is relevant for understanding the competitive development of the industry’s restructuring and liberalization process, but in the existing literature, there is not an adequate consideration of line transmission congestion. The aim of this paper is to propose a new approach to measuring market power in the Italian Power Exchange (IPEX), explicitly considering transmission line congestion. We construct a new measure of the residual demand curve to disentangle unilateral market power from congestion rent for the main Italian generators during the period April 2004 to December 2007. In Italy, this period was one of stable transmission network structure. Following the approach of Wolak (2003, 2009), we measure the unilateral market power with the Lerner index (LI), computed as the inverse of the residual demand elasticity. In conclusion, the correct modeling of the residual demand curve including transmission congestions enables us to compute the zonal LI and therefore more accurately measure the market power when congestion occurs. Our results show that various generators exercise market power only in specific zones. These findings provide deeper understanding of market outcomes in the presence of congestion, suggesting appropriate policy directions for market surveillance and competition regulation.

Constrained auction clearing in the Italian electricity market

Most of the liberalized electricity systems use the auction as a market model. The complexity of the underlying optimization formulation depends on the technical and regulatory constraints that must be considered. In Italy, the auction clearing should include not only congestion management limitations, but also a challenging regulatory constraint imposing that, while the zonal prices are allowed on the selling side, a uniform purchasing price has to be applied for all the zones of the Italian system. Such constraint introduces several complexities such as non-linearity and integrality. In this paper we discuss the modeling issues arising in the Italian context and we propose, in addition, a mechanism for the priority management of the offers/bids acceptance. We test the behavior of the models developed on a set of problems that represent all the possible scenarios that can be met in practice. The numerical results demonstrate the validity and the effectiveness of the proposed models.

A System of Hourly Demand in the Italian Electricity Market

The purpose of this paper is to analyze and test demand behavior in the organized electricity market. According to a theoretical framework of heterogeneous agents’ behavior, we estimate a complete multi-stage system weakly separable using individual demand bid data in the Italian Power Exchange. The novel contribution of this paper is twofold. Firstly, we model hourly demand of heterogeneous groups of agents acting in the Italian electricity market with a simultaneous system for all 24 hours. Secondly, we empirically measure the entire structure of expenditure elasticities and cross price elasticities for all 24 hours of the day, ascertaining whether hourly electricity demands can be considered normal or luxury goods and substitutes or complements in an organized electricity market. Econometric estimation shows that price elasticity tends to be higher when hourly price peak. Moreover, electricity exhibits both substitutability and complementarity characteristic in different hours of the day, the former during the day and the latter during the night. Electricity appears to be a normal good during nighttime and a luxury good during daytime. The demand structure has welfare improving policy implications, because appropriate regulation can favor consumer behavior adjustment to shave consumption away from peak prices, thus yielding lower aggregate equilibrium expenditures. To this end, we advocate reforming the actual administered two-price tariff structure to introduce real time pricing options for Italian final users.

Bayesian Analysis of Demand Elasticity in the Italian Electricity Market

The liberalization of the Italian electricity market is a decade old. Within these last ten years, the supply side has been extensively analyzed, but not the demand side. The aim of this paper is to provide a new method for estimation of the demand elasticity, based on Bayesian methods applied to the Italian electricity market. We used individual demand bids data in the day-ahead market in the Italian Power Exchange (IPEX), for 2011, in order to construct an aggregate demand function at the hourly level. We took into account the existence of both elastic and inelastic bidders on the demand side. The empirical results show that elasticity varies significantly during the day and across periods of the year. In addition, the elasticity hourly distribution is clearly skewed and more so in the daily hours. The Bayesian method is a useful tool for policy-making, insofar as the regulator can start with a priori historical information on market behavior and estimate actual market outcomes in response to new policy actions.

Ramsey prices in the Italian electricity market

In this paper, we derive optimal zonal prices in the Italian day-ahead electricity market using estimation of a complete system of hourly demand in 2010–2011. In Italy, the hourly equilibrium price for all buyers is computed as a uniform average of supply zonal prices, resulting from market splitting due to line congestion. We model ex-ante individual bids expressed by heterogeneous consumers, which are distinguished by geographical zones. Using empirical estimations, we compute demand elasticity values and new zonal prices, according to a Ramsey optimal scheme. This is a new approach in the wholesale electricity market literature, as previous studies have discussed the relative merit of zonal prices, considering only the issue of line congestion. Our results show that the optimal pricing scheme can improve welfare in the day-ahead Italian electricity market, with respect to both the existing uniform price scheme and the proposal to charge the existing supply zonal prices to the demand side.

Prediction of the Italian electricity price for smart grid applications

In this paper we address the problem of one day-ahead hourly electricity price forecast for smart grid applications. To this aim, we investigate the application of a number of predictive models for time-series, including methods based on empirical strategies frequently adopted in the smart grid community, Kalman Filters and Echo State Networks (ESNs). The considered methods have been suitably modified to address the electricity price forecast problem. Strategies based on daily re-adaptation of models’ parameters are taken into consideration as well. The predictive performance achieved by the considered models is assessed, and the methods are compared among each other on recent real data from the Italian electricity market. As a result of the comparison over three years data, ESN methods appear to provide the most accurate price predictions, which could imply significant economic savings in many smart grid activities, such as switching on power plants to support power generation from renewable sources, electric vehicle recharging or usage of household appliances.

Combined cycle unit commitment in a changing electricity market scenario

Abstract For Generation Companies (GENCOs) one of the most relevant issue is the commitment of the units, the scheduling of them over a daily (or longer) time frame, with the aim of obtaining the best profit. It strongly depends on the plant operational generation costs, which depend in turn on the choices taken at the design stage; it follows that design technical choices should also aim at determining the best generation cost structure of generating units with respect to the market opportunities. In the paper the unit commitment (UC) problem has been considered, with highlights on changes in the market scenario. The paper analyzes the relevance of some design choices (structure, size, regulation type) on the economics of the operation of gas–steam combined cycle generating units. To solve the UC problem, a recently proposed method for mixed integer nonlinear programming problems, with the use of a derivative free algorithm to solve the continuous subproblems, has been considered. The results for two GENCOs are reported: one managing a single unit and the other managing three units. Numerical examples show the sensitivity of the UC solutions to the market conditions and to the design choices on the regulation type in the evolving scenario of the Italian Electricity Market.

Marginal cost and congestion in the Italian electricity market: An indirect estimation approach

In this paper we construct an indirect measure of the supply marginal cost function for the main generators from the observed bid data in the Italian electricity market in the period 2004–2007. We compute the residual demand function for each generator, taking explicitly into account the issue of transmission line congestion. This procedure allows recovering correct zonal Lerner index and the implied measure of the marginal cost function. We find evidence of a stable U-shaped marginal cost function for three main Italian generators, but a flat function for ENEL, the former national monopolist. The policy relevance of our approach lies in the possibility to offer some empirical knowledge of the marginal cost function of each generator to the regulator to design appropriate policy measures geared to the promotion of competitive market conditions. We propose a new market surveillance mechanism, which is based on the principle of sanctioning excessive deviations from the estimated measure of the marginal cost function presented in this work.

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.

Market Power and Transmission Congestion in the Italian Electricity Market

Analysis of market power in electricity markets is relevant for understanding the competitive development of the industry's restructuring and liberalization process. Because the existing literature lacks adequate consideration of line transmission congestion, this paper sets forth a new approach to measuring market power in the Italian Power Exchange (IPEX) by explicitly taking into account transmission line congestion. We construct the residual demand curve to disentangle the measure of unilateral market power from congestion rent for the main Italian generators during the period of April 2004 to December 2007. In Italy, this was a period of stable transmission network structure. Following the approach of Wolak (2003, 2009), we measure the unilateral market power with the Lerner Index (LI) computed as the inverse of the residual demand elasticity. In conclusion, the correct modeling of the residual demand curve including transmission congestions allows us to compute the zonal LI and therefore more accurately measure the market power when congestion occurs. Our results show that various generators exercise market power in only some zones, which provides us with a deeper understanding of the IPEX and better support for designing appropriate market surveillance and competition regulation.

Measuring Oligopsony Market Power in the Italian Electricity Market: Preliminary Results

Measuring Oligopsony Market Power in the Italian Electricity Market: Preliminary Results

Techno-economic analysis of a small size short range EES (electric energy storage) system for a PV (photovoltaic) plant serving a SME (small and medium enterprise) in a given regulatory context

Considering the case of small-medium size plants based on PV (photovoltaic), an analysis was developed in order to model, simulate and optimize an electricity storage system to be coupled to a small photovoltaic plant applied to an industry load, to calculate its profitability in a given regulatory context. The case study is the current Italian electricity market. The analysis was done on a small industrial plant in the area of Torino (North-West Italy), with its own photovoltaic plant connected to the public electrical grid. After an analysis of the present situation, the aim of the analysis is to understand the behaviour, from an economic point of view, of the self-consumption of renewable energy in case of a sudden deregulation of the market (switch off of feed in tariffs or RES (renewable energy system) kWh).The study includes a sensitivity analysis of the main technical and economic parameters in order to identify which of them have the greatest influence on economic performance, and therefore which parameters have to be considered with special care by the producers (technical and economic parameters) and the regulatory authorities (regulations) to decide and optimize the adoption of storage systems as a way to sustain the massive introduction of RES in the energy arena.

Seawater pumping as an electricity storage solution for photovoltaic energy systems

The stochastic nature of several renewable energy sources has raised the problem of designing and building storage facilities, which can help the electricity grid to sustain larger and larger contribution of renewable energy. Seawater pumped electricity storage is proposed as a good option for PV (Photovoltaic) or solar thermal power plants, located in suitable places close to the coast line. Solar radiation has a natural daily cycle, and storage reservoirs of limited capacity can substantially reduce the load to the electricity grid. Different modes of pump operation (fixed or variable speed) are considered, the preliminary sizing of the PV field and seawater reservoir is performed, and the results are comparatively assessed over a year-long simulated operation. The results show that PV pumped storage, even if not profitable in the present situation of the renewable energy Italian electricity market, is effective in decreasing the load on the transmission grid, and would possibly be attractive in the future, also in the light of developing off-grid applications.

A Nash equilibrium simulation model for the competitiveness evaluation of the auction based day ahead electricity market

This paper presents a simulation model based on the Nash equilibrium notion for the auction based day ahead electricity generation market. The presented model enhances a previous formalism proposed in the related literature by employing empirical data distributions of the market clearing price as registered by the market authority (e.g. the Independent System Operator). The model is effective when power suppliers with different generation capacities are considered, differently from the starting model that unrealistically assumes equal capacities. The proposed approach aims at evaluating the electricity market competitiveness with regard to the bidder strategies in order to prevent their anticompetitive actions. The framework is applied to a real data set regarding the Italian electricity market to enlighten its effectiveness in different scenarios, varying the number and capacity of participating bidders. The model can be employed as a basis for a decision support tool both for market participants (to define their optimal bidding strategy) and regulators (to avoid collusive strategies).

Medium-term trading strategy of a dominant electricity producer

This paper presents a multi-objective two-stage bilevel stochastic programming framework for a dominant electricity producer to determine an optimal trading strategy in a deregulated electricity spot market in a medium-term time horizon: at the first stage and upper level, the dominant producer aims at maximizing its expected market share and profit, while taking into account the trade-off between the two objectives, and at the second stage and lower level, the independent system operator determines the dispatches and power flows on an hourly basis after realization of uncertainty in market demand, by solving an optimization problem which aims at maximizing the total social welfare. Through Karush–Kuhn–Tucker conditions, the lower level problem is formulated as a complementarity problem and subsequently the dominant producer’s optimal decision making problem as a two-stage stochastic mathematical problem with equilibrium constraints (SMPEC). To solve the SMPEC, it is proposed to reformulate the SMPEC as a mixed integer linear program by representing the complementarity constraints as a system of mixed integer linear inequalities with binary variables. Numerical tests results are reported through a medium size case study based on Italian electricity market.

Italian Energy Portfolio Analysis: An Interactive Renewable Investments Tool

The portfolio analysis is a method for the strategic selection of energy sources able to drive the sustainable evolution of the renewable energy balance. In this paper the portfolio theory is applied in the Italian electricity market for different renewable energy sources (biomass, hydro, photovoltaic and wind) with the aim to select, by diversification, optimal portfolios that minimize investment risk. This analysis can be useful for energy planners to select future green scenarios based on the increasing use of renewable energy.