The high proliferation of converter-dominated Distributed Renewable Energy Sources (DRESs) at the distribution grid level has gradually replaced the conventional synchronous generators (SGs) of the transmission system, resulting in emerging stability and security challenges. The inherent characteristics of the SGs are currently used for providing ancillary services (ASs), following the instructions of the Transmission System Operator, while the DRESs are obliged to offer specific system support functions, without being remunerated for these functions, but only for the energy they inject. This changing environment has prompted the integration of energy storage systems as a solution for transfusing new characteristics and elaborating their business in the electricity markets, while the smart grid infrastructure and the upcoming microgrid architectures contribute to the transformation of the distribution grid. This review investigates the existing ASs in transmission system with the respective markets (emphasizing the DRESs’ participation in these markets) and proposes new ASs at distribution grid level, with emphasis to inertial response, active power ramp rate control, frequency response, voltage regulation, fault contribution and harmonic mitigation. The market tools and mechanisms for the procurement of these ASs are presented evolving the existing role of the Operators. Finally, potential barriers in the technical, regulatory, and financial framework have been identified and analyzed.

In this paper, detailed scalability and replicability plans have been developed to facilitate the adoption of innovation technologies in the pan-EU market. Smart grid development must enable both information and power exchange between suppliers and customers, thanks to the enormous innovation in intelligent communication, monitoring, and management systems. Implementing physical infrastructure alone is not enough, but a smart grid must include new business models and new regulations. In recent years, the number, participants, and scope of smart grid initiatives have increased, with different goals and results. FLEXITRANSTORE project integrates hardware and software solutions in all areas of the transmission system and wholesale markets, unleashing the potential for full flexibility of power systems and promoting the penetration of renewable energy sources and pan-EU markets. Full deployment of these demonstrated solutions requires a reasonable level of scalability and replicability to prevent project demonstrators from continuing local experimental exercises. Scalability and replicability are fundamental requirements for successful scaling-up and replication. Therefore, scalability and replicability enable or at least reduce barriers to the growth and reuse of project demonstrator results.

In this work we propose a new hybrid model, a combination of the manifold learning Principal Components (PC) technique and the traditional multiple regression (PC-regression), for short and medium-term forecasting of daily, aggregated, day-ahead, electricity system-wide load in the Greek Electricity Market for the period 2004–2014. PC-regression is shown to effectively capture the intraday, intraweek and annual patterns of load. We compare our model with a number of classical statistical approaches (Holt-Winters exponential smoothing of its generalizations Error-Trend-Seasonal, ETS models, the Seasonal Autoregressive Moving Average with exogenous variables, Seasonal Autoregressive Integrated Moving Average with eXogenous (SARIMAX) model as well as with the more sophisticated artificial intelligence models, Artificial Neural Networks (ANN) and Support Vector Machines (SVM). Using a number of criteria for measuring the quality of the generated in-and out-of-sample forecasts, we have concluded that the forecasts of our hybrid model outperforms the ones generated by the other model, with the SARMAX model being the next best performing approach, giving comparable results. Our approach contributes to studies aimed at providing more accurate and reliable load forecasting, prerequisites for an efficient management of modern power systems.

The approach of an integrated electricity market is widespread across Europe, since such a market structure has numerous benefits for both the grid and consumers. The current structure and the related policy framework of the electricity markets adopted within the European countries is based on a benchmark model, the so-called Target Model, which describes a reference energy market framework. In this paper, a comprehensive overview of the legislative effort and the resulting Target Model is provided, aiming to set the basis for the description of the adopted electricity markets in Europe. In a second stage, the current status of the Greek electricity market that operates under the Target model scheme is given via the analysis of the involved submarkets, i.e., the forward market, the day-ahead market, the intraday market, and the balancing market. An intricate case study of the Target Model operation in the Greek electricity market within a day of operation is examined, which actually completes the former description. Within the case study, the Greek electricity market is further investigated for its efficiency and the impact on the obtained electricity prices from the first day of the Target Model implementation, which took place in November 2020, and, finally, today is analysed. The results show an overall successful implementation and satisfactory performance of the Target Model in Greece, with an important main result being the reduction of prices in the balancing market and the increase of the intraday market liquidity. However, several challenges are identified and described in detail, while at the same time measures for their confrontation are proposed in order to improve market operation and fully exploit the benefits of the Target Model.

Italy, Greece, and, to a lesser degree, Bulgaria have experienced fast growth in their renewable generation capacity (RESc) over the last several years. The consequences of this fact include a decrease in spot wholesale prices in electricity markets and a significant effect on cross border trading (CBT) among neighboring interconnected countries. In this work, we empirically analyzed historical data on fundamental market variables (i.e., spot prices, load, RES generation) as well as CBT data (imports, exports, commercial schedules, net transfer capacities, etc.) on the Greek, Italian, and Bulgarian electricity markets by applying the Granger causality connectivity analysis (GCCA) approach. The aim of this analysis was to detect all possible interactions among the abovementioned variables, focusing in particular on the effects of growing shares of RES generation on the commercial electricity trading among the abovementioned countries for the period 2015–2018. The key findings of this paper are summarized as the following: The RES generation in Italy, for the period examined, drives the spot prices in Greece via commercial schedules. In addition, on average, spot price fluctuations do not affect the commercial schedules of energy trading between Greece and Bulgaria.

In this paper we examine and compare the efficiency of four European electricity markets (NordPool, Italian, Spanish and Greek) of different microstructure and level of maturity, by testing the weak form of the Efficient Market Hypothesis (EMH). To quantify the level of efficiency deviation of each market from the ‘ideal’ or ‘benchmark market of random walk’, we have constructed a Composite Electricity Market Efficiency Index (EMEI), inspired by similar works on other energy commodities. The proposed index consists of linear and nonlinear components each one measuring a different feature or dimension of the market efficiency such as its complexity, fractality, entropy, long-term memory or correlation, all connected to the associated benchmark values of the Random Walk Process (RWP). The key findings are that overall, all examined electricity markets are inefficient in respect to the weak form of EMH and the less inefficient market, as measured by the EMEI is the NordPool, closely followed by the Spanish market, with the Italian being the third. The most inefficient market is the Greek one. These results are in accordance with the predominant view about the maturity of these markets. This study contributes significantly on improving the research framework in developing consistent and robust tools for efficiency measurement, while the proposed index can be a valuable tool in designing improved guidelines towards enhancing the efficiency of electricity markets.