The integration of a European Electricity Market has leaded to one single market with multi-area which are considered as bidding zones; currently, it regards only the day-ahead market. The Price Coupling of Regions (PCR) project is an initiative for the day ahead market of seven power exchanges APX, Belpex, EPEX SPOT, GME, Nord Pool Spot, OMIE, and OTE. The Italian Power Exchange (GME) has become a part of the PCR since 24^th January 2015. Thus, the impact of PCR on GME after one year of the operation needs to be investigated. In this paper, the authors evaluate the impact of PCR on the Italian Power Exchange one year before and after 24^th January 2015 from three points of view: (i) the convergence of electricity price, (ii) congestion management, and (iii) the price maker in case of no congestion. The used data is available on GME, EPEX Spot, France TSO, Austria TSO and ENTSO-E websites for 2014, 2015 and 2016.

In microgrids, distributed generators that cannot be dispatched, such as a photovoltaic system, need to control their output power at the maximum power point. The fluctuation of their output power should be minimized with the support of the maximum power point tracking algorithm under the variation of ambient conditions. In this paper, a new maximum power point tracking method based on the parameters of power deviation ($\Delta P_{PV}$), voltage difference ($\Delta V_{PV}$), and duty cycle change ($\Delta D$) is proposed for photovoltaic systems. The presented algorithm achieves the following good results: (i) when the solar radiance is fixed, the output power is stable around the maximum power point; (ii) when the solar radiance is rapidly changing, the generated power is always in the vicinity of maximum power points; (iii) the effectiveness of energy conversion is comparable to that of intelligent algorithms. The proposed algorithm is presented and compared with traditional and intelligent maximum power point tracking algorithms on the simulation model by MATLAB/Simulink under different radiation scenarios to prove the effectiveness of the proposed method.

Today, the coupling of Day-Ahead Market in Europe is extensively studied. One of the challenges of the market clearing model is the National Uniform Price used in Italy and known as PUN (“Prezzo Unico Nazionale”) as it introduces nonconvexity in the model resulting in high computation time. In literature, various proposals are made to efficiently find the PUN; among them, the most promising are the iterative procedure and complementarity theory. The goal of the paper is to re-formulate these approaches and compare them to identify their advantages and disadvantages. Tests are made on the real data obtained from the official websites for 10 ^th -15 ^th of March, 2016.