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The latest measure for the development of photovoltaics in Greece utilizes the net-metering scheme. Under this scheme the energy produced by a PV system may be either consumed by the local loads or be injected to the grid. The final cost reported in an electricity bill depends upon the energy produced by the PV system, the energy absorbed from the grid and the energy injected to the grid. Consequently, the actual electricity consumption profile is important to estimate the benefit from the use of this renewable energy source. The state latest statistics in Greece for households reveal that the typical electrical consumption is 3750 kWh while 10244 kWh are consumed in the form of thermal energy. We adopt in our calculations the above amount of electrical energy but assume four different scenarios. These different hourly profiles are examined to study the effects of synchronization upon the final cost of energy. The above scenarios are applied to areas in different climate zones in Greece (Heraklion, Athens and Thessaloniki) to examine the dependence of the hourly profiles and the solar potential upon the financial data with respect to internal rate of return, payback times, net present value and the levelized cost of energy. These parameters are affected by the initial system cost and the financial parameters.

The multi-factor partitioning model (MFP) is one of the shift-share analysis models and constitutes an essential contribution to the effort of describing and understanding a region’s growth. The purpose of the present paper is: 1) To present, the multi-factor partitioning model and its connection to traditional and homothetic one; 2) To explain why the use of standardized relative changes in the use of the MFP model ignores two effects: the distribution effect and the structure effect; 3) To propose a modification of multi-factor partitioning model to take into account the previous mentioned effects; 4) To apply the multi-factor partitioning and the proposed modified multi-factor partitioning model in order to identify growth regional patterns in thirteen Greek regions, and show that the use of multi-factor partitioning model instead the proposed modified model, misleads us to the results.

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