The global solar PV market is growing fast, and so is the production and trade with photovoltaic products and peripherals. Until now, the largest development has taken place in highly developed and electrified countries with good administrative control over their electricity system. Recently, however, new markets in developing countries have become increasingly relevant in terms of market share, system sizes and installed capacities. Statistics from these types of countries are often weak or non-existent, leading to problems for global organizations such as the International Energy Agency (IEA) or the International Renewable Energy Agency (IRENA), whose task is to follow, analyze and document named development.  In this report, a method is presented in which customs data monitored by the ‘Market Analysis and Research’ section of the International Trade Centre, an agency of UN’s World Trade Organization, is analyzed and converted into annual installed PV capacity volumes. By complementing the basic data from the customs database with price statistics from IEA PVPS task 1 along with national module production data from IEA PVPS task 1 and the RTS cooperation a data conversion is executed.  The method has been improved incrementally, where different assumptions have been modified or added, so that the data conversion of exported and imported PV products, expressed in dollar per yearly quarter, match the official statistics of annual installed capacity for a number of reference countries with comprehensive PV capacity statistics. The sensitivity analysis shows that the method is sensitive to the accuracy of the annual domestic national PV module production data and to price changes of Chinese PV modules. For countries with accurate PV module production data, or countries with no module production, the method seems to be able to estimate the annual installed capacity in 2018 with an average difference of 21% and a maximum difference of ±38% and a total average difference of 12%, 17% and 11% for 2016, 2017 and 2018 respectively.  By implementing this method, an estimate on yearly installed capacities can be generated in all countries connected to the UN customs database and where the domestic module production is known. This gives the opportunity to at least get an assessment of how much PV that has been installed in developing countries that lack official statistics about their domestic PV market. The regions with the lowest existing data coverage in the world have been determined to be Africa and the Middle East. When applying the method on countries in Africa and the Middle East, larger capacities than the reference data were obtained.

Despite the share of renewable energies worldwide is increasing, which can help in reducing the CO2 emissions, their unpredictability has become a problem due to the mismatch between generation and demand. Among the different alternatives to solve this problem, energy storage is a very interesting solution. Depending on the aim of the storage, there are two types: intra‑day or seasonal. The former corresponds normally to a highly efficient and high‑cost storage, such as the Li‑ion; whilst the latter is a low efficient and low‑cost storage. An example of this second type of storage is the power‑to‑heat‑to‑power storage, whose efficiency is mainly determined by the heat‑to‑power converter, and it can be increased if the waste heat produced in the converter is reused in a combined heat and power system.Given that the residential sector represents a large amount of the global energy use (both electricity and heat), this study has considered a power‑to‑heat‑to‑power storage in a fully electrified residential building with a PV installation in order to increase self‑consumption and reduce the cost. Both the heating, electricity and cooling demand are supplied by the system.As this storage technology is currently under an early stage of development, this project aims to understand the main challenges for this storage and the advantages over a very well settled technology, such as the Li-ion. In order to achieve this objective, a model has been created in Matlab. A parametric study has been conducted in which optimum sizing of the components for several scenarios have been considered, as a means to identify the most important parameters that could hinder the feasibility of the power‑to‑heat‑to‑power storage system.From the optimization it was concluded that the scenarios with a thermally driven heat pump for cooling, resulted in larger installations leading to higher cost due to the low coefficient of performance. Regarding the other scenarios which consider an electrical heat pump for cooling, this technology can surpass the Li-ion performance for heat‑to‑power efficiencies over 20 %. In these cases, the feasibility is clearly hindered by the cost per energy capacity, which must be below 5 €/kWh and could be achieved with silicon; and the cost per power capacity that must be around 300 €/kW. An example of a heat‑to‑power converter could be the TPV technology which is a solid‑state converter, whose efficiency is currently around 30 % and is expected to reduce its cost up to 300 €/kW. In smaller systems, in which the stand‑by heat losses have more impact over the system’s feasibility due to the larger surface to volume ratio, it is imperative to reduce these heat losses, as well as reduce the cost per energy and power capacities. In addition, it is remarkable that there is no significant improvement when increasing the heat‑to‑power efficiencies over certain values. To finish, as this technology increases its feasibility when implemented in large systems, further studies should be done in the industrial and tertiary sector.

As fossil fuel sources continue to diminish, oil prices continue to increase, and global warming and CO2 emissions keep impacting the environment, it has been necessary to shift energy consumption and generation to a different path. Solar energy has proven to be one of the most promising sources of renewable energy because it is environmentally friendly, available anywhere in the world, and cost competitive. For photovoltaic (PV) system engineers, designing a PV system is not an easy task. Research demonstrates that different PV technologies behave differently under certain conditions; therefore energy production varies not only with capacity of the system but also with the type of module. For years, researchers have also studied how these different technologies perform for long periods of time, when exposed out in the field. In this study, data collected by the Florida Solar Energy Center for periods of over four years was analyzed using two techniques, widely accepted by researchers and industry, to evaluate the long‐term performance of five systems. The performance ratio analysis normalizes system capacity and enables the comparison of performance between multiple systems. In PVUSA Regression analysis, regression coefficients are calculated which correspond to the effect of irradiance, wind speed, and ambient temperature, and these coefficients are then used to calculate power at a predetermined set of conditions. This study allows manufacturers to address the difficulties found on system lifetime when their modules are installed out on the field. Also allows for the further development and improvement of the different PV technologies already commercially available.