Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

The global climate and energy crisis has amplified the need for renewable energy sources, withsolar photovoltaic (PV) systems expected to play a significant role in the future energy mix. In this context, distributed energy systems (DES) are identified as part of the solution to address climate and energy challenges.With the increasing demand for photovoltaic energy sources, there is a growing requirement forefficient Business Case Tools (BCT) to analyze investments in distributed solar PV installations.A two-part model, consisting of a solar model and spot price data, was developed based onparameters such as solar radiation, location, angle, orientation, system losses, installedcapacity, and historical spot price data. The model was integrated with Power BI for investment calculations and visualization of results. The developed model provides approximations for solar PV system electricity production, which were validated against selected installations in allelectricity areas of Sweden. The validation revealed an average relative absolute error of 14.72 percent for the model. The conclusion drawn is that BCT can be utilized to analyze and visualize solar PV investments at specific locations in Sweden. The results indicate that Power BI, as a BCT, has limitations indynamic data collection but performs well in executing calculation of investments and visualizingthe results. Well-developed BCT can facilitate decision-making through real-time calculations and contribute to smoother implementation of distributed systems by providing detailed insightsinto their financial characteristics. Further research is needed to develop a model specificallytailored for distributed installations with storage capabilities. / Världen befinner sig i en global klimat- och energikris vilket ökat behovet av och efterfrågan på förnybara energikällor. Solceller förväntas utgöra en betydande del av den framtida energimixen. I kombination med detta identifieras distribuerade energisystem (DES) som endel av lösningen på klimat- och energifrågan. I takt med den ökade efterfrågan på fotovoltaiska energikällor ställs större krav på effektiva Business Case Tools (BCT) för att analysera investeringar i distribuerade solcellsanläggningar. En modell bestående av två delar, en solmodell och spotprisdata,utvecklades utifrån parametrarna solstrålning, plats, vinkel, riktning, systemförluster, installerad effekt samt historiska spotprisdata. Modellen sammankopplas med Power BI föratt utföra investeringskalkyler och visualisera resultatet. Den utvecklade modellen gerapproximationer för solcellsanläggningars elproduktion, vilket validerades mot utvaldaanläggningar i Sveriges samtliga elområden. Enligt valideringen uppgår modellens genomsnittliga relativa absoluta fel till 14,72 procent. Slutsatsen dras att BCT kan användas för att analysera och visualisera solcellsinvesteringar på specifika platser i Sverige. Resultatet visar att Power BI som BCT har brister när detkommer till dynamisk datainsamling, men genomför och visualiserar investerings kalkyler med enkelhet. Välutvecklade BCT kan användas för att underlätta beslutsfattande genomrealtidsberäkningar och kan bidra till en smidigare implementering av distribuerade systemgenom att belysa deras finansiella karaktär på ett detaljerat sätt. Fortsatt forskning krävs föratt ta fram en modell anpassad för distribuerade anläggningar med lagringsmöjligheter.