No abstract

No abstract

Many countries have adopted schemes to promote investments into renewable energy sources resulting, amongst others, in a high penetration of solar PV energy. The system integration of the increasing amount of variable electricity generation is therefore a highly important task. This paper focuses on a residential quarter with PV systems and explores how heat pumps and thermal and electrical storages can help to integrate the PV generation through self-consumption. However, self-consumption and PV integration are not only affected by technologies but also by pricing mechanisms. This paper therefore analyses the impact of different tariffs on the investment and operation decisions in a residential quarter and its interaction with the external grid. The considered tariffs include a standard fixed perkilowatt-hour price, a dynamic pricing scheme and a capacity pricing scheme. To account for the interdependent uncertainties of energy supply, demand and electricity prices, we use a module-based framework including a Markov process and a two-stage stochastic mixedinteger program. Analysing a residential quarter in Southern Germany as a case study, we find that the integration of a PV system is economically advantageous for all considered tariffs. The self-consumption rate varies between 58 − 75%. The largest PV system is built when dynamic prices are applied. However, the peak load from the external grid increases by a factor of two under this tariff without any incentive for reduction. In contrast, capacity pricing results in a reduction of the peak load by up to 35%.

No abstract

Abstract:Electricity from renewable energy sources (RES-E) is gaining more and more influence in traditional energy and electricity markets in Europe and around the world. When modeling RES-E feed-in on a high temporal and spatial resolution, energy systems analysts frequently use data generated by numerical weather models as input since there is no spatial inclusive and comprehensive measurement data available. However, the suitability of such model data depends on the research questions at hand and should be inspected individually. This paper focuses on new methodologies to carry out a performance evaluation of solar irradiation data provided by a numerical weather model when investigating photovoltaic feed-in and effects on the electricity grid. Suitable approaches of time series analysis are researched from literature and applied to both model and measurement data. The findings and limits of these approaches are illustrated and a new set of validation indicators is presented. These novel indicators complement the assessment by measuring relevant key figures in energy systems analysis: e.g., gradients in energy supply, maximum values and volatility. Thus, the results of this paper contribute to the scientific community of energy systems analysts and researchers who aim at modeling RES-E feed-in on a high temporal and spatial resolution using weather model data.