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Abstract The price effect of the rising share of renewable electricity, which is called ‘merit-order-effect’, leads to noticeable changes in the German power industry and debates about the electricity market design. This paper estimates the merit-order-effect induced by variable renewable energy in the German-Austrian electricity sector with a multivariate regression model. The research focus lies on the impact of the estimated effects on the marketability of variable renewable electricity generation. The results show a systematic decline of the average market revenues for wind and photovoltaic plants in the period from January 2011 to December 2013. Current market data shows a continuation of this trend into 2016. According to the German long term goals for the use of renewables, wind and solar power will play a crucial role in the future electricity generation mix. If investments in these technologies will be profitable without any regulatory remuneration mechanisms in addition to the market revenues, depends on the further cost degression and the development of the merit-order-effect.

Abstract The price effect of the rising share of renewable electricity, which is called ‘merit-order-effect’, leads to noticeable changes in the German power industry and debates about the electricity market design. This paper estimates the merit-order-effect induced by variable renewable energy in the German-Austrian electricity sector with a multivariate regression model. The research focus lies on the impact of the estimated effects on the marketability of variable renewable electricity generation. The results show a systematic decline of the average market revenues for wind and photovoltaic plants in the period from January 2011 to December 2013. Current market data shows a continuation of this trend into 2016. According to the German long term goals for the use of renewables, wind and solar power will play a crucial role in the future electricity generation mix. If investments in these technologies will be profitable without any regulatory remuneration mechanisms in addition to the market revenues, depends on the further cost degression and the development of the merit-order-effect.

Abstract Wind condition awareness is an important factor to maximize power extraction, reduce fatigue loading and increase the power quality of wind turbines and wind power plants. This paper presents a new method for wind speed estimation based on blade load measurements. Starting from the definition of a cone coefficient, which captures the collective zeroth-harmonic of the out-of-plane blade bending moment, a rotor-effective wind speed estimator is introduced. The proposed observer exhibits a performance similar to the well known torque balance estimator. However, while the latter only measures the average wind speed over the whole rotor disk, the proposed approach can also be applied locally, resulting in estimates of the wind speed in different regions of the rotor disk. In the present work, the proposed method is used to estimate the average wind speed over four rotor quadrants. The top and bottom quadrants are used for estimating the vertical shear profile, while the two lateral ones for detecting the presence of a wake shed by an upstream wind turbine. The resulting wake detector can find applicability in wind farm control, by indicating on which side of the rotor the upstream wake is impinging. The new approach is demonstrated with the help of field test data, as well as simulations performed with high-fidelity aeroservoelastic models.

Abstract Wind condition awareness is an important factor to maximize power extraction, reduce fatigue loading and increase the power quality of wind turbines and wind power plants. This paper presents a new method for wind speed estimation based on blade load measurements. Starting from the definition of a cone coefficient, which captures the collective zeroth-harmonic of the out-of-plane blade bending moment, a rotor-effective wind speed estimator is introduced. The proposed observer exhibits a performance similar to the well known torque balance estimator. However, while the latter only measures the average wind speed over the whole rotor disk, the proposed approach can also be applied locally, resulting in estimates of the wind speed in different regions of the rotor disk. In the present work, the proposed method is used to estimate the average wind speed over four rotor quadrants. The top and bottom quadrants are used for estimating the vertical shear profile, while the two lateral ones for detecting the presence of a wake shed by an upstream wind turbine. The resulting wake detector can find applicability in wind farm control, by indicating on which side of the rotor the upstream wake is impinging. The new approach is demonstrated with the help of field test data, as well as simulations performed with high-fidelity aeroservoelastic models.

Abstract Offshore wind energy is a seminal technology to achieve the goals set for renewable energy deployment. However, today's offshore wind energy projects are mostly not yet sufficiently competitive. The optimization of offshore wind turbine substructures with regard to costs and reliability is a promising approach to increase competitiveness. Today, interdisciplinary analyses considering sophisticated engineering models and their complex economic effects are not widespread. Existing approaches are deterministic. This research gap is addressed by combining an aero-elastic wind turbine model with an economic viability model for probabilistic investment analyses. The impact of different monopile designs on the stochastic cost-efficiency of an offshore wind farm is investigated. Monopiles are varied with regard to diameters and wall thicknesses creating designs with increased lifetimes but higher capital expenditures (durable designs) and vice versa (cheaper designs). For each substructure, the aero-elastic wind turbine model yields distributions for the fatigue lifetime and electricity yield and different capital expenditures, which are applied to the economic viability model. For other components, e.g. blades, constant lifetimes and costs are assumed. The results indicate that the gain of increased stochastic lifetimes exceeds the benefit of reduced initial costs, if the overall lifetime is not governed by other turbine components' lifetimes.

Abstract Offshore wind energy is a seminal technology to achieve the goals set for renewable energy deployment. However, today's offshore wind energy projects are mostly not yet sufficiently competitive. The optimization of offshore wind turbine substructures with regard to costs and reliability is a promising approach to increase competitiveness. Today, interdisciplinary analyses considering sophisticated engineering models and their complex economic effects are not widespread. Existing approaches are deterministic. This research gap is addressed by combining an aero-elastic wind turbine model with an economic viability model for probabilistic investment analyses. The impact of different monopile designs on the stochastic cost-efficiency of an offshore wind farm is investigated. Monopiles are varied with regard to diameters and wall thicknesses creating designs with increased lifetimes but higher capital expenditures (durable designs) and vice versa (cheaper designs). For each substructure, the aero-elastic wind turbine model yields distributions for the fatigue lifetime and electricity yield and different capital expenditures, which are applied to the economic viability model. For other components, e.g. blades, constant lifetimes and costs are assumed. The results indicate that the gain of increased stochastic lifetimes exceeds the benefit of reduced initial costs, if the overall lifetime is not governed by other turbine components' lifetimes.

Abstract The purpose of this work is two-fold. First, to introduce a comparison between steady state and dynamic test methods for two different collectors. Second, to design a solar water heating system to satisfy both hot water and space heating demands for a multi-family house in Alexandria, Egypt.

Abstract The purpose of this work is two-fold. First, to introduce a comparison between steady state and dynamic test methods for two different collectors. Second, to design a solar water heating system to satisfy both hot water and space heating demands for a multi-family house in Alexandria, Egypt.

Climate change and limited availability of fossil fuel reserves stress both the importance of deploying renewable energy sources (RES) for electricity generation and the need for a stronger integration of regional electricity markets. This analysis focuses on North African (NA) countries, which possess vast resources of renewable energy but whose electricity supply is still largely dependent on fossil fuels. An analysis of cost-optimized deployment scenarios for RES is conducted in five NA countries in 2030 and 2050. Three electricity models are combined to derive results covering trans-regional to sub-national level, including a detailed analysis of grid capacities and future transmission challenges. Further, opportunities for integration of European and NA electricity markets are evaluated. Results confirm that, by 2050, high RES shares – close to 100% – are possible in NA. Wind energy is the dominant technology. Concentrated Solar Power (CSP) plants also play an important role with rising RES shares due to the possibility to store thermal energy. Electricity exports to Europe gain particular importance in the period after 2030. Substantial transmission grid reinforcements on AC-level and the construction of a high voltage DC overlay grid are prerequisites for the forecasted scenarios.