Using GIS data and satellite-derived irradiance to optimize siting of PV installations in Switzerland

For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland.

Reliable Averages and Risky Extremes

Annelen Kahl, Michael Lehning, Viet Anh Nguyen, Karine Maria Sarrasin

With the perspective of Switzerland’s phase-out from nuclear energy, solar energy potential may take a leading role for the country’s future in renewable energy. Unlike nuclear power stations, photovoltaic (PV) production is prone to intermittency as it depends on the immediate solar irradiance, which fluctuates in space and time. If a large percentage of Switzerland’s electricity was to be derived from solar radiation, stochastic fluctuations pose a risk to the robust supply and healthy function of the electricity network. For most efficient PV planning and siting, it is hence imperative to understand and quantify this variability in solar radiation, in order to anticipate average production as well as worst-case scenarios. Based on 12 years of satellite derived, spatially distributed data of daily average surface incoming shortwave radiation (SIS) this work analyses standard statistics, spatial correlation patterns and extreme conditions of cloud cover over Switzerland. Having compared different irradiance products, we decided to use the SIS product captured on the Meteosat Second Generation satellites, because it provides the most reliable snow/cloud discrimination, which is essential for spatial analysis over alpine terrain. Particularly in regions with high elevation differences, correlation between cloud cover and elevation undergo an annual cycle. In winter more clouds are found in the valleys, while in summer convective clouds dominate at higher elevations. The highest average irradiance values occur in the southern parts of the country, and make the cantons of Vallais, Tessin and Grison ideal candidate locations for PV installations. Simultaneously the Tessin shows a higher risk of periods with long lasting cloud cover, which would discourage from relying too much on solar power in that area. However looking at the question of suitability by studying spatial and temporal correlations of extremes, we see that the Tessin appears to be comparably decoupled from the rest of the country, and leads us to believe that this zone plays a valuable role in compensating temporary deficits in solar production from other regions of the country. This is just one of many example that highlight the complexity of spatio-temporal variability in solar irradiance and its implications for a reliable electricity supply in a future renewable Switzerland.

2016

Risks and Reliability in a Fully Renewable Switzerland

Stuart John Bartlett, Annelen Kahl, Michael Lehning

In Switzerland, the government has made ambitious plans for a major energy transition. There is a planned phase out of nuclear facilities by mid-century, their capacity replaced by an expansion of hydroelectric infrastructure, new geothermal installations, and a considerable number of new solar and wind plants. The principle challenge of this transition is the variational nature of renewable energy. For example, Switzerland generates significantly more hydroelectric power during the snowmelt season than in mid-winter, and solar power has lower yields in the winter. Thus a 100% renewable Switzerland is a desirable goal but brings great challenges, which require specific methods of management. In this work, we carry out a first order assessment of a future Swiss energy system powered exclusively by renewable energy, and highlight the principle operational risks. We approximate yields from the various renewable sources as a function of time using meteorological data for the five year period: 2010-2014. We then highlight power surpluses and deficits with respect to domestic demand. In these situations, energy trade or energy storage must be elicited. We also perform simple power flow simulations of this fully renewable Swiss energy system, allowing us to calculate a lower estimate of the storage facilities required to smooth out seasonal variations. The conclusions raise several fundamental questions concerning the optimal infrastructure investments to be made as Switzerland undergoes its energy transition.

2015

Thermo-Economic Optimisation of Solar Tower Thermal Power Plants

James Spelling

Amidst a backdrop of rapidly increasing world-wide electricity demand, solar thermal power generation shows great potential for supplying the electricity needs of numerous countries in the Sun-belt regions of the world. In these regions, the absence of significant biomass, hydrological or geothermal reserves makes solar thermal power the most promising solution for meeting that most fundamental of demands: energy. Amidst the different options available for harnessing the Sun’s power, solar thermal technologies have been shown capable of producing electricity at the most economically viable rates [32]. However, all currently existing solar thermal power plants have been based around the use of Rankine, or steam turbine, cycles which are limited in the efficiencies they can achieve. In order to make better use of the Sun’s energy, higher efficiency cycles should be used. With their high concentration ratios, solar thermal power tower systems are amongst the best options for making use of the Sun’s potential. As the energy delivery temperature of central receiver systems is higher, they harness the solar radiation at a higher exergy level [4]. This higher temperature also opens the road to the use of more advanced thermodynamic cycles. Hybrid fossil-fuel – solar systems are also imaginable [13], as the energy delivery temperature is compatible with standard gas turbine cycles. Hybrid systems can help mitigate the requirements of thermal energy storage, as well as reducing the perceived risk when investing in new solar technology, which stimulates research and development, as well as providing employment. Recent developments in the field of high temperature volumetric receivers [10] along with rock- based packed-bed storage systems have opened up an interesting possibility. High temperature receivers allow the use of higher-efficiency combined-cycle setups, whereas packed-bed units offer the possibility of cheap storage. Larger storage volumes allow pure-solar systems to extend their power production into the night, making hybrid options less attractive. This is compounded by the common practice of guaranteeing a preferred tariff for electricity sales from pure-solar sources With this in mind, a complete dynamic model of a power plant based on the pure-solar concept has been elaborated. The performance of the setup is evaluated over a range of days, using solar insolation profiles obtained from satellite data. In order to examine different design options and their impact on the performance of the power plant, a multi-objective, thermo-economic optimisation of both the power plant superstructure and operating conditions was performed using the new, dynamic models. By means of an evolutionary algorithm [17], a family of Pareto-optimal points were obtained, representing the trade-off between increased power plant efficiency, and lower levelised energy costs. Through use of optimisation, it was shown that exergetic efficiencies in the region of 21-27% can be achieved, for relatively low power outputs of between 3 and 11 MWe. These configurations correspond with levelised electricity costs in the region of 14-21 UScts/kWhe. In most regions, the use of solar power is encouraged by the guarantee of a preferential tariff for electricity sales from renewable sources. Sale of electricity at a price of around 24 UScts/kWhe [32] should therefore be imaginable, ensuring the economic viability of solar thermal power tower systems. It can be concluded that, when properly designed, solar thermal power plants based on combined cycles are both economically and thermodynamically promising. By raising the efficiency of the plant, the size of the solar collector field is diminished, increasing the otherwise low energy densities of solar power systems. By reducing the levelised electricity costs, solar thermal power plants become more economically viable, accelerating their construction and thus, hopefully, reducing our dependence on fossil-fuels.