We will see that the temporal behaviour significantly changes with the size and the selection of the catchment area used for the power generation. We will also touch on the topics of backup and storage needs and the subject of grid capacities. After this I consider wind energy as major source of power production. And last but not least we will reflect on a possible combination of climate protection and development aid.

The best conditions are found in arid zones of high mountainous regions. Here the potential production is more than twice as high as we can expect in middle European countries. In Poland the production of a photovoltaic system will lie in the range of 130 kWh / (m² a) or approx. 900 Full Load Hours (FLH).

In this example only the production of Mauritania and Senegal in the Southern Sahara show a monthly variation similar to the mentioned electricity consumption. Within all the other regions the behaviour more or less shows an anticyclical pattern compared to the demand.

The costs of PV electricity production are relatively high, so that at the today's investment it seems to be an option for rural areas with high potential and without grid connection where it competes with other sometimes even more expensive techniques.

On this slide you can see for example the ratio between the average electricity production in December and July. As it is the case for the PV electricity production, in the southern Sahara we find that the production only changes slightly over the months while the variations increase considerably going to higher longitudes.

For example the Net Transfer Capacities from Morocco to Spain with its 350 MW and the 1100 MW from Spain to France would not allow high power transfer. But as e.g. can be seen from the calculations presented in the next slide the construction of new transport capacities using today's technologies economically seems to be quite feasible.

Using today's High Voltage DC (HVDC) technology to transport the electricity to Europe (e.g. Kassel GER) the costs of electricity would even for the furthest distance mentioned only increase by 30%. The underlying economical assumptions for HVDC technology are shown in the lower right table. The costs of electricity in Kassel do not seem to be very unreasonable. The option to import solar thermal electricity from Northern Africa to Europe becomes even more interesting if the investment costs for solar fields, the most costly part of SEGS power plants, are reduced. A reduction to roughly 50% of the today's field costs is expected as soon as a capacity of 7 GW of SEGS is erected world-wide. This will reduce the costs of electricity in Kassel to approx. 60% or below 12 DPf/kWh.

Assuming an efficiency of 30% for biomass power plants the secondary resources would be sufficient to e.g. deliver roughly one third of the annual Polish electricity consumption. The lower table exemplary shows a calculation for cost of electricity from Biomass.

• The investment costs are quite strongly dependent on the efficiency of the power plant, on the environmental standards within each country and on the size of the plant. The given costs may fit for German conditions.
• The fuel costs strongly also vary. E.g. some residues are much cheaper than the given example others may have negative costs since they contain substances harmful to the environment (This again could strongly influence the investment costs). The given prices of 2.4 DPf/kWhth are consistent with today's firewood prices and can even be achieved by biomass production for energetic purposes.

The principle of the Hot Dry Rock technique is shown in this slide. At least two wells have to be drilled to a depth of approximately 4000m. One of the wells is used to press water into the porous rock. Here the water heats up and within the second well it flows up to feed a thermal power unit which produces electricity. The HDRt enlarges the geothermal potential since the places where steam or hot water is found which could be used directly to drive a thermal power plant are very rare.

Here the attempt is made to estimate the costs starting from a reference case from the Electric Power Research Institute (EPRI). The assumptions of the reference case and of the underlying economic figures are given in the upper table. Temperature gradients as high as in the reference case will only be found at very few locations on earth, while temperature differences of e.g. 170 K between surface and 4000 m depth are much more common but still far better than average conditions. These conditions would probably allow the production of electricity at costs of 35 DPf/kWh.

Here we see the depth of the layer at which a temperature difference of 170K to the surface conditions is reached. The grey land regions are regions where the next measurement registered within the data collected by the International Heat Flow Commission (IHFC) is more than 300 km away or where the depth of the 170K layer is below 6000m.

The offshore conditions demonstrate very well where the best climate conditions for Energy towers can be found. Here neither transportation nor elevation losses for delivering the water to chimney‘s foot accrue. The best locations are found at the cost lines of the desert belts, where e.g. Passat Winds provide the dry and hot air.

The conditions on land are strongly influenced by the transportation and elevation losses for delivering the water to the chimney‘s foot.The best locations are found at the cost lines of the desert belts, where e.g. Passat Winds provide sufficient dry and hot air, the distance to the water sources are short and elevation to the towers base is low. From a European point of view the areas in the western Sahara and in the Persian Gulf are most interesting.

On this slide you can see for example the ratio between the average annual electricity production and the production in December. E.g. at the mid Saharan west coast we find that the production only slightly changes over the months. Some hundreds of kilometres south significantly higher production in European winter time can be found.

At good sites such as for example in the Persian Gulf region the climate would allow at least a small production at any time during the year. This can be seen from the calculated duration curve of an Energy Tower near Abu Dhabi. At this site the production reaches 40% of the rated power within 78% of the time during the year. A combined production of two Energy Towers, e.g. one close to Elat and the other about 1300 km away in Abu Dhabi, shows that the combination could further improve the temporal behaviour.

The costs of electricity in Kassel economically seem to be very interesting and thus would justify further research and efforts to erect at least a small scale pilot plant.

At the moment the highest rated power of Wind Turbines (WT) available in the market is 2.5 MW, while some efforts are being made to develop WTs with a rated power up to 5 MW.

On this slide you can see for example the ratio between the average electricity production in July and January. We see, that Europe is a typical winter wind region with maxima in winter and minima in summer. While for example at the Saharan west coast we find maxima of the production in summer. In some other regions the production in July and January are quite similar. So the idea of selecting the regions in order to get the best match of production and electricity consumption suggests itself.

Here you see the correlation of the change of power from two wind turbines printed versus the averaging time. It can be derived that fluctuations due to the low correlation within shorter time intervals of some minutes can be smoothened even within one bigger wind park.

For example the 5 minute correlation falls to almost zero after a distance as short as 20 km. While the 12 hour values reach a correlation coefficient of 0.2 at a distance of 500 km.

By the way: The potential production within the area shown only considering sites with more than 1500 FLH is about 100 times higher than the need of the European Union and Norway. So it is possible to be quite selective and choose only the better regions.

From the region shown on the previous slide 43 subregions with good wind conditions have been selected to study the temporal behaviour of their potential wind power production. Here the mean correlation of the power changes is shown over the region‘s distance. As we see from the monthly mean, which is the violet line, the mean correlation drops down to almost zero at a distance of roughly 2000 km. This means that even considerable monthly smoothing effects can be achieved as soon as the catchment area reaches this sizes.

1. Good wind sites within EU & Norway. (With restrictions due to the high population density.)
2. The Jamal Region with northern Russia.
3. Parts of Kazakhstan
4. Southern Morocco (The calculated production is rather conservative. Due to measurements in this region significantly higher production up to 5000 FLH is expected.)
5. Mauritania also has good wind conditions.

To use these potentials we have to have high transport capacities.

1. Good wind sites within EU & Norway. (With restrictions due to the high population density.)
2. The Jamal Region with northern Russia.
3. Parts of Kazakhstan
4. Southern Morocco (The calculated production is rather conservative. Due to measurements in this region significantly higher production up to 5000 FLH is expected.)
5. Mauritania also has good wind conditions.

To use these potentials we have to have high transport capacities.

As mentioned before the potential production within the area shown only considering sites with more than 1500 FLH is about 100 times higher than the demand of the European Union and Norway. So it is possible to be quite selective and choose only the better regions. As an example I selected the following.

1. Good wind sites within EU & Norway. (With restrictions due to the high population density.)
2. The Jamal Region with northern Russia.
3. Parts of Kazakhstan
4. Southern Morocco (The calculated production is rather conservative. Due to measurements in this region significantly higher production up to 5000 FLH is expected.)
5. Mauritania also has good wind conditions.

To use these potentials we have to have high transport capacities.

As mentioned before the potential production within the area shown only considering sites with more than 1500 FLH is about 100 times higher than the demand of the European Union and Norway. So it is possible to be quite selective and choose only the better regions. As an example I selected the following.

1. Good wind sites within EU & Norway. (With restrictions due to the high population density.)
2. The Jamal Region with northern Russia.
3. Parts of Kazakhstan
4. Southern Morocco (The calculated production is rather conservative. Due to measurements in this region significantly higher production up to 5000 FLH is expected.)
5. Mauritania also has good wind conditions.

To use these potentials we have to have high transport capacities.

1. Good wind sites within EU & Norway. (With restrictions due to the high population density.)
2. The Jamal Region with northern Russia.
3. Parts of Kazakhstan
4. Southern Morocco (The calculated production is rather conservative. Due to measurements in this region significantly higher production up to 5000 FLH is expected.)
5. Mauritania also has good wind conditions.

To use these potentials we have to have high transport capacities.

1. Good wind sites within EU & Norway. (With restrictions due to the high population density.)
2. The Jamal Region with northern Russia.
3. Parts of Kazakhstan
4. Southern Morocco (The calculated production is rather conservative. Due to measurements in this region significantly higher production up to 5000 FLH is expected.)
5. Mauritania also has good wind conditions.

To use these potentials we have to have high transport capacities.