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Abstract:In this paper, we conduct a feasibility study of the wind energy potential in Gaza, which suffers from a severe shortage of energy supplies. Our calculated energy harvested from the wind is based on data for a typical meteorological year, which are fed into a small wind turbine of 5 kW power rating installable on the roof of residential buildings. The expected annual energy output at a height of 10 m amounts to 2695 kWh, but it can be increased by 35-125% at higher altitudes between 20 m and 70 m. The results also depict the great potential of wind energy to complement other renewable resources such as solar energy: the harvested energy of a wind system constitutes to up to 84% of the annual output of an equivalent power rating photovoltaic system and even outperforms the solar energy in the winter months. We also show that one wind turbine and one comparable photovoltaic system together could provide enough energy for 3.7 households. Hence, a combination of wind and solar energy could stabilize the decentralized energy production in Gaza. This is very important in a region where people seek to reach energy self-sufficient buildings due to the severe electricity shortage in the local grid.

Weather risk is one of the main causes for income fluctuation in agriculture. Since 1997, the economic consequences of weather risk can be insured with weather derivatives, which are offered for many different weather events, such as temperature, rainfall, snow or hurricanes. It is well known that the hedging effectiveness of weather derivatives is interfered by the existence of geographical basis risk, i.e., the deviation of weather conditions at different locations. In this paper, we explore how geographical basis risk of rainfall based derivatives can be reduced by regional diversification. Minimizing geographical basis risk requires knowledge of the joint distribution of rainfall at different locations. For that purpose, we estimate a daily multi-site rainfall model from which optimal portfolio weights are derived. We find that this method allows to reduce geographical basis risk more efficiently than simpler approaches as, for example, inverse distance weighting.

In the context of the rapid development of renewable energy in Germany in the last decade, and increased concerns regarding its potential impacts on farmland prices, this paper investigates the impact of wind energy and biogas production on agricultural land purchasing prices. To quantify the possible impact of the cumulative capacity of wind turbines and biogas plants on arable land prices in Saxony-Anhalt, we estimate a community-based and a transaction-based model using spatial econometrics and ordinary least squares. Based on data from 2007 to 2016, our analysis shows that a higher cumulative capacity of wind turbines in communities leads to higher farmland transaction prices, though the effect is very small: if the average cumulative capacity of wind turbines per community doubles, we expect that farmland prices per hectare increase by 0.4%. Plots that are directly affected by a wind turbine or part of a regional development plan, however, experience strong price increases.