The share of wind power generation is steadily increasing and it reached 20.4% of Germany's power supply in 2018. Thus wind power is becoming a critical infrastructure with major contributions to power supply and power system grid stability. Consequently a resilient operation of offshore wind farms (OWFs) is required under normal and disturbed conditions. Resilience stands for the ability of a complex system to proactively and reactively maintain its functionality and performance despite failures or manipulations. A functional model describes the technical behavior of engineered, cyber-physical systems in relation to the intended task or results of the system. It is a representation of the operation, functionality and performance of the system, e.g. in the form of a block diagram. The block diagram consists of components performing, according to their technical characteristics, specified functions on the inputs. Applied to the OWF the components can be grouped into several layers representing the main functional processes. Within this paper we consider the threat of system failures triggered through cyber-physical attacks, based on the vulnerability of the OWFs to such attacks as documented in the literature. Most of the main functional processes can be manipulated maliciously. The functional model is used to discuss the impacts of different scenarios of cyber-physical attacks and their resulting cascade effects, which may cause a non-resilient behavior of the OFW. Crucial parameters and signals can be manipulated maliciously. Limit thresholds can be exceeded by far even under normal environmental and power grid conditions. Excessive mechanical stresses, electrical and thermal loads can be realized, leading to extreme damage or even destruction of components/subsystems without the possibility of reactive intervention or timely recovery. We propose measures on component and functional level for closing the mentioned security gaps to ensure the resilience of the OWF.

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-This paper analyzes the different methods available today for treating major issues in developing countries. The authors discuss problems which have already been addressed by existing models and those that need to be solved. INTRODUcnONThe energy situation in developing countries is getting more and more complex. While in the industrialized countries a more or less stable level of the energy demand has been reached, developing countries still face twindling growth rates for both, commercial and traditional forms of energy. An adequate energy supply infrastructure which has to cope with this drastically increased demand will have to manage the technological feasibility and reliability problems as well as the financial restrictions associated herewith. The ilIlJ"inent depletion of natural fossil resources, and the irreversible negative effects on the environment leads to a growing awareness of the intertemporal and intergenerational character of the energy problem.In order to cope with this complex situation, the decision maker has a variety of pOlitical instruments at his disposal, which cover measures from direct price and quantity regulations to pricing policies and the promotion of investments in specific economic sectors or favoring the relevant research and development capabilities.All these activities are influenced by a number of uncertainties, which often are beyond the control of the respective country, like the world prices for energy carriers for example. Also, due to the close interaction of the different economic and social sectors of the economy, one may not regard the specific actions in isolation, but should consider their mutual interference also. This entity of measures, effects and feedbacks results in a complex and challenging planning task, and requires thorough analyses, which is usually very data intensive. For that reason, computer based planning tools are most suitable to assist in the rational decision making process.Recent developments in the field of computer based energy planning methods go from specific single fuel, single sector models to more complex integrated systems. Also there is a tendency away from large mainframe computer implementations to user-friendly mini-, micro-and personal computers.705

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