There is a high level of financial risk associated with the direct participation of wind generation in liberalised electricity markets, due to the stochastic nature of output and imbalance charges set by market prices. The positioning of generation with respect to the market is therefore critical to successful trading activities. Examined is the use of risk characterisation to select the best output level for a wind generator to trade, dependant on maximising revenue and managing marginal costs from imbalances in a competitive market situation. Trading strategies based on utility risk assessment are presented as a possible way to improve market participation for wind generators based on these criteria.

Designing a power supply of a newly built property, investor has at his disposal whole range of technologies, skillful selection of which will minimize the total cost of supplying the facility with energy. Apart from renewable energy sources like photovoltaics, wind turbines or solar heating, classical technologies like district heating, micro/mini cogeneration unit or gas boiler can be used. For an optimal use of a complex power system, energy storages may be necessary, as well as an advanced control system. The choice of the property power supply structure is extremely important, because this decision will impact the costs that will be incurred by the owner over the next few decades. This article shows how to select the structure and parameters of power supply of residential premises, taking into account the characteristics of consumption of electricity, heat and weather conditions. The obtained solutions were analyzed depending on availability of district heating and local generation, adopted electricity tariff, as well as energy and capacity prices. The results demonstrated profitability of local generation in the form of cogeneration and wind energy for own consumption, while local generation focused on electricity sale to the grid and PV installations proved to be not economically feasible.

In Europe an increasing share of wind power is sold on the power market. Therefore more and more wind power generators become balancing responsible and face imbalance cost that reduce revenues from selling wind power. A comparison of literature illustrates that the imbalance cost of wind power varies in a wide range. To explain differences we indentify parameters influencing imbalance cost and compare them for case studies in Austria, Denmark and Poland. Besides the wind power forecast error also the correlation between imbalance and imbalance price influences imbalance cost significantly. Especially in systems with significant wind shares, an assessment of imbalance cost based on the amount of imbalance and average System Sell and System Buy Prices is therefore not reliable. While imbalance cost rather reflects cash flows within the clearing of imbalances, the presented concept of cost of imperfect forecast is better suited to reflect real cost incurred due to inaccurate wind power forecasts.