Different Methods for Congestion Management and Risk Management

Transmission congestion must be managed so that transmission capacity is utilised as efficiently as possible with minimal social welfare loss usually by system operator. Congestion management must provide incentives for investments in transmission network and generation capacity in the right areas. Minimizing the risks associated with different congestion management methods is important task for every market participant who is trading between different areas. Risk management, in that case is focused on the managing of different trade arrangements with a goal of hedging against uncertainty trading with electricity across the border. The development of systems like contracts for differences, financial transmission rights, transmission congestion contracts and the like is very important for encouraging new operators to enter the business and for boosting trades on the official market. However, all contracts involve price setting, which is influenced by the parties negotiating power, so while they do cover the risk of fluctuating energy prices they fail to eliminate the exercise of market power and the exploitation of dominant positions. In this paper we discuss the differences between these solutions with a focus on risk management issues in three regions: Scandinavia, Continental Europe and South East Europe. We discuss market-based mechanisms such as implicit and explicit auctions, counter trade and/or redispatch from an economic viewpoint. The advantages and disadvantages of these methods are considered, and the costs and benefits are assessed. Special emphasis is put on risk management, because transmission congestion risks may expose market players to severe losses. We demonstrate the main issues with numerical and graphical examples. Our findings illustrate that the potential benefits of a co-ordinated congestion mechanism are increase of market competition, maximum interconnection usage, and reduction of market player risk as well as generation of revenue in mar- ket-based methods