Network extension versus redispatch: An economic and electro-technical analysisDeriving an improved regulatory framework for the electricity system using a coherent simulation of the electrical transmission network and the electricity market which account

哪些发电厂可以用来满足电力需求取决于可用的网络容量。网络的拥挤阻碍了使用成本最低的生产者。为了得到一个最优的电力系统，将这些“再调度成本”与通过扩展网络避免拥塞的成本进行比较至关重要。随机影响使得网络成本和再调度成本的比较更加复杂。传统上，发电厂或网络元件的计划外停电是这种随机影响的最突出的例子。这些影响通常被解释为“最坏情况”。网络计划在最糟糕的情况下仍然安全运行。可再生能源安装的强劲增长大大增加了由于天气相关的不确定性（风速，阳光）造成的随机影响。区域高度集中，特别是风力发电厂的高度集中，越来越多地导致网络中的压力情况。为了完全避免这些问题，需要大规模的网络扩展。因此，在评估网络扩展时，只考虑最坏情况变得越来越不充分;相反，应确定允许临时拥塞的最小成本。为了实现这一点，在项目的第一部分，将使用概率分布函数描述任何随机影响。这样就可以评估重新调度措施的频率和强度，然后将其与网络扩展成本进行比较。在项目的第一部分得出的最佳解决方案通常不是纯市场过程的结果。市场的不完善，如网络运营商之间的外部性，或发电厂的位置选择忽视对网络的影响，将阻止这一点。这就要求更好地理解市场设计和市场监管如何影响第一个最佳解决方案的实施。因此，该项目的第二部分将分析当前的市场机构，提出以下问题：它们是否为私人行为者提供了实施第一个最佳解决方案的激励？如果没有，如何改进？电力技术和经济学研究者之间的密切跨学科合作有望提供：1.改进电力网络中的不确定性会计。2.不确定性下的网络和发电的综合方法。3.提高对自由化能源市场中激励兼容实施的理解。

Which power plants can be used to meet demand for electricity depends on the network capacity that is available. Congestion of networks inhibits using the producers with the lowest costs. For deriving an optimal electricity system, it is crucial to compare these "redispatch costs" to the cost of avoiding congestion by extending the network. Stochastic influences make this comparison of network costs and redispatch costs more complicated. Traditionally, unplanned outages of power plants or of network elements were the most prominent examples of such stochastic influences. These influences usually were accounted for by "worst case" scenarios. Networks were planned to operate still safely under the worst possible circumstances. The strong increase in the installation of renewable energy sources has strongly increased the amount of stochastic influences due to weather related uncertainty (wind speed, sunshine). A high regional concentration, in particular of wind power plants, increasingly causes stress situations in the network. To fully avoid these, massive network extensions would be necessary. Therefore, for evaluating network extension, it becomes increasingly inadequate to look at worst case scenarios; rather, a cost minimum allowing for temporary congestion should be identified.To achieve this, in the first part of the project any stochastic influences will be depicted using probability distribution functions. This allows to evaluate the frequency and intensity of redispatch measures, which can then be compared to network extension costs. The optimal solution derived in the first part of the project will usually not be the outcome of a pure market process. Market imperfections like externalities between network operators, or locational choices of power plants disregarding effects on the network will prevent this. This calls for a better understanding of how market design and market regulation affects the implementation of the first best solution. Hence, the second part of the project will analyze the current market institutions by asking: Do they provide the incentives for private actors to implement the first best solution? If not, how could they be improved?The close inter-disciplinary co-operation between electro-technical and economics researcher promises to deliver:1.Improvements in accounting for uncertainty in electricity networks.2.An integrated approach to networks and generation under uncertainty.3.An improved understanding of incentive compatible implementation in liberalized energy markets.