Improving the deterministic reserve requirements method to mitigate wind uncertainty
|Authors:||Mogo, Jules Bonaventure|
|Advisor:||Cros, Jérôme; Kamwa, Innocent|
|Abstract:||Power grids are subject to a variety of uncertainties that may expose them to potential safety issues. Interruptions in electricity supply for instance, may result from an unseasonable temperature fluctuations or a power station outage, which are events of stochastic nature involving the weather or the failure of a component in the grid. The result may be sudden imbalances in supply and demand, leading to load interruptions. To plan for such unforeseen events, the grid carries ’reserve’, i.e., additional capacity above that needed to meet actual demand. However, scheduling the appropriate amount of reserve needed for a reliable and cost-effective grid operation is very challenging, especially in the context of increased uncertainties due to liberalization and the large-scale wind electric generators (WEGs) penetration to grid. Traditional grids assume a fixed knowledge of system conditions for the next day. Wind power being very poor to predict, an extra reserve generation to accommodate its uncertainty is required. Because WEGs aren’t built around spinning turbines, conventional units have been left stressed while responding to large and fast variations in the system net load. Given the temporal operating restrictions that limit their flexibility, the properly functioning of the electricity market can be altered as the energy transactions may not be carried out in realtime, exactly as agreed for security reasons. In this context, the use of the deterministic criteria alone as is the case today, may not be economical or reliable in limiting the risk of uncertainty; calling for sophisticated methods based on more-complex characteristics of uncertainty. This thesis proposes reliable and sound solutions to the increased variability and uncertainty in short-term power grid operations emanating from increasing the share of WEGs in the generation mix and competition from electricity markets. The conservativeness of the deter ministic method has been greatly improved with an adjustable extra generation reserve that accounts for the stochastic feature of WEGs. An inherent flexibility–design that attempts to reduce the onus placed on conventional units to balance the system has been considered. In doing so, the jerkings around these units while responding to large and fast variations in the system net load have been considerably mitigated. Adequate market policies that incentivize flexible resources to make their units with higher ramp rates available to follow dispatch signals have been crafted, thereby avoiding potential reliability degradation or costly out-ofmarket actions. A combined Security Constrained Unit Commitment (SCUC) and Optimal Power Flow (OPF) optimization problem that encompasses all the above mentioned goals has been formulated. Translated into a Mixed Integer Quadratic Programming (MIQP) problem that can return a feasible solution with a known optimality level, the SCUC-OPF engine has been used to investigate various effects of grids integration on reducing the overall operating costs associated with more wind power in the system. Last but not least, the effectiveness of our model to withstand contingencies has been done with a probabilistic model benchmark that accounts for the random nature of grid failure. This allows the adjustment of the Day- Ahead Market (DAM) strategy with respect to the Real-Time Market (RTM). Our model is proven to be more acceptable as it is time-saving, and has particular implications for wind integration studies as it can reverse the hidden cost of integrating WEGs to grid.|
|Document Type:||Thèse de doctorat|
|Open Access Date:||1 May 2019|
|Collection:||Thèses et mémoires|
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