A Framework for Power System Operational Planning under Uncertainty Using Coherent Risk Measures
Abstract : With the increasing integration of renewable energy sources (RESs) and the implementation of dynamic line rating (DLR), the accompanying uncertainties in power systems require intensive management to ensure reliable and secure operational planning. However, while numerous approaches and methods in the literature deal with uncertainties, they have not been analyzed axiomatically. This paper presents an analysis of risk in power system operation using coherent risk measures, elaborating on the origin of risk and the mechanisms of its management in the presence of various sources of uncertainty. To illustrate the practicality and benefits of coherent risk measures, a risk-averse asymmetry robust unit commitment (UC) model is established. It is based on coherent reformulations of the uncertain reserve and line flow constraints and is formulated in the form of a compact computationally efficient mixed-integer second-order conic program (SOCP). The overall performance of the proposed framework is verified using the updated 2019 IEEE Reliability Test System and the ACTIVSg2000 test system over a year-long period.
? Modern power systems are in the process of undergoing significant changes caused by environmental, economic and social concerns.
? From the environmental perspective, in order to reduce the greenhouse gas emissions, many power systems actively retire existing fossil-fired generation capacity and replace it with intermittent renewable energy sources (RESs), primarily in the form of wind and solar power.
? A review of the forecasting methodologies and challanges for DLR is presented by the authors of and , who also discuss several of the existing DLR projects.
? It is an optimization problem, concerned with slowresponding thermal generating units, to determine the operation schedule of these generating units to meet forecast net load at minimum cost under different constraints and environments.
? This problem is challenging because of the high level of uncertainty in net load which results from load uncertainty and renewable generation uncertainty.
? Imposing reserve constraints on the UC problem, however, incurs extra operational cost, and does not explicitly model the uncertainty.
? Other uncertainties associated with UC problem include unexpected generator and transmission line outages.
• Real-time DLR estimation algorithm for a transmission line with limited number of weather stations is proposed in, while the authors of propose to combine direct and indirect measurements for a similar problem.
• A probabilistic forecasting method for DLR is proposed in that combines the Monte-Carlo simulations with the conductor thermal model.
• Ensemble weather-forecasting models are utilized in for the probabilistic day-ahead forecasting of DLR.
• The proposed models are entirely data-based and therefore do not require estimation of physical parameters of the conductors.
? We investigate and compare the performance of stochastic programming and robust optimization as the most widely studied approaches for unit commitment under net load uncertainty.
? The performance of these methods is assessed in out-of-sample simulation.
? Because the results of all approaches depend strongly on the risk parameter used, we also provide insights on approaches for practitioners who want to choose appropriate methods for their systems.
? In order to cope with the computational difficulties caused by a large number of scenarios, scenario reduction techniques are used frequently.
? Benders decomposition and progressive hedging are two methods to improve the performance of solving the SUC with a two-stage structure.
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