학술논문

Objective PDF-Shaping-Based Economic Dispatch for Power Systems with Intermittent Generation Sources via Simultaneous Mean and Variance Minimization
Document Type
Conference
Source
2018 IEEE 14th International Conference on Control and Automation (ICCA) Control and Automation (ICCA), 2018 IEEE 14th International Conference on. :927-934 Jun, 2018
Subject
Aerospace
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Cost function
Economics
Stochastic processes
Probability density function
Generators
Uncertainty
Language
ISSN
1948-3457
Abstract
With the ever increased penetration of renewables in power grid, economic power dispatch faces a challenge in terms of minimizing the generation cost which is increasingly affected by random factors and constraints subjected to random inputs. In this context, the cost functions are random for which the widely used mean value based minimization can only achieve limited profit gain. Indeed, as the probability density function (PDF) is a comprehensive measure of characteristics of any random variables, the desired optimization should address the shaping of the PDF of the generation cost function rather just its mean value. Through a simple case study, this paper firstly reveals the long tail PDF shape of the cost function when the traditional mean-value based optimization is used. This is then followed by the development of a novel PDF-shaping-based method that optimizes both the mean and variance of the PDF of the cost function. It has been shown that the proposed approach can reshape the PDF of the generation cost function so as to make it as left and as narrow as possible, leading to a significant low risk for high generation cost. Generic PDF shaping based optimization in [22] has also been described. Simulation tests have been included to show the effectiveness of the proposed approach and encouraging results have been obtained.