TY - GEN
T1 - Objective PDF-Shaping-Based Economic Dispatch for Power Systems with Intermittent Generation Sources via Simultaneous Mean and Variance Minimization∗
AU - Wang, S. B.
AU - Wang, H.
AU - Fan, R.
AU - Zhang, Z. F.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/21
Y1 - 2018/8/21
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85053130323&partnerID=8YFLogxK
U2 - 10.1109/ICCA.2018.8444293
DO - 10.1109/ICCA.2018.8444293
M3 - Conference contribution
AN - SCOPUS:85053130323
SN - 9781538660898
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 927
EP - 934
BT - 2018 IEEE 14th International Conference on Control and Automation, ICCA 2018
PB - IEEE Computer Society
T2 - 14th IEEE International Conference on Control and Automation, ICCA 2018
Y2 - 12 June 2018 through 15 June 2018
ER -