Multiobjective CVaR Optimization Model and Solving Method for Hydrothermal System Considering Uncertain Load Demand

In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective...

Full description

Saved in:
Bibliographic Details
Published in:Mathematical problems in engineering Vol. 2015; no. 2015; pp. 1 - 10
Main Authors: Qin, Chao, Li, Huan-huan, Ju, Liwei, Tan, Zhongfu, Peng, Daoxin
Format: Journal Article
Language:English
Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2015
John Wiley & Sons, Inc
Subjects:
Algorithms
Confidence intervals
Constraints
Decision theory
Electric power
Electrical loads
Energy consumption
Engineering
Entropy
Fuzzy
Fuzzy logic
Fuzzy set theory
Hydroelectric power stations
Hydrothermal systems
Integer programming
Linear programming
Mathematical analysis
Mathematical models
Methods
Mixed integer
Multiple objective analysis
Neural networks
Objectives
Operation scheduling
Optimization
Optimization models
Pollutants
Random variables
Risk levels
Scheduling
Storage capacity
Thermal power plants
Thermal simulation
China
ISSN:1024-123X, 1563-5147
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective optimization model and its solving method. In the optimization model, load demand’s actual values and deviation values are regarded as random variables, scheduling objective is redefined to meet confidence level requirement and system operation constraints and loss function constraints are taken into consideration. To solve the proposed model, this paper linearized nonlinear constraints, applied fuzzy satisfaction, fuzzy entropy, and weighted multiobjective function theories to build a fuzzy entropy multiobjective CVaR model. The model is a mixed integer linear programming problem. Then, six thermal power plants and three cascade hydropower stations are taken as the hydrothermal system for numerical simulation. The results verified that multiobjective CVaR method is applicable to solve hydrothermal scheduling problems. It can better reflect risk level of the scheduling result. The fuzzy entropy satisfaction degree solving algorithm can simplify solving difficulty and get the optimum operation scheduling scheme.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1024-123X
1563-5147
DOI:10.1155/2015/741379