scholarly journals A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming

Energies ◽  
2014 ◽  
Vol 8 (1) ◽  
pp. 233-256 ◽  
Author(s):  
Wushan Cheng ◽  
Haifeng Zhang
Keyword(s):  
Wind Power ◽  
Economic Dispatch ◽  
Chance Constrained Programming ◽  
Constrained Programming ◽  
Dynamic Economic Dispatch

scholarly journals Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1604
Author(s):  
Krešimir Fekete ◽  
Srete Nikolovski ◽  
Zvonimir Klaić ◽  
Ana Androjić
Keyword(s):  
Power System ◽  
Wind Power ◽  
Power Plants ◽  
Chance Constrained Programming ◽  
Transmission Network ◽  
Wind Power Plants ◽  
Hydropower Plants ◽  
Optimization Stage ◽  
Optimization Methodology ◽  
Constrained Programming

Stochastic production from wind power plants imposes additional uncertainty in power system operation. It can cause problems in load and generation balancing in the power system and can also cause congestion in the transmission network. This paper deals with the problems of congestion in the transmission network, which are caused by the production of wind power plants. An optimization model for corrective congestion management is developed. Congestions are relieved by re-dispatching several cascaded hydropower plants. Optimization methodology covers the optimization period of one day divided into the 24 segments for each hour. The developed optimization methodology consists of two optimization stages. The objective of the first optimization stage is to obtain an optimal day-ahead dispatch plan of the hydropower plants that maximizes profit from selling energy to the day-ahead electricity market. If such a dispatch plan, together with the wind power plant production, causes congestion in the transmission network, the second optimization stage is started. The objective of the second optimization stage is the minimization of the re-dispatching of cascaded hydropower plants in order to avoid possible congestion. The concept of chance-constrained programming is used in order to consider uncertain wind power production. The first optimization stage is defined as a mixed-integer linear programming problem and the second optimization stage is defined as a quadratic programming (QP) problem, in combination with chance-constrained programming. The developed optimization model is tested and verified using the model of a real-life power system.

The Influence Research of Complementarities of Electric Vehicles and Distributed Energy on Grid Spinning Reserve Capacity and Peak Regulation

2012 ◽  
Vol 608-609 ◽  
pp. 1623-1626
Author(s):  
Zi Heng Xu ◽  
Rui Ma ◽  
Shu Kui Li
Keyword(s):  
Wind Power ◽  
Electric Vehicles ◽  
Reserve Capacity ◽  
Chance Constrained Programming ◽  
Distributed Energy ◽  
Joint Operation ◽  
Spinning Reserve ◽  
Electric Company ◽  
Load Demand ◽  
Constrained Programming

This paper raises a model which concerns about spinning reserve capacity of output and predicted error based on chance-constrained programming. The distribution function is established on the load demand of electric vehicles. Considering the complementarities of electric vehicles and small hydro and wind power generations, this paper constructs a dispatch model on the participation of electric vehicles in reserve capacity and peak regulation. Joint operation of different units in the system achieved by genetic algorithm examines the influence from joint dispatch of electric vehicles and small hydro and wind power generations on spinning reserve capacity and peak regulation plan, setting different values of confidence to make comparison of electric charge in the entire system. According to the real operation statistics of an electric company in a certain province, the reliability and accuracy of the model was guaranteed.

Dynamic Economic Dispatch Incorporating Wind Power with Carbon Trading Scheme

2012 ◽  
Vol 487 ◽  
pp. 94-98
Author(s):  
Tung Sheng Zhan
Keyword(s):  
Wind Power ◽  
Co2 Emission ◽  
Economic Dispatch ◽  
Emission Trading ◽  
Trading Market ◽  
Accelerated Particle Swarm Optimization ◽  
Trading Scheme ◽  
Dynamic Economic Dispatch ◽  
The Relationship ◽  
Electricity Utility

This paper proposed an issue aiming at the goal of pierces the relationship between the emission trading scheme and dynamic economic dispatch (DED) problem for the electricity utility. A model of the CO2 emission trading market will be investigated and introduced into DED problem incorporating wind power plant and independent power providers (IPPs). Then, an accelerated particle swarm optimization (APSO) algorithm is introduced in order to avoid prematurity convergence of the original PSO and improve searching efficiency. Thus, APSO was used to determine the DED strategy of the utility with incorporation of wind power generation and contribution of IPPs. The CO2 emission trading is treated as the inner-cost, and the superfluous CO2 quotas will be resale into the market, whereas the shortage quotas can be purchased from the market.

Artificial Bee Colony Algorithm to Solve Dynamic Economic Dispatch Considering Wind Power Penetration

2013 ◽  
Vol 416-417 ◽  
pp. 2092-2096
Author(s):  
Xi He ◽  
Gao Xia Wang
Keyword(s):  
Wind Power ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Integrated System ◽  
Swarm Optimization ◽  
Abc Algorithm ◽  
Reasonable Time ◽  
Bee Colony ◽  
Dynamic Economic Dispatch

This paper use artificial bee colony algorithm (ABC) to solve dynamic economic dispatch (DED) problem in wind power integrated system for generating units with value-point effect and system-related constrains. The feasibility of the proposed method is validated with ten-unit-test systems for a period of 6 and 24 hours respectively. The effectiveness and feasibility of the artificial bee colony algorithm are demonstrated by comparing its performance with improved particle swarm optimization. Numerical results show that the ABC algorithm can provide accurate dispatch solutions within reasonable time for certain type of fuel cost functions.

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