Fully decentralised multi-area dynamic economic dispatch for large-scale power systems via cutting plane consensus

2016 ◽  
Vol 10 (10) ◽  
pp. 2486-2495 ◽  
Author(s):  
Wenmeng Zhao ◽  
Mingbo Liu ◽  
Jianquan Zhu ◽  
Licheng Li
2020 ◽  
Vol 7 (4) ◽  
pp. 621-630
Author(s):  
Riyadh Bouddou ◽  
Farid Benhamida ◽  
Ismail Ziane ◽  
Amine Zeggai ◽  
Moussa Belgacem

Electricity markets are open after the deregulation of power systems due to competition. An optimization problem based on dynamic economic dispatch has recently come up in the new context of deregulated power systems known as bid-based dynamic economic dispatch (BBDED). It is one of the major operations and control functions in the electricity markets used to determine the optimal operations of market participants with scheduled load demands during a specified period. BBDED involves power generation companies (GENCOs) and customers to submit energy and price bids to the independent system operator (ISO) in a day-ahead market. The ISO clears the market with the objective of social profit maximization. In this paper, a BBDED problem is solved using an improved simulated annealing algorithm (ISA), including system constraints with different periods under bidding strategies. The proposed ISA technique is implemented in MATLAB and applied on a 3-unit system, a 6-unit system, and a 40-unit large-scale system. The proposed ISA is evaluated by comparison with relevant methods available in the literature, to demonstrate and confirm its potential in terms of convergence, robustness, and effectiveness for solving the BBDED problem.


2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yaming Ren

With the continuous development of the world economy, the development and utilization of environmentally friendly and renewable energy have become the trend in many countries. In this paper, we study the dynamic economic dispatch with wind integrated. Firstly, we take advantage of the positive and negative spinning reserve to deal with wind power output prediction errors in order to establish a dynamic economic dispatch model of wind integrated. The existence of a min function makes the dynamic economic dispatch model nondifferentiable, which results in the inability to directly use the traditional mathematical methods based on gradient information to solve the model. Inspired by the aggregate function, we can easily transform the nondifferentiable model into a smooth model when parameter p tends to infinity. However, the aggregate function will cause data overflow when p tends to infinity. Then, for solving this problem, we take advantage of the adjustable entropy function method to replace of aggregate function method. In addition, we further discuss the adjustable entropy function method and point out that the solution generated by the adjustable entropy function method can effectively approximate the solution of the original problem without parameter p tending to infinity. Finally, simulation experiments are given, and the simulation results prove the effectiveness and correctness of the adjustable entropy function method.


Energy ◽  
2015 ◽  
Vol 93 ◽  
pp. 2175-2190 ◽  
Author(s):  
Anbo Meng ◽  
Hanwu Hu ◽  
Hao Yin ◽  
Xiangang Peng ◽  
Zhuangzhi Guo

1989 ◽  
pp. 22-34
Author(s):  
M. Ruddin Ab. Ghani ◽  
Prof. M.G Singh

Dynamic multi-period economic dispatch for large-scale power systems is considered. The formulation presented caters for loading and deloading rates, limits on generators outputs, spinning reserves requirements and group power import-export limits. It is also suitable for implementation within a constraint relaxation strategy. The solution algorithm is based on a Dantzig-Wolfe decomposition, which yields a capacitated transshipment subproblem along with a master problem solved by the Revised Simplex method.The computational efficiency of the algorithm renders it suitable for on-line dispatch.


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