The large integration of wind energy into electrical systems poses important challenges to the power operators in the scheduling of the production and in the management of the network. This leads to the necessity to m...
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The large integration of wind energy into electrical systems poses important challenges to the power operators in the scheduling of the production and in the management of the network. This leads to the necessity to modify the current industry procedures, such as the unitcommitment (UC) and the Economic Dispatch (ED), to take into account large amounts of wind power production. Even if an exhaustive literature exists on the general unit commitment problem, devoted on how to improve its mathematical formulation and its solution algorithm, the research that considers the unit commitment problem with wind generators is limited. In this work, a new unitcommitment model in presence of wind energy resources has been defined and analyzed, in order to formulate and solve the problem of determining the best configuration (optimal mix) of available thermal, hydro and wind power plants, taking into account proper emission considerations and the risk associated with the use of wind turbines.
This paper presents a novel approach to solve the constrained unit commitment problem using the Selective Self-Adaptive Ant Colony Optimization (SSACO) for improving search performance by automatically adapting ant po...
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This paper presents a novel approach to solve the constrained unit commitment problem using the Selective Self-Adaptive Ant Colony Optimization (SSACO) for improving search performance by automatically adapting ant populations and their transition probability parameters, which cooperates with the Candidate Path Management Module (CPMM) and the Effective Repairing Heuristic Module (ERHM) in reducing search space and recovering a feasible optimality region so that a high quality solution can be acquired in a very early iterative. A new concept of the Relativity Pheromone Updating (RPU) is also introduced to provide a reasonable evaluation of the pheromone trail intensity among the agents. The proposed SSACO method not only enhances the convergence of search process, but also provides a suitable number of the population sharing which conducts a good guidance for trading-off between the importance of the visibility and the pheromone trail intensity. The proposed method has been performed on a test system up to 100 generating units with a scheduling time horizon of 24 hours. The numerical results show the most economical saving in the total operating cost when compared to the previous literature results. Moreover, the proposed SSACO topology can remarkably speed up the computational time of ant colony optimization, which is favorable for a large-scale UC problem implementation.
The vital role in power system is that to optimally utilize the resources to meet the demand where the generation scheduling can be performed by unitcommitment. In this paper the formulation of unitcommitment has be...
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ISBN:
(纸本)9781509056835
The vital role in power system is that to optimally utilize the resources to meet the demand where the generation scheduling can be performed by unitcommitment. In this paper the formulation of unitcommitment has been discussed and the solution is obtained by the Conventional Dynamic Programming method. The Hybrid Genetic With Differential Evolution Algorithm was proposed. In this Hybrid algorithm a new strategy had been followed that the Genetic Algorithm had been performed for the Economic Dispatch problem and the results of the Economic Dispatch (manipulated by GA) has been incorporated in the unit commitment problem and then the problem was evaluated by Differential Evolution Algorithm. Comparatively the Hybrid Genetic With Differential Evolution Algorithm yields better results satisfying several unitcommitment Constraints where the objective of minimum total cost had been obtained. The proposed algorithm is performed on 4 generating system and IEEE standard 10 generating unit system.
Accurate sizing of power reserve (PR) due to inaccurate forecast of both renewable energy sources (RES) and load demand in a microgrid can provide substantial cost reductions. This paper proposes two strategies to dis...
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ISBN:
(纸本)9781509014101
Accurate sizing of power reserve (PR) due to inaccurate forecast of both renewable energy sources (RES) and load demand in a microgrid can provide substantial cost reductions. This paper proposes two strategies to dispatch the PR into different power generators. The first one uses only micro gas turbine (MGT). The second one uses MGTs plus PV based active generators (AGs). The latter enables the RES to cover the system load demand and PR for some period during a day. To implement those methods, firstly an urban microgrid with PV power generators is introduced. Then, day-ahead optimal planning with dynamic programming (DP) for unit commitment problem (UCP) is applied under several non-linear constraints. Finally, a case study application has been completed to verify the proposed methods.
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