Power
S. Abbasi; D. Nazarpour; S. Golshannavaz
Abstract
Background and Objectives: Distributed generations (DGs) based on renewable energy, such as PV units, are becoming more prevalent in distribution networks due to technical and environmental benefits. However, the intermittency and uncertainty of these sources lead to technical and operational challenges. ...
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Background and Objectives: Distributed generations (DGs) based on renewable energy, such as PV units, are becoming more prevalent in distribution networks due to technical and environmental benefits. However, the intermittency and uncertainty of these sources lead to technical and operational challenges. Energy storage application, uncertainty analysis, and network reconfiguration are apt therapies to resist these challenges. Methods: Energy management of modern, smart, and renewable-penetrated distribution networks is tailored here considering the uncertainties correlations. Network operation costs including switching operations, the expected energy not served (EENS) index as the reliability objective, and the node voltage deviation suppression as the technical objective are mathematically modeled. Multi-objective particle swarm optimization (MOPSO) is considered as the optimization engine. Scenario generation method and Nataf transformation are used in probabilistic evaluations of the problem. Moreover, the technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is deployed to make a final balance between different objectives to yield a unified solution.Results: To show the effectiveness of the proposed approach, the IEEE 33-node distribution network is put under extensive simulations. Different cases are simulated and interrogated to assess the performance of the proposed model.Conclusion: For different objectives dealing with different aspects of the network, remarkable achievements are attained. In brief, the final solution shows 4.50% decrease in operation cost, 13.07% improvement in reliability index, and 18.85% reduction in voltage deviation compared to the initial conditions.
A. Badri
Abstract
This paper represents a complete survey on Generation Companies’ (GenCos’) optimal bidding strategy problem in restructured power markets. In this regard after an introduction to competitive electricity markets, concept of optimal bidding strategy is presented. Considering large amount of ...
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This paper represents a complete survey on Generation Companies’ (GenCos’) optimal bidding strategy problem in restructured power markets. In this regard after an introduction to competitive electricity markets, concept of optimal bidding strategy is presented. Considering large amount of works accomplished in this area a novel classification is implemented in order to categorize the existing diverse studies. Accordingly, studies are classified in different categories based on market mechanism, trading mechanism, type of competition, transmission security, type of power plant, type of commodity and type of objective function. For each category, the corresponding studies are presented to show the effectiveness of each item. At the end, the impact of uncertainty and risk on GenCos’ optimal bidding strategy problem is represented and a number of applicable methods to simulate stochastic nature of the problem are investigated. The presented paper may be applicable for that group of researches that are interested in GenCos’ optimal bidding strategy to give a comprehensive perspective in this issue.
