Multiobjective optimization model for the connection of wind power generation to distribution networks

L. F. Ochoa, A. Padilha-Feltrin, J. R. S. Mantovani, G. P. Harrison

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Current energy policies are encouraging the connection of renewable energy generation to both transmission and distribution networks, mainly due to environmental concerns but also to promote energy diversification. In the last decade, several initiatives from industry and governments were taken to accelerate wind power projects resulting in successful commercial development of the technology. Consequently, wind power is expected to play an increasingly important role in the electric power system infrastructure and market. On the other hand, given that distribution networks were not planned to support insertion of power generation units (Distributed Generation), various studies have reported that such integration may create technical and safety problems. The main issues include where to locate and how to operate distributed generation to minimize the impact on distribution management. Moreover, special attention should be paid to wind power generation since its impact are time-variant given the nature of the renewable source.In this work a steady-state analysis considering the assessment of technical impacts such as losses and reverse power flows for time-variant loads and generation is proposed, aimed at finding a set of optimal connection points for wind power generation in medium voltage distribution networks. Depending on the network size and on the number of generators to be connected to the network, the problem presents a combinatorial nature, requiring an optimization tool able to handle multiple objectives. When using weighting factors for the multiobjective approach, the main advantage is the controllability of the emphasis of one impact (objective) over the other, giving flexibility to the distribution engineer (decision maker). Nevertheless, this approach needs a complete knowledge of the priority of each objective. Therefore, distribution engineers require different alternatives in decision making so they can be able to choose the most appropriate solution for the current situation without biasing any objective. Here, the impacts will be analyzed simultaneously based on the non-dominated sorting genetic algorithm (NSGA) leading to a more realistic and diversified set of solutions.With current legislation generally disallowing utility-owned generation, in practice, distribution engineers are limited in their ability to specify the connection point of a generation unit. Nevertheless, a multiobjective optimization analysis based on technical impacts permits knowing where this generation could be more beneficial for the studied distribution network, helping distribution engineers take decisions and even shape the nature of the contract that might be established between the utility and the distributed generator owner.A medium voltage distribution network considering its one-year basis demand profile is analyzed. Wind power generation is calculated based on wind speed measurements performed by the UK Meteorological Office for the central Scotland during 2003. Results are presented and discussed remarking the time-variant benefits and drawbacks of wind power generation.
Original languageEnglish
Title of host publicationX SEPOPE - Symposium of Specialists in Electric Operational and Expansion Planning
Number of pages9
Publication statusPublished - 2006

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