Transmission Expansion Planning: Literature Review and Classification
—Power systems must be prepared to match the current growing demand for electrical energy. In this paper, the transmis sion network plays an important role, delivering the electric power generated in conventional power plants to load centers. For the last 45 years, the transmission network expansion...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universidad Loyola Andalucía |
| Repositorio: | Brújula |
| OAI Identifier: | oai:repositorio.uloyola.es:20.500.12412/4971 |
| Acceso en línea: | https://hdl.handle.net/20.500.12412/4971 |
| Access Level: | acceso abierto |
| Palabra clave: | Transmission expansion planning Power markets Network reliability Literary framework Generation and demand uncertainties Load modeling Investment Uncertainty Power system reliability Planning Reliability |
| Sumario: | —Power systems must be prepared to match the current growing demand for electrical energy. In this paper, the transmis sion network plays an important role, delivering the electric power generated in conventional power plants to load centers. For the last 45 years, the transmission network expansion planning (TNEP) problem has been widely studied; nowadays, TNEP, combined with new challenges, is being highly investigated, as researchers aim to reach a better solution. This paper presents a complete review and classification of the most significant works to date, providing a lit erary framework for TNEP specialists. Hence, a categorization of proposed models, case studies, innovations, and solution methods of the most relevant works regarding TNEP is provided. In order to establish a complete background, not only traditional approaches, but also those involving maintenance, uncertainties in generation and demand, reliability, electricity markets, energy storage, and risk management in TNEP are highlighted. This framework can help planners to improve previous formulations and methods and can propose more efficient models to better exploit existing infras tructure and reduce costs of investment |
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