Long-Term Decision on Wind Investment with Considering Different Load Ranges of Power Plant for Sustainable Electricity Energy Market

Valinejad, Jaber, Marzband, Mousa, Akorede, Mudathir, Elliott, Ian D., Godina, Radu, Matias, João Carlos de Oliveira and Pouresmaeil, Edris (2018) Long-Term Decision on Wind Investment with Considering Different Load Ranges of Power Plant for Sustainable Electricity Energy Market. Sustainability, 10 (10). ISSN 2071-1050

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Official URL: https://www.mdpi.com/2071-1050/10/10/3811

Abstract

The aim of this paper is to provide a bi-level model for the expansion planning on wind investment while considering different load ranges of power plants in power systems at a multi-stage horizon. Different technologies include base load units, such as thermal and water units, and peak load units such as gas turbine. In this model, subsidies are considered as a means to encourage investment in wind turbines. In order that the uncertainties related to demand and the wind turbine can be taken into consideration, these effects are modelled using a variety of scenarios. In addition, the load demand is characterized by a certain number of demand blocks. The first-level relates to the issue of investment in different load ranges of power plants with a view to maximizing the investment profit whilst the second level is related to the market-clearing where the priority is to maximize the social welfare benefits. The bi-level optimization problem is then converted to a dynamic stochastic mathematical algorithm with equilibrium constraint (MPEC) and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a real transmission network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the investments different load ranges of power plants on long-term strategic decision-making.

Item Type: Article
Uncontrolled Keywords: capacity investment; market power; wind resources; dynamic planning; stochastic approach
Subjects: H800 Chemical, Process and Energy Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Paul Burns
Date Deposited: 22 Oct 2018 12:26
Last Modified: 01 Aug 2021 12:50
URI: http://nrl.northumbria.ac.uk/id/eprint/36384

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