Investment Incentives in Competitive Electricity Markets
Source abstract
Abstract
This paper presents the analysis of a novel framework of study and the impact of different market design criterion for the generation expansion planning (GEP) in competitive electricity market incentives, under variable uncertainties in a single year horizon. As investment incentives conventionally consist of firm contracts and capacity payments, in this study, the electricity generation investment problem is considered from a strategic generation company (GENCO) ′ s perspective, modelled as a bi-level optimization method. The first-level includes decision steps related to investment incentives to maximize the total profit in the planning horizon. The second-level includes optimization steps focusing on maximizing social welfare when the electricity market is regulated for the current horizon. In addition, variable uncertainties, on offering and investment, are modelled using set of different scenarios. The bi-level optimization problem is then converted to a single-level problem and then represented as a mixed integer linear program (MILP) after linearization. The efficiency of the proposed framework is assessed on the MAZANDARAN regional electric company (MREC) transmission network, integral to IRAN interconnected power system for both elastic and inelastic demands. Simulations show the significance of optimizing the firm contract and the capacity payment that encourages the generation investment for peak technology and improves long-term stability of electricity markets.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electric Power System Optimization · Smart Grid Energy Management · Optimal Power Flow Distribution
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Bradley Department of Electrical and Computer Engineering, Virginia Tech, NVC, Falls Church, VA 24043, USA
Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol 47148-71167, Mazandaran, Iran
Department of Physics and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University Newcastle, Newcastle upon Tyne NE1 8ST, UK
Department of Electrical Engineering, Lahijan Branch, Islamic Azad University, Lahijan 4416939515, Iran
Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
C-MAST, University of Beira Interior, 6201-001 Covilhã, Portugal
INESC-ID, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
INESC TEC and the Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
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