Generation expansion planning within the context of electricity markets

Generation expansion planning within the context of electricity markets | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Generation expansion planning within the context of electricity markets Nikolaos E. Koltsaklis, Jaroslav Knápek This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3939871/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Generation expansion planning is defined as the problem determining the optimal type of energy technologies to be installed, time, and construction location. This problem becomes even more complicated within the context of electricity markets since market conditions have to be taken into consideration, including their volatilities and shocks. This work addresses the problem of optimal generation expansion planning, taking into account the market operation through the introduction of unit commitment constraints. In addition, it considers the penetration of distributed energy resources into the system, including energy storage systems and demand response programs. The overall methodological framework is based on mixed-integer programming techniques and has been tested in an illustrative power system under various assumptions regarding CO 2 emissions limits as well as CO 2 and natural gas fuel prices. The results highlight that renewable power units are installed in all cases, while non-renewable power units are installed only if they are low-carbon (biomass and nuclear) or they are equipped with a CCS technology (hard coal and natural gas). In addition, there is a positive correlation with the installation of energy storage systems; namely, the more the capacity of the installed RES units, the more the capacity of the installed energy storage systems. The increase in the price of natural gas fuel is able to lead to power mixes with higher CO 2 intensity, if it is combined with a low CO2 emissions price. Energy storage systems, accompanied by demand response programs to some extent, play a decisive role in both energy and reserves balance in the zero-emissions power mix. System operators, regulatory authorities, and potential investors can utilize the developed optimization framework to quantify the roadmap and the long-term dynamics of the studied power system to optimize the investment strategy of their resources and portfolios. Optimization Mixed-integer linear programming Generation expansion planning Unit commitment Energy storage Demand response. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 27 May, 2024 Reviews received at journal 08 May, 2024 Reviewers agreed at journal 11 Apr, 2024 Reviews received at journal 23 Feb, 2024 Reviewers agreed at journal 16 Feb, 2024 Reviewers invited by journal 13 Feb, 2024 Editor assigned by journal 13 Feb, 2024 Submission checks completed at journal 13 Feb, 2024 First submitted to journal 08 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3939871","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":272647949,"identity":"e2d81905-6dfc-487b-8203-af8a0f5e101a","order_by":0,"name":"Nikolaos E. 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This problem becomes even more complicated within the context of electricity markets since market conditions have to be taken into consideration, including their volatilities and shocks. This work addresses the problem of optimal generation expansion planning, taking into account the market operation through the introduction of unit commitment constraints. In addition, it considers the penetration of distributed energy resources into the system, including energy storage systems and demand response programs.\u003c/p\u003e \u003cp\u003eThe overall methodological framework is based on mixed-integer programming techniques and has been tested in an illustrative power system under various assumptions regarding CO\u003csub\u003e2\u003c/sub\u003e emissions limits as well as CO\u003csub\u003e2\u003c/sub\u003e and natural gas fuel prices. The results highlight that renewable power units are installed in all cases, while non-renewable power units are installed only if they are low-carbon (biomass and nuclear) or they are equipped with a CCS technology (hard coal and natural gas). In addition, there is a positive correlation with the installation of energy storage systems; namely, the more the capacity of the installed RES units, the more the capacity of the installed energy storage systems. The increase in the price of natural gas fuel is able to lead to power mixes with higher CO\u003csub\u003e2\u003c/sub\u003e intensity, if it is combined with a low CO2 emissions price. 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