An integrated stochastic multi-regional long-term energy planning model incorporating autonomous power systems and demand response

Nikolaos E. Koltsaklis, Pei Liu and Michael C. Georgiadis

Energy, 2015, vol. 82, issue C, 865-888

Abstract: The power sector faces a rapid transformation worldwide from a dominant fossil-fueled towards a low carbon electricity generation mix. Renewable energy technologies (RES) are steadily becoming a greater part of the global energy mix, in particular in regions that have put in place policies and measures to promote their utilization. This paper presents an optimization-based approach to address the generation expansion planning (GEP) problem of a large-scale, central power system in a highly uncertain and volatile electricity industry environment. A multi-regional, multi-period linear mixed-integer linear programming (MILP) model is presented, combining optimization techniques with a Monte Carlo (MCA) method and demand response concepts. The optimization goal concerns the minimization of the total discounted cost by determining optimal power capacity additions per time interval and region, and the power generation mix per technology and time period. The model is evaluated on the Greek power system (GPS), taking also into consideration the scheduled interconnection of the mainland power system with those of selected autonomous islands (Cyclades and Crete), and aims at providing full insight into the composition of the long-term energy roadmap at a national level.

Keywords: Generation expansion planning; Power sector; Monte Carlo; Demand response; Islands' interconnection; CO2 emissions (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (37)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:82:y:2015:i:c:p:865-888

DOI: 10.1016/j.energy.2015.01.097

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