Transmission Expansion and Electricity Trade: A Case Study of the Greek Power System

The integration of European electricity markets, through the market coupling process, can create significant efficiency gains in terms of social welfare to European consumers and industries. The market coupling process is anticipated to more efficiently utilize the generation and transmission activities, reducing the requirements of large idle generation capacity. This paper uses an optimization-based methodological framework to address the problem of the optimal planning of a power system at an annual level in competitive and volatile power markets, under dynamic formulation of the strategy employed by all market participants. The model is used for the scenario-based transmission expansion of the Greek power system with neighboring power systems in Southeast Europe, identifying its impact on a series of operational and economic aspects. The model determines the optimal power generation mix in each scenario, the electricity trade with the neighboring countries, the evolution of the system marginal price and the resulting environmental impact. This enables the identification of the remuneration of all types of producers from the wholesale market through a detailed calculation of all the relevant cost components. The proposed approach can provide useful insights on the optimal portfolio determination by potential investors at a national and/or regional level, highlighting potential risks and appropriate price signals on critical infrastructure projects under real electricity market operating conditions. Keywords: CO2 emissions; Electricity trade; Power market dynamics; Power generation mix; Transmission expansion JEL Classifications: Q43, Q4

Price Signal of Tradable Guarantees of Origin for Hedging Risk of Renewable Energy Sources Investments

The risk of renewable energy sources (RES) investments in several European Union (EU) countries is offset by site-specific compensation, resulted by competitive auctions according the EU state aid guidelines for energy for the period 2014-2020. However, this scheme of incentivizing RES will probably be replaced, inheriting risk for RES investments. A potential market-based scheme could be the introduction of tradable guarantees of origin (GOs). This paper uses an integrated model, integrating the optimal power systems expansion planning problem with the unit commitment problem, which performs the simulation of the day-ahead electricity market. The model is used for the expansion of the Greek power system, identifying the RES capacity mix per technology type. The model estimates the new RES capacity, the evolution of the day-ahead price and the levelized cost of avoided energy. This enables the identification of the remuneration of RES producers from the wholesale market and the premium required for covering their levelized cost of electricity. The estimation of this premium provides insights on the price signals of tradable GOs, which could offset the risk of RES investments. The paper finally discusses the GOs' status and challenges, towards becoming the preferred policy for RES promotion. Keywords: Renewable Energy Sources, Guarantees of Origin, Risk, Power System Expansion Planning, Feed-in-Tariff, State Aid Guidelines JEL Classifications: Q4, Q4

Strategic Energy Planning under Uncertainty: a Mixed-Integer Linear Programming Modeling Framework for Large-Scale Energy Systems

Various countries and communities are defining strategic energy plans driven by concerns related to climate change and security of energy supply. Energy models are needed to support this decision-making process. The long time horizon inherent to strategic energy planning requires uncertainty to be accounted for. Most energy models available today are too complex or computationally expensive for uncertainty analyses to be carried out. This study proposes a concise multi-period Mixed-Integer Linear Programming (MILP) formulation for strategic energy planning under uncertainty. The modeling framework allows optimizing the energy system in a snapshot future year having as objective the total annual cost and assessing as well the global CO2-equivalent emissions. Key features of the model are a clear distinction both between demand and supply and between resources and technologies, a low computational time and a multiperiod resolution to account for issues related to seasonality and energy storage. The model is applied to a real case study and a Global Sensitivity Analysis (GSA) highlights the impact of uncertain parameters in energy planning

Generation expansion planning optimisation with renewable energy integration: A review

Generation expansion planning consists of finding the optimal long-term plan for the construction of new generation capacity subject to various economic and technical constraints. It usually involves solving a large-scale, non-linear discrete and dynamic optimisation problem in a highly constrained and uncertain environment. Traditional approaches to capacity planning have focused on achieving a least-cost plan. During the last two decades however, new paradigms for expansion planning have emerged that are driven by environmental and political factors. This has resulted in the formulation of multi-criteria approaches that enable power system planners to simultaneously consider multiple and conflicting objectives in the decision-making process. More recently, the increasing integration of intermittent renewable energy sources in the grid to sustain power system decarbonisation and energy security has introduced new challenges. Such a transition spawns new dynamics pertaining to the variability and uncertainty of these generation resources in determining the best mix. In addition to ensuring adequacy of generation capacity, it is essential to consider the operational characteristics of the generation sources in the planning process. In this paper, we first review the evolution of generation expansion planning techniques in the face of more stringent environmental policies and growing uncertainty. More importantly, we highlight the emerging challenges presented by the intermittent nature of some renewable energy sources. In particular, we discuss the power supply adequacy and operational flexibility issues introduced by variable renewable sources as well as the attempts made to address them. Finally, we identify important future research directions

Computational techniques for the optimal utilization of energy resources

Long-term energy planning constitutes an integral part of the overall energy policy, the fundamental objectives of which concern security of energy supply, environmental protection, regional development, and increased productivity and competitiveness, with the ultimate aim of reducing energy cost. At the international level, there is another set of factors exerting influence, including demographic change, global economic growth, increasing demand for energy, climate change, environmental pollution and ever-shrinking energy resources. As a consequence, the formulation of a systematic methodological framework for the analysis and design implementation of energy policies is of top priority for the international community.Furthermore, the implementation of long-term energy planning involves a significant degree of complexity due to the diversification of energy supply and the existence of multiple available power technologies, the volatility and uncertainty of the defining parameters of the system, the environmental impact, social responses and financial considerations (e.g., credit risk).The goal of long-term energy planning is to provide a road-map towards an affordable, sustainable and secure energy future by minimizing the total cost of development and operation of the energy system. The objective of this thesis is by using methods of mathematical programming, and particularly mixed-integer linear programming techniques, to contribute towards the development of mathematical models for the optimal development and evolution of energy systems by taking into account technical, economic, environmental and regulatory constraints. Emphasis is placed on the power system which constitutes the most critical energy system, accounting for the production, transmission and distribution of electricity. The proposed computer-aided frameworks can be utilized to simulate conditions of uncertainty of several system parameters, covering an extensive time scale, from an hourly level to several years, and can also be extended to decentralized energy networks covering the entire spectrum of the energy supply chain.O μακροχρόνιος ενεργειακός σχεδιασμός αποτελεί αναπόσπαστο κομμάτι της συνολικής ενεργειακής πολιτικής, θεμελιώδεις στόχοι της οποίας είναι η ασφάλεια του ενεργειακού εφοδιασμού, η περιβαλλοντική προστασία, η περιφερειακή ανάπτυξη, καθώς και η αύξηση της παραγωγικότητας και της ανταγωνιστικότητας, με τελικό στόχο την μείωση του ενεργειακού κόστους. Σε διεθνές επίπεδο επιδρά και μια άλλη σειρά παραγόντων στους οποίους συμπεριλαμβάνονται η δημογραφική εξέλιξη, η παγκόσμια οικονομική ανάπτυξη, η αυξανόμενη ενεργειακή ζήτηση, η κλιματική αλλαγή, η περιβαλλοντική μόλυνση και οι ολοένα και συρρικνούμενοι ενεργειακοί πόροι. Ως συνέπεια των παραπάνω, δημιουργείται η ανάγκη για ένα συστηματικό πλαίσιο ανάλυσης και σχεδιασμού υλοποίησης ενεργειακών πολιτικών.Επιπλέον, η υλοποίηση του μακροχρόνιου ενεργειακού σχεδιασμού εμπεριέχει σημαντικό βαθμό πολυπλοκότητας εξαιτίας της διαφοροποίησης των πηγών προμήθειας και της ύπαρξης πολλαπλών διαθέσιμων τεχνολογιών ηλεκτροπαραγωγής, της μεταβλητότητας και της αστάθειας των προσδιοριστικών παραμέτρων του ενεργειακού συστήματος, του περιβαλλοντικού αντίκτυπου, των κοινωνικών αντιδράσεων και της εξεύρεσης ή μη χρηματοδοτικών πόρων. Ο στόχος του μακροχρόνιου ενεργειακού σχεδιασμού αφορά την ασφαλή και ακριβή σχεδίαση ενός μακροπρόθεσμου οδικού χάρτη ανάπτυξης ενός ενεργειακού συστήματος μέσω της ελαχιστοποίησης του συνολικού κόστους ανάπτυξης και λειτουργίας του συστήματος. Η επιδίωξη της παρούσας διδακτορικής διατριβής είναι μέσω της εφαρμογής μεθόδων μαθηματικού προγραμματισμού και ειδικότερα τεχνικών μεικτού ακεραίου γραμμικού προγραμματισμού, να συνεισφέρει στην ανάπτυξη μαθηματικών υποδειγμάτων που λαμβάνοντας υπ’ όψιν τεχνικούς, οικονομικούς, περιβαλλοντικούς και ρυθμιστικούς περιορισμούς να παρέχουν τα βέλτιστα αποτελέσματα σε ότι αφορά την βέλτιστη εξέλιξη και πορεία των ενεργειακών συστημάτων. Η παρούσα διατριβή εστιάζει σε ένα από τα πλέον κρίσιμα ενεργειακά συστήματα, ήτοι το ηλεκτρικό σύστημα, το οποίο αποτελεί σημαντικό τμήμα της συνολικής ενεργειακής δραστηριότητας για κάθε οικονομία, αντιπροσωπεύοντας τις διαδικασίες παραγωγής, μεταφοράς και διανομής ηλεκτρικής ενέργειας. Οι αναπτυχθείσες υπολογιστικές προσεγγίσεις δύναται να χρησιμοποιηθούν και υπό συνθήκες αβεβαιότητας κάποιων παραμέτρων του συστήματος, σε ευρεία χρονική κλίμακα, από ωριαίο επίπεδο έως και μιας σειράς ετών, ενώ μπορούν επίσης να επεκταθούν και σε αποκεντρωμένα ενεργειακά δίκτυα, καλύπτοντας έτσι ολόκληρο το φάσμα της ενεργειακής εφοδιαστικής αλυσίδας

A novel integrated profit maximization model for retailers under varied penetration levels of photovoltaic systems

In contemporary energy markets, the Retailer acts as the intermediate between the generation and demand sectors. The scope of the Retailer is to maximize its profits by selecting the appropriate procurement mechanism and selling price to the consumers. The wholesale market operation influences the profits since the mix of generation plants determines the system marginal price (SMP). In the related literature, the SMP is treated as a stochastic variable, and the wholesale market conditions are not taken into account. The present paper presents a novel methodology that aims at connecting the wholesale and retail market operations from a Retailer’s perspective. A wholesale market clearing problem is formulated and solved. The scope is to examine how different photovoltaics (PV) penetration levels in the generation side influences the profits of the Retailer and the selling prices to the consumers. The resulting SMPs are used as inputs in a retailer profit maximization problem. This approach allows the Retailer to minimize economic risks and maximize profits. The results indicate that different PV implementation levels on the generation side highly influences the profits and the selling prices. © 2020 by the authors. Licensee MDPI, Basel, Switzerland