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Substantial R &D efforts are currently directed towards the development of combined heat and power (CHP) systems that automatically and seamlessly connect to the power grid. In this paper we develop a real options model to assess the impact that the operational flexibility characterizing such systems will have on the optimal timing and capacity associated with investments in CHP plants. We take the viewpoint of a manufacturer operating in an energy-intensive industry who contemplates investing in CHP. We discuss and compare investments in two types of CHP systems: a standard one that is operationally rigid and a technologically advanced one that is operationally flexible. The interaction between temporal and operational flexibility under uncertainty and irreversibility is central to our analysis. We show that operational flexibility guarantees earlier investment but has an ambiguous effect in terms of capacity. In particular, when operational flexibility is very valuable the potential investor is opting for investing in a plant with larger productive capacity. The potential investor chooses a smaller CHP unit if otherwise. A numerical exercise calibrated using data from the Italian pulp and paper and electricity industries complements our theoretical analysis. [ABSTRACT FROM AUTHOR]

The online version of the original article can be found at https://doi.org/10.1007/s10479-023-05273-xCorrection to: Annals of Operations Researchhttps://doi.org/10.1007/s10479-023-05273-xThis correction is published as the text published under Statements and Declaration section was mismatched due to proofing error.Original article has been corrected.Publisher's NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.By Dimitrios Zormpas and Giorgia OggioniReported by Author; Author [Extracted from the article]

• We analyse the reserve procurement in a renewable-dominated power system. • We focus on when reserves are scheduled and compare three market designs. • A full co-optimization of energy and reserve (Model 3) is the most efficient system. • Reserve scheduled after the clearing of the energy market can be as efficient as Model 3. • Reserve scheduled before the clearing of the energy market is the least efficient system. This paper investigates different reserve issues inspired by the European situation, focusing on both the moment when reserves are procured and the degree of coordination among Transmission System Operators (TSOs) in that procurement. We present three scheduling models formulated as stochastic programs that represent the day-ahead energy market, the reserve procurement, and the real-time balancing market in a renewable-dominated power system. Two of the proposed models are inspired by reserve procurement mechanisms currently applied in Europe, where reserves are committed either before (Model 1) or after (Model 2) the clearing of the day-ahead energy market. Then, we use as benchmark a third model in which energy and reserve capacity are co-optimized (Model 3). In all models, we consider the procurement of both conventional and upward/downward reserves. We also assess the impact of these organizations on market participants' remuneration and test the impact of cross-border constraints as those applying in the European power system. The case study is based on the IEEE 24-node RTS, considering the uncertainty in renewable power production and demand. Our results show that Model 1 is the least efficient market design as it leads to a misallocation of the available capacity, while Model 2 becomes as efficient as Model 3 when the TSOs procure reserve in a coordinated way. Finally, a coordinated procurement of reserves reduces the system operating costs in all models. [ABSTRACT FROM AUTHOR]

The European-Union Emissions Trading System (EU-ETS) is a cap and trade scheme that requires the industries participating in the program to obtain allowances to cover their carbon emissions. Energy Intensive Industries claim that this system puts their European plants at an economics disadvantage compared to facilities located outside the EU. As a direct consequence, industries may relocate their production activities in unregulated countries, leading to the so-called carbon leakage effect. In order to curb this effect, several policies have been devised, including grandfathering of CO 2 allowances and border tax adjustment. This paper investigates the impact of these two policies on the cement sector, with a particular focus on the Italian market, particularly prone to carbon leakage. The analysis is based on an oligopolistic partial equilibrium model with a detailed technological representation of the market. The model is a Generalized Nash Equilibrium Problem that accounts for the interactions of cement companies. Simulations show that neither the grandfathering nor the border tax adjustment fully solve the carbon leakage problem because cement companies modify their cement and clinker trade strategies according to the measure applied in order to avoid or reduce their carbon costs. [ABSTRACT FROM AUTHOR]

Cross-border trade remains a contentious issue in the restructuring of the European electricity market. This paper analyzes the cross-border trade problem through a set of models that represent different degrees of coordination both between the energy and the transmission markets and among national Transmission System Operators (TSOs). We first present a nodal price-like organization of the system, where Power Exchanges (PXs) and Transmission System Operators are integrated to operate the energy and transmission markets. This system is not implemented in Europe but its success elsewhere makes it the natural reference for the study. We then move to a more realistic representation of the European electricity market based on the so-called market coupling design where energy and transmission are operated separately by PXs and TSOs. We consider different degrees of coordination of the national TSOs' activities to assess the range of inefficiencies that the lack of integration can lead to. The paper supposes price taking agents and hence leaves aside the incentive to game the system induced by zonal systems. [ABSTRACT FROM AUTHOR]

• An adaptive robust optimization model for a distribution system is proposed. • Capacity expansion decisions comprise charging stations, solar and storage units. • Short-term variability and long-term uncertainty are considered. • Sensitivity analyses are conducted to evaluate changes in investment decisions. The decarbonization of energy systems passes through the transition towards low- and zero-emission vehicles and the investments in efficient technologies. To this end, an adaptive robust optimization approach is proposed for the expansion planning problem of a distribution system where expansion decisions involve the construction of renewable generating units, storage units, and charging stations for electric vehicles. The problem is formulated under the perspective of a central planner that aims at determining the expansion plan that minimizes both investment and operation costs. Both short-term variability and long-term uncertainty are considered in the proposed approach and are modeled in different ways. Short-term variability of the demand, the production of stochastic units, and the price of electricity withdrawn from or injected into the transmission system is modeled using a number of representative days corresponding to different operating conditions. Long-term uncertainty in the future peak demands, the future value of electricity exchanged with the transmission grid, and the number of electric vehicles is instead modeled through confidence bounds. A case study based on a 69-node distribution network shows the effectiveness of the proposed technique and the relationship between the optimal expansions decisions, the revenues from selling electricity to the electric vehicles, the degree of independence from the transmission system, and the role played by the investment budget availability. Moreover, an ex-post decarbonization analysis is conducted to evaluate the environmental impact of the adoption of electric vehicles. Finally, the proposed approach outperforms the results of a stochastic model in terms of computational performance. [ABSTRACT FROM AUTHOR]

We propose a spatial equilibrium problem for a pulp and paper supply chain network under the Emission Trading System (ETS) and the circular economy principles. The developed closed-loop supply chain model, based on the variational inequality theory, accounts for the forest deployment and the production of paper using both virgin pulp and recyclable paper waste in an area that is subject to the ETS. In addition, it considers the exchanges of virgin pulp, paper, recyclable and not-recyclable paper waste between this regulated area and geographical zones where no environmental policies apply. The aim of this paper is to investigate the ETS impacts on the pulp and paper industries located in an environmentally regulated area in terms of operating costs, production and trading volumes of the aforementioned commodities, and emissions generated. The case study focuses on the European pulp and paper companies, which are among the energy-intensive industries deemed to be exposed to the carbon leakage risk as a consequence of the ETS application. Sensitivity analyses on the carbon price value and on the trade flexibility are conducted. Our results show that the ETS implies additional costs for the European pulp and paper companies and induces them to resort more on imports of virgin pulp and paper from not-regulated zones. [ABSTRACT FROM AUTHOR]