Search

This report is part of the data documentation for the Global Gas Model (GGM) as prepared for analyses in the H2020 SET-Nav project1 and subsequent studies. Since some data are proprietary we cannot make available all input data we have used. By describing input data, the processing steps, and the resulting input files we aim for maximum transparency and to allow anyone to reproduce the data sets from scratch if desired. GGM was developed by Egging (2010, 2013), also based on expertise gained in the development and application of the European Gas Model (Egging et al., 2008) and the World Gas Model (Egging et al., 2010, 2009). GGM was applied with various data sets and versions in studies of the future global (Holz et al., 2015) and European gas markets (Holz et al., 2016, 2017). In addition to the impact of climate policy, supply security has been a recurring concern (e.g. Richter and Holz, 2015). Moreover, a stochastic version that used a scenario tree was applied in Egging and Holz (2016). In the SET-Nav project, GGM contributed to the analyses of projects of common interest (PCI), their profitability and public support requirements (Kotek et al., 2018). This is a deterministic model version (i.e. no probabilistic scenario tree).

The deployment of Renewable Energy Resources (RES) is affecting the profitability and scheduling of conventional generators (e.g. gas-fired power plants) as well as creating short-term electricity balancing problems. To manage RES variable output, additional flexible power capacity will be needed to cope with peak demand. Gas power plants ability to provide flexibility in a short time period make them especially suitable for fast balancing. Could gas power plants compensate RES fluctuations without creating instability in the gas transmission network? How investments on the gas infrastructure affects the evolution of the electricity sector and vice-versa? To answer these questions and jointly represent electricity-gas energy sectors, this paper presents 1) a methodology on combining cost based optimization models for gas and electricity and 2) the effects of long-term policy targets set to the EU electricity sector and its influence on the gas infrastructure. To address long-term (strategic investments) and short-term (operational) aspects, we model both sectors as multi-horizon stochastic programs. Models results illustrate a strong dependency of the electricity infrastructure on the short-term operations of the gas sector. Under a high RES deployment scenario, gas infrastructure investments declines slightly which increases cross-border electricity capacity needs.

Stochastic optimization approaches ignore that the decisions of different actors in markets typically do not lead to a system-wide optimal solution. Suppliers in markets with entrance barriers or other aspects that hinder competition, can use their dominant positions to exert market power and drive up market prices. To represent such gaming behavior, a different modeling approach is needed. Equilibrium models can represent varying market structures, including perfect competition and oligopoly. This chapter presents a multi-stage stochastic equilibrium model for a general commodity market wherein suppliers, transportation agents and storage agents make capacity investment decisions while facing uncertainty in future market circumstances and production and sales decisions in later stages when the uncertainty has been revealed. An illustrative example for the natural gas market is used to show how market power may affect decisions and expected profits, and discuss the value of the stochastic solution for the different agents in our gaming setting. This is an Accepted Manuscript of a book chapter published by Nova Science Publishers, Inc.in [Stochastic Programming: Theory, Applications and Impacts]

Recent supply security concerns in Europe have revived interest into the natural gas market. Here, we investigate investment behavior and trade in an imperfect market structure under uncertainty in both supply and demand. We focus on three uncertain events: i) transit of Russian gas via Ukraine that may be disrupted from 2020 on; ii) natural gas intensity of electricity generation in OECD countries that may lead to higher or lower natural gas demand after 2025; and iii) availability of shale gas around the globe after 2030. We illustrate how timing of investments is affected by inter-temporal hedging behavior of market agents, such as when LNG capacity provides ex-ante flexibility (e.g., in Ukraine to hedge for a possible Russian supply disruption) or an expost fallback option if domestic or nearby pipeline supply sources are low (e.g., uncertain shale gas resources in China). Moreover, we find that investment in LNG capacities is more determined by demand side pull (due to higher needs in electric power generation) than by supply side push (higher shale gas supplies needing an outlet).

In this paper, we use the Global Gas Model to analyze the perspectives and infrastructure needs of the European natural gas market until 2050. Three pathways of natural gas consumption in a future low-carbon energy system in Europe are envisaged: i) a decreasing natural gas consumption, along the results of the PRIMES model for the EMF decarbonization scenarios; ii) a moderate increase of natural gas consumption, along the lines of the IEA (2012) World Energy Outlook's New Policy Scenario; and iii) a temporary increase of natural gas use as a bridge technology, followed by a strong decrease after 2030. Our results show that import infrastructure and intra-European transit capacity currently in place or under construction are largely sufficient to accommodate the import needs of the EMF decarbonization scenarios, despite the reduction of domestic production and the increase of import dependency. However, due to strong demand in Asia which draws LNG and imports from Russia, Europe has to increasingly rely on pipeline exports from Africa and the Caspian region from where new pipelines are built. Moreover, pipeline investments open up new import and transit paths, including reverse flow capacity, which improves the diversification of supplies. In the high gas consumption scenario similar pipeline links are realized-though on a larger scale, doubling the costs of infrastructure expansion. In the bridge technology scenario, the utilization rates of (idle) LNG import capacity can be increased for the short period of temporary strong natural gas demand.

When using material from this publication, Statistics Norway shall be quoted as the source. Abstracts with downloadable Discussion Papers in PDF are available on the Internet: http://www.ssb.no. Natural gas is increasingly important as a fuel for electric power generation as well as other uses due to its environmental advantage over other fossil fuels. Using the World Gas Model, a large-scale energy equilibrium system based on a complementarity formulation, this paper analyzes possible future gas cartels and their effects on gas markets in a number of regions across the world. In addition, scenarios related to lower transport costs and decreased unconventional gas supply in the United States are considered Funding from the Petrosam program of the Research Council of Norway (project #184739).

In this paper, we discuss potential developments of the world natural gas industry at the horizon of 2030. We use the World Gas Model (WGM), a dynamic, strategic representation of world natural gas production, trade, and consumption between 2005 and 2030. We specify a base case which defines the business-as-usual assumptions based on forecasts of the world energy markets. We then analyze the sensitivity of the world natural gas system with scenarios: i) the emergence of large volumes of unconventional North American natural gas reserves, such as shale gas; ii) on the contrary, tightly constrained reserves of conventional natural gas reserves in the world; and iii) the impact of CO2-constraints and the emergence of a competing environmental friendly backstop technology. Regional scenarios that have a global impact are: iv) the full halt of Russian and Caspian natural gas exports to Western Europe; v) sharply constrained production and export activities in the Arab Gulf; vi) heavily increasing demand for natural gas in China and India; and finally vii) constraints on liquefied natural gas (LNG) infrastructure development on the US Pacific Coast. Our results show considerable changes in production, consumption, traded volumes, and prices between the scenarios. Investments in pipelines, LNG terminals and storage are also affected. However, overall the world natural gas industry is resilient to local disturbances and can compensate local supply disruptions with natural gas from other sources. Long-term supply security does not seem to be at risk.

We provide the description and illustrative results of the World Gas Model, a multi-period complementarity model for the global natural gas market. Market players include producers, traders, pipeline and storage operators, LNG liquefiers and regasifiers as well as marketers. The model data set contains more than 80 countries and regions and covers 98% of world wide natural gas production and consumption. We also include a detailed representation of cross-border natural gas pipelines and constraints imposed by long-term contracts in the LNG market. The Base Case results of our numerical simulations show that the rush for LNG observed in the past years will not be sustained throughout 2030 and that Europe will continue to rely on pipeline gas for a large share of its imports and consumption.

This paper presents results of simulating a more collusive behavior of a group of natural gas producing and exporting countries, sometimes called GASPEC. We use the World Gas Model, a dynamic, strategic representation of world gas production, trade, and consumption between 2005 and 2030. In particular, we simulate a closer cooperation of the GASPEC countries when exporting pipeline gas and liquefied natural gas; we also run a more drastic scenario where GASPEC countries deliberately withhold production. The results shows that compared to a Base Case, a gas cartel would reduce total supplied quantities and induce price increases in gas importing countries up to 22%. There is evidence that the natural gas markets in Europe and North America would be affected more than other parts of the world. Lastly, the vulnerability of gas importers worldwide on gas exporting countries supplies is further illustrated by the results of a sensitivity case in which price levels are up to 87% higher in Europe and North America, but non-GEC countries increase production by a mere 10%.

In this paper, we present a detailed and comprehensive complementarity model for computing market equilibrium values in the European natural gas system. Market players include producers and their marketing arms which we call transmitters, pipeline and storage operators, marketers, LNG liquefiers, regasifiers, tankers, and three end-use consumption sectors. The economic behavior of producers, transmitters, pipeline and storage operators, liquefiers and regasifiers is modeled via optimization problems whose Karush-Kuhn-Tucker (KKT) optimality conditions in combination with market-clearing conditions form the complementarity system. The LNG tankers, marketers and consumption sectors are modeled implicitly via appropriate cost functions, aggregate demand curves, and ex-post calculations, respectively. The model is run on several case studies that highlight its capabilities, including a simulation of a disruption of Russian supplies via Ukraine.

The EU has high ambitions for its clean energy transition. Reducing yearly CO2emissions by 80% until 2050 requires large-scale implementation of renewable energy technologies and likely a large-scale electrification of non-energy sectors such as transportation. A major challenge imposed by renewable energy supply is the uncontrollable and intermittent nature of generation. Large flexibility volumes and capacities are needed to manage an energy system with high shares of renewables. Norway, with a large hydropower base and flexibility potential in its offshore natural gas transmission grid, can support the EU clean energy transition by providing much needed flexibility and controllability. This will require expansion of hydropower production and transmission capacity as well as altered management of gas export pipelines. To make these flexibility options available, market participants must be incentivized by new market designs and instruments that place higher value on flexibility and controllability.

The deployment of Renewable Energy Resources (RES) is affecting the profitability and scheduling of conventional generators (e.g. gas-fired power plants) as well as creating short-term electricity balancing problems. To manage RES variable output, additional flexible power capacity will be needed to cope with peak demand. Gas power plants ability to provide flexibility in a short time period make them especially suitable for fast balancing. Could gas power plants compensate RES fluctuations without creating instability in the gas transmission network? How investments on the gas infrastructure affects the evolution of the electricity sector and vice-versa? To answer these questions and jointly represent electricity-gas energy sectors, this paper presents 1) a methodology on combining cost based optimization models for gas and electricity and 2) the effects of long-term policy targets set to the EU electricity sector and its influence on the gas infrastructure. To address long-term (strategic investments) and short-term (operational) aspects, we model both sectors as multi-horizon stochastic programs. Models results illustrate a strong dependency of the electricity infrastructure on the short-term operations of the gas sector. Under a high RES deployment scenario, gas infrastructure investments declines slightly which increases cross-border electricity capacity needs.