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The shale gas developments over the last two decades have challenged the gas price linkage with crude oil. The decoupling of the US wholesale gas from oil markets is mainly attributed to the rapid development of unconventional production, which formed a regional natural gas market based on regional market fundamentals. Moreover, investments in exporting facilities in the US made more quantities available to the rest of the world making global integration more plausible. This paper provides empirical evidence on the price and volatility transmission among the main European (NBP and TTF) and the Japan-Korean Marker (JKM) gas markets with that of Brent crude oil market, a crude oil benchmark used in Europe and Asia. The paper provides evidence that there are no price spillovers among oil and gas in European gas hubs. The European markets, contrary to the JKM market, seem to be mature enough as in the case of the US gas market. Finally, the paper provides policy recommendations on key elements for establishing functional gas hubs.Keywords: natural gas and oil markets; price and volatility spillovers; Europe, JapanJEL Classifications: Q40, Q41, C5DOI: https://doi.org/10.32479/ijeep.9774

Developing economies are in process of liberalizing their electricity markets, following similar process in developed economics. This process aims at establishing liquid energy exchanges that provide clear price signals, providing indications on the profitability of different operations: production, retail, trading in interconnections. This paper aims at developing a unit commitment model for examining zonal market pricing in Kazakhstan. The latter has an extensive landscape but sparsely populated, while is also characterized by the high availability of domestic fossil fuels, but located in different sub-regions of the country. The provision of zonal price signals in such a power system in invaluable, as it enables the provision of clear price signals on the needed infrastructure and the estimation of the zonal hourly energy and technology mix. Moreover, in enables the formation of dynamic bidding strategies by market participants in cases with favourable conditions, such as the implementation of scarcity pricing. This paper presents a unit commitment model that used to assess different bidding strategies and to provide zonal price signals. The strategies are formed, depending on the technology type and fuel prices comparison. Results provide clear signals on needed infrastructure among zones in Kazakhstan. It also shows that dynamic biding can lead to market coupling. Finally, it indicates the importance of institutional capability to monitor bidding strategies, eliminating speculation.

Developing economies are in process of liberalizing their electricity markets, following similar process in developed economics. This process aims at establishing liquid energy exchanges that provide clear price signals, providing indications on the profitability of different operations: production, retail, trading in interconnections. This paper aims at developing a unit commitment model for examining zonal market pricing in Kazakhstan. The latter has an extensive landscape but sparsely populated, while is also characterized by the high availability of domestic fossil fuels, but located in different sub-regions of the country. The provision of zonal price signals in such a power system in invaluable, as it enables the provision of clear price signals on the needed infrastructure and the estimation of the zonal hourly energy and technology mix. Moreover, in enables the formation of dynamic bidding strategies by market participants in cases with favourable conditions, such as the implementation of scarcity pricing. This paper presents a unit commitment model that used to assess different bidding strategies and to provide zonal price signals. The strategies are formed, depending on the technology type and fuel prices comparison. Results provide clear signals on needed infrastructure among zones in Kazakhstan. It also shows that dynamic biding can lead to market coupling. Finally, it indicates the importance of institutional capability to monitor bidding strategies, eliminating speculation.Keywords: Electricity markets, unit commitment model, KazakhstanJEL Classifications: Q4, Q47, L94DOI: https://doi.org/10.32479/ijeep.9022

The integration of electric vehicles (EVs) in the power system is a challenging issue for the power system and network operators. The paper uses several Unit Commitments (UC) models which incorporate high levels of wind power production, applying different methods to tackle the renewables’ uncertainty. The selected power system is IEEE RTS 96. The UC models are further extended to integrate the EVs. Our focus is to assess the EVs impact on the total operating cost and the power grid adequacy to handle the extra load, by examining different charging profiles and penetration levels of EVs with the different UC models. Simulation results show that an optimized charging strategy is considerably more efficient than the random charging strategy, both in the total operating cost and the ability to integrate more EVs. The comparison between the UC models show that the most robust UC model leads to higher total operating cost, due to its more conservative methodology to tackle the stochastic nature of wind. There exists a non-linear trade-off between power system robustness and the total operating cost, depending on each power system characteristics, affecting also the penetration level of EVs.Keywords: Electric Vehicles, Unit Commitment, Renewables, Uncertainty, Power System, IEEE RTS 96JEL Classifications: Q47, L94DOI: https://doi.org/10.32479/ijeep.7125

There is lot of discussion on the level of the oil dependence of the Russian economy, as well as on whether the Russian Federation presents signs of the Dutch disease or even if already suffers by it. In this paper, we develop econometric models for examining the oil dependence of the Russian economy. We construct two VARs and then we proceed with VECMs models. The models consider macroeconomic factors, such as industrial production index, unemployment, GDP and government expenditure, as well as oil factors, such crude oil price and Russian oil production. We employ impulse response functions to catch the interactions among variables. We find strong evidence on the oil dependence of the Russian economy; however, we do not find firm established proof of the Dutch disease.Keywords: Russia, oil, cointegrationJEL Classifications: Q43, C01, P48