Search Results (22)

This study investigates the spatial and economic differentiation of organic farming across the European Union by analyzing regional specialization patterns using Location Quotients (LQ). The results reveal a highly heterogeneous landscape shaped by the interaction of agro-ecological conditions, production traditions, market development, and structural characteristics of national agricultural systems. Six distinct regional models of organic farming are identified: the Nordic–Baltic cereal–forage model, the Alpine–Central European grassland model, the Mediterranean permanent-crop model, the Central–Eastern European raw-material model, the Western European intensive horticultural model, and the island-based niche-specialization model. Regression analyses show that overall organic specialization is strongly associated with market development, whereas the structure of organic crop production is primarily determined by agro-ecological and structural factors rather than consumer demand or purchasing power. These findings highlight the strong embeddedness of organic farming within long-term regional development pathways and underscore the need for regionally differentiated policy instruments within the Common Agricultural Policy. Effective support measures should be tailored to dominant crop types, production systems, and comparative advantages across Member States. Full article

The recent updates to the Single Day-Ahead Coupling (SDAC) framework in the European energy market, along with new rules for providing manual frequency restoration reserve (mFRR) products in the Nordic Energy Activation Market (EAM), have introduced a finer Market Time Unit (MTU) resolution. These developments underscore the growing importance of flexible assets, such as power-to-hydrogen (PtH) facilities, in delivering system flexibility. However, to successfully participate in such markets, well-designed and accurate bidding strategies are essential. To fulfill this aim, this paper proposes a Mixed Integer Linear Programming (MILP) model to determine the optimal bidding strategies for a typical PtH facility, accounting for both the technical characteristics of the involved technologies and the specific participation requirements of the mFRR EAM. The study also explores the economic viability of sourcing electricity from nearby wind turbines (WTs) under a Power Purchase Agreement (PPA). The simulation is conducted using a case study of a planned PtH facility at the Port of Hirtshals, Denmark. Results demonstrate that participation in the mFRR EAM, particularly through the provision of downward regulation, can yield significant economic benefits. Moreover, involvement in the mFRR market reduces power intake from the nearby WTs, as capacity must be reserved for downward services. Finally, the findings highlight the necessity of clearly defined business models for such facilities, considering both technical and economic aspects. Full article

This paper studies the volatility of electricity spot prices in the Nordic market (Sweden, Finland, Denmark, and Norway) under regime switching. Utilizing Markov-switching GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, we provide strong evidence of nonlinear regime shifts in the volatility dynamics of these prices. Using in-sample criteria, we find that regime-switching models have lower AIC (Akaike information criterion) than single-regime GARCH models. In addition, out-of-sample forecasts indicate that regime-switching GARCH models have superior Value-at-Risk (VaR) prediction ability relative to single-regime models, which is directly pertinent to risk management. These findings highlight the importance of incorporating regime shifts into volatility models for accurately assessing and mitigating risks associated with electricity price fluctuations in deregulated markets. Full article

This paper presents PLEXOS modelling of the Nordic and Baltic low-carbon electricity market until 2030, using a total of 35 different weather years’ (1982–2016) ERAA profiles as inputs for the modelling and focusing on the occurrence of severe electricity scarcity situations in Finland, analyzing their duration and depth. The expected development of generation and demand is modelled based on available authoritative sources, such as ENTSO-E TYNDP and national projections. The present amount of nuclear power in Finland and growing amounts of wind and solar generation across the Nordic electricity system are modelled. This study analyzes scarcity situations by calculating residual loads and the expected electricity spot market prices assuming the different weather years with the generation fleet and demand in 2024 and 2030 scenarios. This study finds that, despite the very significantly growing amount of variable renewable generation (42.5 TWh/a increase in wind generation from 2024 to 2030 in Finland only), the frequency and severity of scarcity situations will increase from 2024 to 2030. The main reasons are the retirement of Combined Heat and Power plants and the transition to more electrified district heating in Finland and the expected demand growth. The findings indicate that without further measures Finland is not sufficiently prepared for cold winter periods with high heating and electricity demand and events of serious scarcity can occur. Full article

The global development and enhancement of electricity financial markets aim to mitigate price risk in the electricity spot market. Power producers utilize financial derivatives for both hedging and speculation, necessitating careful selection of portfolio strategies. Current research on investment strategies for power financial derivatives primarily emphasizes risk management, resulting in a lack of a comprehensive investment framework. This study analyzes six short-term electricity futures contracts: base day, base week, base weekend, peak day, peak week, and peak weekend. A multi-agent deep reinforcement learning algorithm, Dual-Q MADDPG, is employed to learn from interactions with both the spot and futures market environments, considering the hedging and speculative behaviors of power producers. Upon completion of model training, the algorithm enables power producers to derive optimal portfolio strategies. Numerical experiments conducted in the Nordic electricity spot and futures markets indicate that the proposed Dual-Q MADDPG algorithm effectively reduces price risk in the spot market while generating substantial speculative returns. This study contributes to lowering barriers for power generators in the power finance market, thereby facilitating the widespread adoption of financial instruments, which enhances market liquidity and stability. Full article

China has made significant progress in developing renewable energy, but challenges in integrating variable sources like wind, solar, and hydro power persist. Existing research has a regional focus and lacks a comprehensive understanding of integration challenges in specific regions. Moreover, research concentrates on individual energy types rather than multiple sources. Addressing these challenges requires a deeper analysis of market rules, incentives, and mechanisms for integrating numerous renewable energy types. The existing research also overlooks crucial aspects like energy consumption, grid planning, and power market mechanisms. To promote renewable energy integration effectively, policymakers must address these interconnected factors through comprehensive investigations and research efforts. This study proposes tailored solutions to encourage integration in China based on international experiences, such as Brazil’s contract markets and electricity redistribution mechanism, the Nordic spot market, and California’s negative pricing mechanism. The strategies derived from global practices for China’s renewable energy integration include diverse trading mechanisms, expanded contract markets, optimized local consumption, fortified grid infrastructure, and improved market mechanisms. Full article

In this empirical study, multifactor stochastic volatility models for the financial Nordic/Baltic power markets are developed, implemented, and analyzed. Stochastic volatility projections are the primary aim, followed by volatility forecasts and market repercussions. The research provides a functional variant of the conditional distribution $\left(f\left(x|y\right)\right)$ based on conditional moments and a long-simulated state vector realization (MCMC-GMM) that is evaluated on observed data (a non-linear Kalman Filter) and applicable for step-forward volatility forecasts. For front year and quarter financial electricity contracts, the SV model creates two mean-reverting factors: one persistent and slowly moving component and one choppy, rapidly moving component. According to these factors, static volatility predictions with optimum and generous lags have a Theil covariance percentage of well over 97 percent for the front year contracts and 86 percent for the front quarter contracts. The volatility visibility and its associated static forecasts improve market transparency and will eventually make diversification and risk management easier to implement. Full article

The past decade has seen rapid development of the bioeconomy in the Nordic region. Consequently, the composition of sectors that intervene in the concept of bioeconomy serves as a powerful, progressive, and pure engine, which creates and drives market opportunities across various industries, particularly in the Nordic region. While the existing literature focuses explicitly on the bioeconomy and its holistic potential and results in the Nordic region, there are no studies that focus on the distribution of economic performance across Nordic Bioeconomy Sectors. In fact, previous research highlights the lack of empirical studies in bioeconomy from the social science perspective. This research methodology was designed in four different stages with the integration of so-called hybrid research methods. The qualitative research approach was conducted in order to define the criteria and indicators for Nordic Bioeconomy Sectors (NBES) and their economic performance. The quantitative research approach was conducted to statistically test Hypothesis H1 of this study and to conduct central tendency measures of economic performance within Nordic countries and Nordic Bioeconomy Sectors (NBES). The findings contribute in several ways to understand how sectors in the Nordic region performed economically. Firstly, the economic performance among the Nordic Bioeconomy Sectors (NBES) proves that individual sectors have diverse relationships with each other; therefore, each economic activity performs independently rather than correlative. Full article

Electricity has been produced in Norway in hydropower plants since 1877. The first wind power plant was put into operation in 1986. The growth in wind power production was weak in the first years after the turn of the millennium, but after Norway joined the Swedish subsidy scheme Tradable Green Certificates in 2012, there was significant growth in the wind power industry. While most of the hydropower production in Norway is owned by the public sector, the majority of wind power production is owned by foreign investors. Since wind power has been very much discussed in Norway, a levelized cost of energy (LCOE) model that can be well suited for this type of discussion is presented. The point here is that one must include all the costs, including the externalities. The Norwegian electricity market is dominated by a single player: Nord Pool. Ninety-six percent of all the electricity produced in Norway is sold through the power exchange Nord Pool, and the prices set by Nord Pool affect the finances of all the electricity producers in Norway, as well as producers in Scandinavia and the Baltic countries. This paper is a survey of the growth, development of production and economic performance of the Norwegian wind power industry and some aspects of the electricity market in the Nordic countries. Full article

To limit global warming to less than 2 °C requires a low-carbon transition with very large shares of renewables. Options such as wind, solar and hydro are influenced by both short and longer-term weather and climate variability. While still subject to natural and anthropogenic climate forcing and fluctuating energy prices, water reservoirs can dually operate as storage and production facilities and serve to balance the more volatile production capacity from solar and wind. This paper assesses the dynamics and demands of the hydro-dominated Nordic electricity system and market and identifies untapped potential for climate services based on a combination of literature-based research, documented stakeholder needs and data sources on historical and future conditions. A critical need for both improving the appropriateness and reliability of existing climate services and for developing new tailored solutions for a broader group of stakeholders from the renewable energy sector in the Nordics is observed. The quantification of uncertainties related to short-term weather forecasts and longer-term climate predictions is also found to be important for minimizing the financial risk in relation to systems management and to overall investments in renewable energy. Full article

In this paper, we present the results from the development and the simulation of a hydro power model for Sweden and Norway, using SpineOpt software and openly available data. We employ (i) hydrological and market data from the Nordic region and (ii) the abstract representation of the multi-vector modelling and simulation engine SpineOpt, to compile an open-source model of a large portion of the hydro power plants of the Nordic region, for conducting realistic hydro power generation studies. We place the hydro power system operation within the structuring of the Nordic electricity market and study the effect that different objectives have on the operational results. By employing the SpineOpt functionalities for automating the transformation of the temporal resolution of the model, we explore the trade-of between its computational burden and accuracy. Full article

This study investigates whether the merger of NASDAQ and OMX could reduce the portfolio diversification possibilities for stock market investors and whether it is necessary to implement national policies and international treaties for the sustainable development of financial markets. Our study is very important because some players in the stock markets have not yet realized that stock exchanges, during the last decades, have moved from government-owned or mutually-owned organizations to private companies, and, with several mergers having occurred, the market is tending gradually to behave like a monopoly. From our analysis, we conclude that increased volatility and reduced diversification opportunities are the results of an increase in the long-run comovement between each pair of indices in Nordic and Baltic stock markets (Denmark, Sweden, Finland, Estonia, Latvia, and Lithuania) and NASDAQ after the merger. We also find that the merger tends to improve the error-correction mechanism for NASDAQ so that it Granger-causes OMX, but OMX loses predictive power on NASDAQ after the merger. We conclude that the merger of NASDAQ and OMX reduces the diversification possibilities for stock market investors and our findings provide evidence to support the argument that it is important to implement national policies and international treaties for the sustainable development of financial markets. Full article

Finland has adopted a high profile in climate change mitigation. A national target of achieving carbon neutrality by 2035 has been declared. As a part of this, the use of coal for energy purposes has been banned from May 2029 onwards. The Nordic electricity market was a world fore-runner in creating a liberalized, multi-national electricity market in the 1990s. At present, the electricity systems of Finland, Sweden, and Norway are already very low-carbon. The Baltic countries Estonia, Latvia, and Lithuania joined the Nordic market about a decade ago. Estonian electricity production is the most carbon-intensive of all the EU countries due to the extensive use of domestic oil shale. Especially Lithuania still suffers from capacity deficit created by the closure of the Soviet time nuclear reactor Ignalina in Lithuania. This paper presents the ambitions of the EU and national level energy and climate policies and models the multi-national impacts of Finland’s forthcoming closure of coal-fired generation. We also take into account Sweden’s planned decrease in nuclear generation. We find that these national-level policies have an impact on the Baltic countries as reduced import possibilities and increasing electricity prices, and the expected rise of the EU CO₂ allowance prices amplifies these. We further find that the abandonment of coal and nuclear power plants increases the net import and increases CO₂ emissions in neighboring regions. Full article

Attention towards topics such as environmental pollution, climate change, or biodiversity has strongly increased in the last years. The struggles to balance market powers and ecological sustainability somehow evoke memories of the early days of European welfare states, when social protection emerged as a means to prevent industrial capitalism from disruptive social tensions due to excessive social inequalities. In fact, social and environmental crises are inseparably intertwined, as ecological destruction is likely to be followed by social deprivation, and a lack of social security can be a crucial barrier for ecologically sustainable action. Our paper seeks to provide a step towards such an integrated perspective by studying problem pressure and public interventions in the area of green welfare, that is, in social and environmental protection. By using available data from Eurostat and Environmental Performance Index (EPI) databases, we contrast environmental and social performances to detect links between the social and the ecological dimension in these areas and unearth different configurations of green welfare among European countries. Our findings suggest that there are different “worlds of eco-welfare states” which only partially overlap with the more conventional “world of welfare states” but show how the Nordic countries are in the relatively-better performing cluster. Full article

With the increasing coupling of the power system and the natural gas system, the electric–gas interconnection system has become a typical form of comprehensive energy utilization. Through the energy conversion function of the coupling unit, the system can flexibly participate in the bidding for purchasing and selling energy in a power market and a natural gas market on the premise of meeting the internal demand of multiple loads. To solve the internal coordination and optimization problem and the external flexible bidding problem in the multi-energy market, this paper proposes a robust optimization model of energy purchase and sale for the electric–gas interconnection system in a multi-energy market. Firstly, the basic structure of the electric–gas interconnection system is introduced, and the steady-state model of energy flow in the system is built based on the energy hub model. Secondly, considering the uncertainty of energy prices and the output power of renewable energy units in the system, a bidding model for energy purchase and sale of the electric–gas interconnection system in multi-energy market based on the idea of robust optimization is constructed in the framework of the Nordic energy market. Finally, empirical analysis based on the actual data is carried out, and the results prove the validity and superiority of the model. In this paper, aiming at the uncertainty of energy price, a large number of scenes are generated by Latin hypercube sampling (LHS), and then a k-means algorithm is used to reduce the scenes, so as to simulate typical scenes. Aiming at the uncertainty of the output power of the renewable energy unit in the system, a cardinal uncertainty set is used to control deviation between the actual output power and predicted output power, so that the overall robustness of the model can be controlled. The proposed model can make decision-making independent of the accurate probability distribution of uncertainty factors, and is suitable for complex multi energy systems. Meanwhile, the model possesses excellent robustness, which can effectively reduce the risk of bidding loss in the process of energy purchase and sale. Full article