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In this paper we take the perspective of a competitive hydropower producer located in Southern Norway, and calculate the profitability of investing in a pumped storage facility in price-scenario for Europe in 2050. A methodology to analyze the combined supply of day-ahead energy and real-time balancing is described and applied. A sequential optimization for optimal supply in each market is applied, utilizing the same resource cost for hydropower. When supplying balancing energy in addition to the supply in the day-ahead market, total income increase by only 2.2%. However, the additional income because of the investment increases by 21%. [ABSTRACT FROM AUTHOR]

Abstract: The future European energy supply system will have a high share of renewable energy sources (RES) to meet the greenhouse gas emission policy of the European Commission. Such a system is characterized by the need for a strongly interconnected energy transport grid as well as a high demand of energy storage capacities to compensate the time fluctuating characteristic of most RE generation technologies. With the RE generators at the location of high harvest potential, the appropriate dimension of storage and transmission system between different regions, a cost efficient system can be achieved. To find the preferred target system, the optimization tool GENESYS (Genetic Optimization of a European Energy System) was developed. The example calculations under the assumption of 100% self-supply, show a need of about 2,500 GW RES in total, a storage capacity of about 240,000 GWh, corresponding to 6% of the annual energy demand, and a HVDC transmission grid of 375,000 GWkm. The combined cost for generation, storage and transmission excluding distribution, was estimated to be 6.87 ct/kWh. [Copyright &y& Elsevier]

Abstract: A growing amount of congestions is expected for future operation of electrical transmission grids in Europe. Within this context, storages can be used to assist transmission system operators in daily operation and to avoid costly redispatch measures. In this paper, a research methodology to evaluate impact and interdependencies between market operation of storages and participation in redispatch measures is presented. Furthermore, a methodology for the evaluation of benefits by storages solely administrated by TSO is introduced. The methods are evaluated in a case study for the German electricity system in the year 2020. [Copyright &y& Elsevier]

Grid integrated water electrolysers have the potential of coupling electric power systems subjected to high shares of renewable energy sources with sectors of hydrogen demand, thus contributing to European decarbonization goals in future. We therefore investigate the business potential of future electrolyser applications in cross-commodity arbitrage trading by applying a complex power market simulation method for future scenarios and different European countries. Based on this, we evaluate the potential of additional provision of grid services towards grid operators in order to increase the electrolyser utilization ratio. For this, we use a method that identifies measures of transmission grid operators in order to ensure secure grid operation. In this context, uncertain hydrogen prices and different sectors of hydrogen demand are addressed through sensitivities of different hydrogen sales prices. The analysis shows a high dependency of business model efficiency on the hydrogen price. While cross-commodity arbitrage trading can achieve profitability for the transportation sector, applications for the industry sector and natural gas system are less efficient. The results however indicate that for these less efficient applications grid service provision can be an option of increasing the electrolyser utilization ratio thus increasing its profitability. [ABSTRACT FROM AUTHOR]

Highlights: [•] We develop an energy hub by wind, storage and demand response in distribution network. [•] We present two objective functions for the hub operation under certainty and uncertainty of wind, price and demand. [•] We consider operation costs, emission and reliability in the objective function. [•] We apply two stage stochastic programming of GAMS for solving the hub MILP model under uncertainty. [•] We evaluate effect of DERs and the uncertainties on hub operation costs and reliability in nine cases. [Copyright &y& Elsevier]

Energy System Optimization Models are applied to inform decision making processes and therefore must account for the uncertainty as it exists in the real world. In the recent decade, Modeling to Generate Alternatives gained popularity for considering structural uncertainty in Energy System Optimization Models. Modeling to Generate Alternatives finds numerous near-optimal alternatives, which could give the impression that all alternatives are comparably good. However, if one could compare near-optimal shadow prices of energy demand, certain alternatives would be superior to other solutions. Nevertheless, shadow prices of near-optimal solutions reflect the effort of being different and no approach to calculate expedient shadow prices of near-optimal solutions (comparable to the optimal one) has been presented. A simple approach is suggested and discussed with its implications, using an example scenario. The obtained shadow prices further differentiate the quality of solutions in the near-optimal solution space. Deeper analysis reveals regional or temporal bottlenecks of solutions and can help identify better search directions for alternative solutions. To some extent, the shadow prices highlight effects of parametric uncertainty, even though the proposed method cannot counteract this uncertainty. • Energy System Optimization Modeling benefits from analysis of near-optimal solutions. • Approach to enable expedient comparison of near-optimal shadow prices is presented. • Numerous near-optimal solutions are evaluated using said shadow prices. • Shadow prices differentiate the quality of Modeling to Generate Alternatives' solutions. [ABSTRACT FROM AUTHOR]

The energy system decarbonization leads to a decentralization of generation and flexibility. Among the new concepts to integrate distributed flexibility are local energy markets. While a broad range of research investigates local energy markets on a distribution grid level in detail, research on their system impact has been limited. Therefore, we develop a framework to investigate different configurations of local markets as well as the operation of distributed energy resources and their interaction with the wholesale markets. This framework is applied to a pan-European case study with detailed bottom-up modeling of local energy markets in France and Germany. Additionally, transmission grid simulations are carried out to investigate the impact of local trading on grid congestions. Our results show that a direct coordination of distributed flexibility within the wholesale market is more efficient than a preference for local trading. Nonetheless, local energy markets can be used as an incentive for the expansion of distributed flexibility as well as a way to break down the complexity of coordinating millions of distributed assets in a single market. Additionally, our results show that local trading relieves the transmission grid. • Bottom-up modeling of distributed flexibility in France and Germany. • Large-Scale-Modeling of LEMs. • Impact Assessment on Day-ahead market and transmission grid. [ABSTRACT FROM AUTHOR]

Integrating increasing shares of weather-dependent renewable energies into energy systems while maintaining high levels of security of supply constitutes a challenge for system operators. The system integration of large shares of variable renewable energy generation requires an effective operation of electricity grids and efficient coordination among grid operators. Hence, the detailed modelling of grid operation has increasingly become important in recent years. Methods for modelling the operation of (extra) high-voltage grids are undergoing persistent enhancements in academia and industry. Existing approaches vary in data granularity and computational methods. Moreover, assumptions on technical details in grid models vary. The results are thus subject to differences in input data and modelling methods. The paper at hand aims to identify the most relevant differences that exist amongst grid simulation models and methods for studying congestion management in a European context. Differences are studied based on a comparison of grid simulation models from eight German energy modelling institutions. The effects of model parameterization and formulation on congestion management results are investigated based on three different case studies focusing on outage simulation, line constraint relaxation and the modelling of cross-border measures. Results indicate that data parametrization can have large impacts on model results with respect to congestion management volumes and the geographic distribution of the respective measures. The analysis also highlights the need to thoroughly calibrate key model parameters. The research findings will assist the grid modelling community and power system planners in simulating congestion management and increase the validity and explorative power of grid simulation models. • Various differences in model formulations for grid operation exist in academia. • Soft-constraints are widely used to detect data inconsistencies and infeasibilities. • Simplified outage simulations particularly impact congestion results in meshed grids. • Parametrization of cross-border measures largely affects congestion volumes. [ABSTRACT FROM AUTHOR]

Abstract: Feeder reconfiguration is one of the most important tasks for loss reduction and reliability improvement in distribution networks. Most of studies so far have investigated reconfiguration problem as a static problem considering fixed level of loads. This assumptions lead to suboptimal solution because of time-varying nature of loads in distribution networks. The switching operation should be cost effective and the reconfiguration scheme should balance the benefits in system loss reduction and reliability improvement against the costs of switching. Moreover, this is a dynamic problem and switching operations of time intervals over a year are not independent. This paper presents a method to determine annual feeder reconfiguration scheme considering switching costs and time-varying variables such as load profiles. In the first stage of the proposed method, to obtain effective configurations, optimal configuration for each day of year is determined independently using harmony search algorithm (HSA) and graph theory. After determination of effective configurations for the network, in the second stage, year is divided into multi equal periods and considering loss cost, interruption cost and also switching cost from a configuration to another configuration, dynamic programming algorithm (DPA) is used to find the optimum annual reconfiguration scheme. The proposed method has been tested on 95-bus distribution network and the obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically. [Copyright &y& Elsevier]