Optimally allocating renewable generation in Ireland: a long-term outlook until 2050. ESRI Research Bulletin, 2018/03

The Irish energy white paper released in December 2015 states the objective of diversifying electricity generation from renewable energy sources (RES-E). While onshore wind is planned to continue to make a significant contribution, the question arises which roles other RES-E technologies, such as solar PV, wind offshore or bioenergy, will play in the future. Moreover, the Irish 2030 target for RES-E is about to be set. Since the electricity demand growth in future is uncertain and the national target is yet unknown, this creates a high uncertainty around the overall amount of RES-E required. In this uncertain context, this research seeks to provide support for 1. achieving the national RES-E target determined as percentage share of energy demand in a cost minimal way under consideration of different diversification approaches, and 2. long-term planning of the electricity system by providing insight into the future regional distribution of generation and demand under different scenarios

Renewable origin, additionality, temporal and geographical correlation – eFuels production in Germany under the RED II regime

E-fuels are a promising technological option to reduce the carbon footprint in the transportation sector. To ensure the renewable origin of electricity-based fuels and minimize the impact of power-to-liquid facilities on the electricity grid, the European Union implemented electricity purchase conditions within the Renewable Energy Directive II. In this work, we analyze the impact of these electricity purchase conditions on the optimal placement, dimensioning and operation of facilities and the German electricity system. The results show that implementing the proposed electricity purchase conditions increases electrolysis capacity by 15.8% and reduces utilization by 672 h in 2030. With the constrained electricity supply, the power-to-liquid facilities concentrate on network nodes with high renewable potential, while the carbon dioxide supply loses importance. Overall, the German electricity system is not heavily affected by the proposed purchase conditions as the required renewable generation capacities only increase slightly. At the same time, carbon dioxide abatement costs rise by 14.3% by introducing the electricity purchase conditions

Does experience matter? Assessing user motivations to accept a vehicle-to-grid charging tariff

Vehicle-to-grid (V2G) could be a cornerstone to ensure the efficient integration of a large number of electric vehicles (EVs) and the resulting electricity demand into the energy system. However, successful V2G adoption requires direct interaction with the EV user. To explore user preferences and requirements in the context of a V2G charging tariff, we conducted a survey (N = 1196). We assess users’ minimum range requirements and willingness to pay for a V2G charging tariff and relate them to users’ experience with EVs. By building a mediation model, we evaluate the importance of three charging strategies to guide users’ minimum range requirements and expected monetary savings. The results reveal EV owners’ preference for a climate-neutral charging strategy, leading to a higher readiness to accept lower minimum ranges and lower monetary savings. These results are especially important to aggregators, aiming to design profitable business models, while accounting for user requirements and preferences

Highly resolved optimal renewable allocation planning in power systems under consideration of dynamic grid topology

The system integration of an increasing amount of electricity generation from decentralised renewable energy sources (RES-E) is a major challenge for the transition of the European power system. The feed-in profiles and the potential of RES-E vary along the geographical and temporal dimension and are also subject to technological choices and changes. To support power system planning in the context of RES-E expansion and allocation planning required for meeting RES-E targets, analyses are needed assessing where and which RES-E capacities are likely to be expanded. This requires models that are able to consider the power grid capacity and topology including their changes over time. We therefore developed a model that meets these requirements and considers the assignment of RES-E potentials to grid nodes as variable. This is a major advancement in comparison to existing approaches based on a fixed and pre-defined assignment of RES-E potentials to a node. While our model is generic and includes data for all of Europe, we demonstrate the model in the context of a case study in the Republic of Ireland. We find wind onshore to be the dominating RES-E technology from a cost-efficient perspective. Since spatial wind onshore potentials are highest in the West and North of the country, this leads to a high capacity concentration in these areas. Should policy makers wish to diversify the RES-E portfolio, we find that a diversification mainly based on bioenergy and wind offshore is achievable at a moderate cost increase. Including solar photovoltaics into the portfolio, particularly rooftop installations, however, leads to a significant cost increase but also to a more scattered capacity installation over the country

Highly resolved optimal renewable allocation planning in power systems under consideration of dynamic grid topology

The system integration of an increasing amount of electricity generation from decentralised renewable energy sources (RES-E) is a major challenge for the transition of the European power system. The feed-in profiles and the potential of RES-E vary along the geographical and temporal dimension and are also subject to technological choices and changes. To support power system planning in the context of RES-E expansion and allocation planning required for meeting RES-E targets, analyses are needed assessing where and which RES-E capacities are likely to be expanded. This requires models that are able to consider the power grid capacity and topology including their changes over time. We therefore developed a model that meets these requirements and considers the assignment of RES-E potentials to grid nodes as variable. This is a major advancement in comparison to existing approaches based on a fixed and pre-defined assignment of RES-E potentials to a node. While our model is generic and includes data for all of Europe, we demonstrate the model in the context of a case study in the Republic of Ireland. We find wind onshore to be the dominating RES-E technology from a cost-efficient perspective. Since spatial wind onshore potentials are highest in the West and North of the country, this leads to a high capacity concentration in these areas. Should policy makers wish to diversify the RES-E portfolio, we find that a diversification mainly based on bioenergy and wind offshore is achievable at a moderate cost increase. Including solar photovoltaics into the portfolio, particularly rooftop installations, however, leads to a significant cost increase but also to a more scattered capacity installation over the country

Decentralized Energy Systems, Market Integration, Optimization

In this study we develop a flexible modeling toolbox for decentralized electricity systems with an agent-based simulation approach at its core. Two RES-E generation models for wind and PV each with a high temporal and spatial resolution are presented and approaches to model specific aspects of the demand side in detail are introduced. The implementation of an AC load flow algorithm is described and the concept of a market-based congestion management mechanism is outlined