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

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

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Demonstration of visualization techniques for the control room engineer in 2030.:ELECTRA Deliverable D8.1. WP8: Future Control Room Functionality

Deliverable 8.1 reports results on analytics and visualizations of real time flexibility in support of voltage and frequency control in 2030+ power system. The investigation is carried out by means of relevant control room scenarios in order to derive the appropriate analytics needed for each specific network event

Impacts of electric vehicles on the European high and extra high voltage power grid

The impact of electric vehicles on the electricity grid has been focused on by the literature in many facets, comprising considerations of the electricity system of a single household up to the highest voltage grid level. But each of these analyses is focusing on a single grid level. While the impact on the local level depends strongly on the specific environment and is consequently diverse, there is strong evidence that the impact on the highest grid level is non-critical. So far, there is no study considering several voltage levels together. Consequently, we analyzed here for the first time all voltage levels between 60 and 380 kV together for the European transmission grid and included, besides the load flexibilities from home charging, also the load from fast charging stations for the year 2050 with a completely replaced car fleet by electric vehicles. While the impact on the security of supply is rather marginal, with a slight increase of load shedding on some distribution grid nodes, the impact on nodal prices and greenhouse gas emission is—with up to 9%—more severe. When applying the model on the highest grid level alone, our results show significantly smaller impacts. These results endorse our comprehensive approach, which considers several grid levels and their comprehensive interactions—an isolated consideration of grid levels seems inappropriate for our research questions

Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland. ESRI Working Paper No. 653 March 2020

This paper analyses how people’s attitudes towards onshore wind power and overhead transmission lines affect the costoptimal development of electricity generation mixes, under a high renewable energy policy. For that purpose, we use a power systems generation and transmission expansion planning model, combined with information on public attitudes towards energy infrastructure on the island of Ireland. Overall, households have a positive attitude towards onshore wind power but their willingness to accept wind farms near their homes tends to be low. Opposition to overhead transmission lines is even greater. This can lead to a substantial increase in the costs of expanding the power system. In the Irish case, costs escalate by more than 4.3% when public opposition is factored into the constrained optimisation of power generation and grid expansion planning across the island. This is mainly driven by the compounded effects of higher capacity investments in more expensive technologies such as offshore wind and solar photovoltaic to compensate for lower levels of onshore wind generation and grid reinforcements. The results also reveal the effect of public opposition on the value of onshore wind, via shadow prices. The higher the level of public opposition, the higher the shadow value of onshore wind. And, this starkly differs across regions: regions with more wind resource or closest to major demand centres have the highest shadow prices. The shadow costs can guide policy makers when designing incentive mechanisms to garner public support for onshore wind installations

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero‑carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.publishedVersio