eFlame – electric Flexibility assessment modeling environment
What is eFlame used for?
The modeling environment eFlame enables the economic and ecological assessment of various energy-related assets across a range of use cases. The term “energy-related assets” encompasses flexibility options such as battery storage systems and smart uni- or bidirectionally charged electric vehicles, as well as generation or consumption units like photovoltaic systems and industrial loads. Use cases that can be modeled with eFlame include, for example, trading on electricity and balancing markets or the optimization of self-consumption.
We can answer the following relevant questions with eFlame, for example:
- What is the historical and future revenue potential of storage technologies participating in electricity markets?
- To what extent can CO₂ emissions be reduced through CO₂-optimized or market price-optimized operation of flexible assets?
- What revenues can be generated through PV self-consumption optimization for households or businesses? To what degree can energy self-sufficiency be increased?
- Which companies are suitable candidates for peak load shaving, and what are the characteristics of their electric vehicle fleets?
- Which types of electric vehicles and user profiles are best suited to which use case?
Model Structure
The eFlame modeling environment enables a variable scenario definition by integrating a range of sub-models. Figure 1 illustrates the overall structure of the modeling framework. To realistically represent household behavior, eFlame utilizes the FfE Household Load Profile Generator, which generates consistent electrical and thermal load profiles based on various parameters such as household equipment, number of occupants, and size of the household. Thermal demand can be met using a heat pump, optionally supported by a thermal storage system, in an optimized manner. For the modeling of industrial companies, the FREM database is used, which contains real load profiles. Battery storage systems or other flexible assets, renewable energy systems including photovoltaic and wind power, as well as electric vehicles and their associated infrastructure, can be parameterized variably. In the case of electric vehicles, individual driving profiles from the Household Load Profile Generator can be assigned to match specific household types, while aggregated or discrete vehicle profiles can represent entire private or commercial fleets. Vehicles can be flexibly assigned to geographic regions and grid connection points. Furthermore, electricity imports from or exports to the grid can be modeled at the grid connection point using predefined electricity price time series.
The core of the eFlame model environment is the ResOpt (Residential Optimizer) optimization module, which calculates optimal load profiles for flexible assets, taking into account ancillary conditions. Depending on the modeled use case, ResOpt is formulated as a linear or mixed-integer linear programming problem. ResOpt is also used as a module in the GridSim distribution grid model to assess the grid impacts of household and commercial behavior.
Scenario configuration and result storage are handled via the FfE database, enabling consistent data management and flexible adaptation. The necessary input data are loaded from the database in Matlab, where simulations are initiated and optimization problems are solved using either the Gurobi or CPLEX solvers. Two high-performance servers are available at FfE for solving these optimization problems.
Application of eFlame in FfE Projects
Completed Projects
The eFlame model was initially developed as part of the completed research project BDL – Bidirectional Charging Management of Electric Vehicles. The project highlighted the economic and ecological added value of controlled and bidirectionally charged electric vehicles (EVs) compared to vehicles with immediate, uncontrolled charging behavior. Various vehicle-to-home use cases, such as PV self-consumption optimization, vehicle-to-business use cases, such as peak load capping, and vehicle-to-grid use cases, such as trading on the electricity market or the provision of balancing power, were investigated.
- Revenue potential, ecological added value and costs through the controlled and bidirectional charging of electric vehicles
- Revenue opportunities by integrating combined vehicle-to-home and vehicle-to-grid applications in smart homes
- Integrating Bidirectionally Chargeable Electric Vehicles into the Electricity Markets
- Repercussions of battery marketing options on the electricity market
In the subsequent research project Trade-EVs II, the focus was on commercial locations. Various use cases of controlled and bidirectional charging of electric vehicles at commercial locations were investigated, including both company-owned and employee vehicles in the optimization process. The aim was to develop the most cost-optimized charging strategies possible in order to reduce the operating costs of the vehicles. To do this, trading on various electricity markets (day-ahead and intraday) was combined with the provision of balancing power. Additionally, the project integrated opportunity costs resulting from battery degradation into the eFlame model.
- Assessing the incorporation of battery degradation in vehicle-to-grid optimization models
- Attractiveness and Business Model Potential of the Spot Market Optimized Charging of Electric Vehicles
- Opportunity or risk? Model-based optimization of electric vehicle charging costs for different types of variable tariffs from a consumer perspective
The NEFTON research project focused on the analysis and optimization of possible charging strategies for electric trucks. The investigations were carried out using a representative depot as a case study. Peak load shaving, temporal arbitrage, and PV self-consumption optimization were combined within a multi-use optimization framework using the eFlame model. Based on the simulation results, charging load profiles, power demand peaks, and charging costs for future electric truck depots could be derived.
In the unIT-e² project, the analyses conducted in BDL Next were extended to include additional (multi-)use cases for electric passenger vehicles. Various multi-use scenarios were assessed, such as the combined participation of electric vehicles in multiple spot markets as well as the integration of PV self-consumption optimization with spot market trading. In addition, the influence of Section 14a EnWG on the flexibility marketing of electric vehicles was examined. The analyses included both economic and ecological assessments. For the first time, price forecasts were also integrated into eFlame to account for future market conditions and uncertainties in price developments. Moreover, international market frameworks were considered to evaluate differences across countries. This work is being continued within the BDL Next project, with a specific focus on multi-use cases and price uncertainties.
- Use cases of smart and bidirectional charging: analysis and assessment of feasibility in European countries – FfE
- Several Contributions at the E-Mobility Symposium in Helsinki – FfE
- Systemic Evaluation of PV Self-Consumption Optimization Using Electric Vehicles
- The Impact of DSO Grid-Integration Measures on EV Users in Germany
Current Projects
Following the above-mentioned completed research projects, work is now underway in current research projects BDL Next, Kopernikus Synergie III, Bid-E-V and Spirit-E.
In the BDL Next project, eFlame is being used in particular in the three subject areas of price uncertainties, the European perspective and energy communities. In the continuation of the work from unIT-e², price uncertainties are now analyzed using a rolling optimization horizon, allowing for a more dynamic assessment of their impact on combined market participation strategies. Additionally, international market frameworks are also taken into account in order to evaluate cross-country differences. The model is also being extended to represent flexible actors within energy communities. This is intended to determine the revenue and flexibility potential of joint consumption optimization, as well as flexible residual electricity procurement and surplus electricity marketing.
In the Kopernikus SynErgie III project, a simulation-based assessment is conducted to evaluate the ecological and economic potential of V2H/V2G-capable electric passenger vehicles charged at the Living Lab of the FIM/FIT Institute in Augsburg. The analyzed use cases include PV self-consumption optimization, temporal arbitrage, and CO₂-optimized charging. These use cases serve as the foundation for the real implementation of bidirectional charging management within a field test. The data collected from this implementation and the other simulated use cases are combined to derive overarching findings.
The Bid-E-V project aims to promote the electrification of vehicle fleets in the logistics sector with the help of bidirectional electric vans. Within this context, eFlame is used to investigate optimal charging strategies for electric vans. The objective of the optimization is to minimize the Total Cost of Ownership (TCO) by combining multiple use cases.
The Spirit-E project analyzes and evaluates the systemic and grid-related integration of electrified commercial vehicle fleets and depot sites into the energy system. The eFlame model is used to assess the economic viability of electrified fleets and locations, as well as to analyze their systemic potential. The focus lies on the simulation of depot sites with various charging system configurations. In addition, the cost savings for use cases of bidirectional commercial vehicle fleets are calculated and the effects on the total cost of ownership (TCO) are determined, building on the work from Bid-E-V.
Consulting Projects
The eFlame model has also been successfully applied in various consulting projects.