Optimizing Energy Systems with AnyLogic Simulation Modeling

Preface:

European Institute for Energy Research (EIFER), the joint research center of Karlsruhe Institute of Technology and EDF Company, is an organization that deals with the decentralization of energy systems on various territories, and promotes renewable energy sources. Localized energy systems, unlike classical ones, do not require to transmit electricity over long distances, as they are located close to the load they serve. Being less hierarchical, they provide the prospects of power storage, renewable energy inclusions, and demand forecasting. EIFER engineers chose AnyLogic simulation modeling to find out how the localized systems should be planned and operated. It helped design multiscale models, which included all parts of the energy system, and aimed at understanding causes and effects throughout the systems’ scales. With AnyLogic, the company defied to handle emergency phenomena that might happen in decentralized systems.

Case #1: Smart Grid Modeling on Island Systems – Demand Side Flexibility

Energy System Simulation Modeling

Problem:

Energy production on island territories is expensive and depends on the cost of oil. EIFER aimed to test how the inclusion of photovoltaic elements would affect the classical energy system at such territories, thus trying to reduce costs and oil dependency.

Energy System Simulation Modeling

Solution:

The current system comprised three scales based on the voltage areas. The area with the lowest voltage (final customer level) was chosen for the implementation of photovoltaic elements. After those were distributed in the model, and experiments were run, the data was re-aggregated to capture the impact on the whole system and avoid any breakages and power overconsumption.

It was decided to model the scenario when the island would be partly covered with clouds to test if the system’s balance would be disturbed. It turned out that, due to cloud coverage, there was higher production at the thermal plant located at non-cloudy areas, which could lead to the system’s imbalance.

Outcome:

AnyLogic modeling helped simulate the influence of photovoltaics on the island’s current energy system. The cloud coverage scenario was implemented to test the model’s flexibility and show meteorological impact on the system.

Case #2: Optimization for Local Energy System Management

Energy System Simulation Modeling

Problem:

EIFER researchers study not only new ways of energy generation, but also already existing ones, namely cogeneration. This process involves simultaneous generation of electricity and useful heating, thus cutting production costs. Also, it is one of the most cost-efficient methods of reducing carbon emissions. EIFER engineers used AnyLogic to model and optimize cogeneration energy system’s behavior and find out how its various energy sources interact.


Solution:

In the agent-based model, the production plant generated electricity and heat, while ordinary people and the tertiary sector consumed it. The heat went to households, whereas electricity went to households or to grids. The output statistics showed how energy was distributing among the consumers and made possible to analyze capital and operational expenditures.

Outcome:

AnyLogic helped represent the energy system as a holistic one, connecting separate parts in one model. With AnyLogic, a modeling library was created to make it simpler to reuse certain blocks and agents in other models. User-friendly interface simplified the interaction with the model for unskilled AnyLogic users.

Output statistics allowed modelers to capture seasonality factors affecting the energy system, and analyze economic indicators.

Conclusion:

Energy systems tend to be multiscale and may be easily affected by various factors. With AnyLogic simulation modeling, it is possible to simplify complex systems and capture the issues connected with variabilities, demonstrating how alterations in one scale may affect the whole system.


To learn more on how EIFER performs energy systems’ decentralization and applies renewable energy sources, read the following papers:

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