Academic articles

Hybrid Simulation and Optimization-Based Capacity Planner for Integrated Photovoltaic Generation with Storage Units

Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization.

Hybrid simulation of renewable energy generation and storage grids

The share of renewable energy sources in energy production is growing steadily. Domestic homes can be equipped with solar panels, micro combined heat and power systems, batteries, and they can become adaptive consumers. They can also deliver energy to the grid and react to the energy supply. This paper presents a hybrid simulation approach for the analysis of a grid of domestic homes equipped with different technological options with respect to efficiency and costs. For energy storage and energy flows the system dynamics modeling paradigm is used whereas control decisions are modeled as statecharts. The highly intermittent solar irradiation and also the electric power and heat demands are implemented as stochastic models. The component-based design allows for quick creation of new case studies. As examples, different homes with batteries, micro combined heat and power systems, or energy carrier carbazole as energy storage are analyzed

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