8 research outputs found

    PowerSimulationsDynamics.jl -- An Open Source Modeling Package for Modern Power Systems with Inverter-Based Resources

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    The inclusion of inverter-based resources from renewable energy creates new challenges for the stability and transient behavior of power systems which are best understood by studying their dynamic responses through simulation. In this paper, we develop an open source simulation toolbox, PowerSimulationDynamics.jl, to study the dynamic response of a balanced system with high penetration of inverter-based resources. PowerSimulationDynamics.jl is implemented in the Julia language and features a rich library of synchronous generator components and inverter models. In addition, it allows the study of both quasi-static phasors that employ an admittance matrix representation for the network and electromagnetic dq models that use a dynamic representation of the network. Case studies and validation exercises show that PowerSimulationDynamics.jl results closely match Quasi-Static Phasor (QSP) tools like Siemens PSSe, ANDES, and wave-form Electro-magnetic Transient (EMT) simulations like PSCA

    Small-Scale Communities Are Sufficient for Cost- and Data-Efficient Peer-to-Peer Energy Sharing

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    Due to ever lower cost, investments in renewable electricity generation and storage have become more attractive to electricity consumers in recent years. At the same time, electricity generation and storage have become something to share or trade locally in energy communities or microgrid systems. In this context, peer-to-peer (P2P) sharing has gained attention, since it offers a way to optimize the cost-benefits from distributed resources, making them financially more attractive. However, it is not yet clear in which situations consumers do have interests to team up and how much cost is saved through cooperation in practical instances. While introducing realistic continuous decisions, through detailed analysis based on large-scale measured household data, we show that the financial benefit of cooperation does not require an accurate forecasting. Furthermore, we provide strong evidence, based on analysis of the same data, that even P2P networks with only 2--5 participants can reach a high fraction (96% in our study) of the potential gain, i.e., of the ideal offline (i.e., non-continuous) achievable gain. Maintaining such small communities results in much lower associated costs and better privacy, as each participant only needs to share its data with 1--4 other peers. These findings shed new light and motivate requirements for distributed, continuous and dynamic P2P matching algorithms for energy trading and sharing
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