CityMoS Platform

The functionality offered by the CityMoS platform as described in this chapter is currently unique among the investigated literature. CityMoS provides the architecture to compose

2 Several bugs reducing the performance have been found and acknowledged by the vendor resulting in a yet unpublished interim version 4.4.1i.

interoperable distributed system simulations and is thereby not limited to neither the described power and transportation system simulations nor the presented interactive visualization. In principle, any simulation implementing an HLA Bridge package as specified in Section 3.6 can be included. This also allows replacing any of the provided federates by other simulations in case their functionality better matches the individual use case. Competing tools focus on either the transportation or the power system side. Achieving interoperability among multiple simulations has never been the design goal of any of those tools. As argued in [164], extensive source code modifications are therefore required to allow studying bidirectional dependencies instead of simply implementing an HLA Bridge package into a new federate of the CityMoS platform as described in Section 3.6. Albeit, in the following, alternatives for both CityMoS Power and CityMoS Traffic are outlined:

• CityMoS Power

The functionality of CityMoS Power which is provided in four different modules can currently not be replaced by a single tool as argued in Section 2.1. Related approaches providing a functionality approximating the one of the first two modules, planning and evaluating PNMs, were already presented and discussed in Section 2.6.1. Software tools implementing any of those approaches are publicly not available. Alternatives to the third module, scheduling of battery energy storage, are described in [13–15]. Again, a software implementation of any of the approaches is publicly not available. With the fourth module offering the possibility for conducting power flow simulations, the situation is different. There are multiple different algorithms and tools available allowing for computing the capacity utilization at every branch as well as the voltage at every bus. A total of 40 commercial and 25 non-commercial power system simulation software packages are provided in [165, 166], each being equivalently able of replacing JPOWER as the applied power flow model.

• CityMoS Traffic

Transportation system simulations can be distinguished according to their level of detail representing the traffic flow intomacro-, meso-, micro-, andnanoscopicsimulations [167].

Only at a micro- and nanoscopic level of detail individual agents are simulated. This level is assumed necessary for this work’s investigation. On a more coarse-grained level, individual driving pattern or driver behavior is not modeled thus providing results which tempo-spatially do not have the level of detail required in the context of this work. An excellent primer into agent-based transportation system modeling and simulation can be found in [168, 169].

In Table 3.3, a list of the most relevant transportation system simulations distinguished by their license type is provided. A detailed comparison of many of them can, for instance, be found in [164, 168–170]. With regard to the current limitation of CityMoS Traffic lacking a proper bidirectional HLA module as described in Section 3.4, any of the presented simulations may alternatively be used, assuming a proper implementation.

This is due to the usage of the same well-known driver behavior and vehicle component models as well as similar routing algorithms. Applying the same trip data as input, the

Table 3.3: Overview of transportation system simulation tools.

Acronym Name Literature

Opensource

JAAMSIM Java Animation Modelling and Simulation [173, 174]

MAINSIM Multimodal Innercity Simulation [175]

MATSim Multi-Agent Transport Simulation [176]

MITSIMLab Microscopic Traffic Simulator Laboratory [177]

MovSim Multi-model Open-source Vehicular-traffic Simulator [178]

REPAST Recursive Porous Agent Simulation Toolkit [179, 180]

SUMO Simulation of Urban Mobility [181, 182]

TRANSIMS Transportation Analysis and Simulation System [183, 184]

Veins Vehicles in Network Simulation [185, 186]

Commercial

AIMSUN Advanced Interactive Microscopic Simulator for Urban and Non-Urban Networks

[187]

CORSIM Corridor Simulation [188]

ITSUMO Intelligent Transportation System for Urban Mobility [189]

PARAMICS Parallel Microscopic Simulation [190]

VISSIM Verkehr In Städten - Simulationsmodell [191]

output of any of those simulations does presumably not differ much, although not being investigated further in this work.

The referenced simulations do not provide for simulation interoperability. They, however, may be extended by a proper HLA module. For SUMO, the steps required to integrate HLA are described in [171]. Latest efforts in designing a distributed simulation platform offering a transportation system simulationsoftware as a service in the cloud using HLA are still at a conceptual stage [172]. In [127], a similar concept is presented for the CityMoS platform.

3.8 Conclusions

CityMoS is a distributed simulation platform intended for urban infrastructure planning in which the single components are interoperating using the IEEE Standard 1516-2010, termed HLA. This standard is used for constructing reusable and interoperable distributed system simulations enabling bidirectional communication between joined federates, even spanning across heterogeneous hardware and software platforms. CityMoS is not limited to specific simulations; instead, any component supporting HLA with a compatible SOM may act as a joined federate. In the context of this work, CityMoS is used for investigating the impact of different road transportation electrification scenarios on urban power systems in Chapter 4.

The platform therefore comprises the following components:

• CityMoS Power

As an implementation of the PSS framework described in Chapter 2, CityMoS Power allows planning and evaluating PNMs for subsequently conducting power flow studies

on them. The included smart scheduling approach for battery energy storage enables applying different, even price-responsive strategies for charging and discharging PEVs.

CityMoS Power is implemented in Java and can operate either standalone using offline data or as a joined federate dynamically exchanging data with other participants of the same federation execution. Its input and output data uses the XML format for which a formal specification in form of an XSD is provided.

• CityMoS Traffic

The agent-based transportation system simulation CityMoS Traffic is able to simulate the movements of a vehicle population as a discrete sequence of events in time. Each vehicle is modeled as an individual agent represented by a driver-vehicle unit comprising own driver behavior and vehicle component models. Those models allow agents to also represent PEVs as required for this work. Agents are routed along a given road network according to their individual trip data. Its output data in a disaggregated form comprises the tempo-spatial position of each single agent. In an aggregated form, tempo-spatial trip data including the required energy and covered distance is provided. Due to storage requirements and processing speed, both the aggregated and disaggregated form uses the CSV format.

• CityMoS Frontend

As an interactive visualization tool, CityMoS Frontend allows participating in and controlling of federation executions and their joined federates in a coupled environment using HLA. User interactions are not limited to the standalone visualization of offline data; instead, they also cover the exchanged data between joined federates at runtime.

This way, users are enabled to not only visualize and inspect the output of all joined federates but also actively produce data and thereby interact with them. Visually providing insights into the exchanged data of a federation execution allows users to be more easily attracted to the simulation platform by nurturing their understanding of its functioning and creating confidence in the results. CityMoS Frontend is also implemented in Java. Instead of defining an own data format, the input and output format used by each joined federate is supported.

The functionality offered by the ensemble of the single components of the CityMoS platform is currently unique among the investigated literature. The platform allows evaluating a great variety of large-scale what-if road transportation electrification scenarios on realistically emu-lated power system infrastructure before they are implemented in a real-world setting. Those scenarios include but are not limited to alternating the design of the power and transporta-tion system infrastructure, varying the CS locatransporta-tion and power connectransporta-tion, applying different scheduling strategies, assuming diverse agent charging behavior, diversifying the composition of the vehicle population, as well as applying demand-responsive or vehicle-to-grid charging and discharging schemes. In case further scenarios need to be investigated, CityMoS can be extended by additional federates as, for instance, a railway transportation system simulation.

Existing federates can also be replaced by alternative ones in case their functionality better matches the individual use case. In its presented composition, the CityMoS platform is mainly targeting researchers who want to conduct large-scale exploratory simulation experiments to

investigate interdependence between various systems and their components. Moreover, experts of adjacent areas who are not familiar with either transportation or power system simulations are provided a tool with which they are able to conduct interdisciplinary studies targeting the exploration of future road transportation electrification.