Multi-modal Energy System Research Articles

Local multi-modal energy market for thermal-electric energy systems with consideration of temperature flexibility in heating subnetworks

District heating systems are critical in this transition towards climate-neutral energy systems as they enable a close coupling of thermal and electric energy systems. However, the operation of these multi-modal energy systems and adequate representation of conversion dependencies, such as from heat pumps, remain challenging.To address this challenge, a novel method is presented that incorporates the temperature of subnetworks of district heating systems into the market matching of a local energy market for thermal-electric energy systems. This market-based coordination approach includes a linear formulation of market orders tailored to the needs of consumers, producers, and prosumers in local multi-modal energy systems. Emphasis is put on the temperature flexibility of heat pumps that concurrently participate in both heat and electricity markets. Complementary market commodities are introduced to account for temperature constraints set by the market participants. The physical models of the district heating network and electric distribution grid are formulated linearly and incorporated into the market-matching.The proposed method is applied in a case study representing a German district heating system. We conclude that the temperature flexibility of heating subnetworks, and dependencies involved in energy conversion can be incorporated within a linear market-matching problem.

A reference architecture for the American Multi-Modal Energy System enterprise

The American Multimodal Energy System (AMES) is a system-of-systems comprised of four separate but interdependent infrastructure enterprises: the electric grid, the natural gas enterprise, the oil enterprise, and the coal enterprise. Their interdependence creates the need to better understand the underlying architecture in order to move towards a more sustainable, resilient and accessible energy system. Collectively, these requirements necessitate a sustainable energy transition that constitute a change in the AMES instantiated architecture; although it leaves its reference architecture largely unchanged. Consequently, from a model-based systems engineering perspective, identifying the underlying enterprise model’s reference architecture becomes a high priority. This paper defines a reference architecture for the AMES and its four component energy enterprises in a single SysML model. The architecture includes (allocated) block definition and activity diagrams for each enterprise. The reference architecture was developed from the S&P Global Platts (GIS) Map Data Pro data set and the EIA Annual Energy Outlook dataset. This reference architecture serves as the foundation from which to accurately and consistently create mathematical and informatic digital twins of the AMES.

Optimization-based framework for low-voltage grid reinforcement assessment under various levels of flexibility and coordination

The rapid electrification of residential heating and mobility sectors is expected to drive the existing distribution grid assets beyond their planned operating conditions This change will also reveal new potentials through sector coupling, flexibilities, and the local exchange of decentralized generation. This paper thus presents an optimization framework for multi-modal energy systems at the low voltage (LV) distribution grid level. In this, we focus on the reinforcement requirements of the grid and the techno-economic assessment of flexibility components and coordination between agents. By employing a multi-level approach, computational complexity is reduced, and various levels of coordination and flexibilities are implemented. We conclude the work with a case study for a representative rural grid in Germany, in which we observe high economic potential in the flexible operation of buildings, majorly thanks to better integration of photovoltaics. Across all paradigms barring a best-case benchmark, grid reinforcement based on a mix of passive and active measures was necessary. A synergy effect is observed between flexibilities and coordination, as their combination reduces the peaks to the extent of completely avoiding grid reinforcement. The presented framework can be applied with a wide range of grid and component types to outline the broad landscape of future LV distribution grids.

Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example

Sustainable energy grids and networks are converging. In recent decades, cost, sustainability, and digitization drivers have caused engineering systems to evolve into systems-of-systems that deliver multiple services across multiple application domains. These engineering systems include electrified-transportation systems, the energy–water nexus, and multi-modal energy systems. The rather complex and heterogeneous interdependencies between engineering system services necessitates a precise informatic representation that ultimately supports optimized management of the holistic dynamics and tradeoffs. Consequently, ontologically-robust, quantitative modeling tools are needed to represent the heterogeneity of the modeled system-of-systems while still remaining generic and extensible to a diversity of application domains. Hetero-functional graph theory has demonstrated itself as a such modeling tool. This work now builds upon this foundation to develop a dynamic hetero-functional network minimum cost flow optimization that meets the requirements of these emerging systems-of-systems. It optimizes the supply, demand, transportation, storage, transformation, assembly, and disassembly of multiple operands in distinct locations over time in a systems-of-systems of arbitrary number, function, and topology. First, the paper introduces a general approach to define a dynamic system-of-system model that integrates customizable dynamic device models into a hetero-functional graph theory structural model. To this end, the work leverages Petri net dynamics and the hetero-functional incidence tensor. The Petri net based models are then translated into a quadratic program in canonical form. The hetero-functional network minimum cost flow optimization is demonstrated on a hydrogen–natural gas infrastructure test case. Four distinct scenarios are studied to demonstrate potential synergies and cascading network effects of policy across multiple infrastructures.

Accessible Modeling of the German Energy Transition: An Open, Compact, and Validated Model

We present an easily accessible model for dispatch and expansion planning of the German multi-modal energy system from today until 2050. The model can be used with low efforts while comparing favorably with historic data and other studies of future developments. More specifically, the model is based on a linear programming partial equilibrium framework and uses a compact set of technologies to ease the comprehension for new modelers. It contains all equations and parameters needed, with the data sources and model assumptions documented in detail. All code and data are openly accessible and usable. The model can reproduce today’s energy mix and its CO2 emissions with deviations below 10%. The generated energy transition path, for an 80% CO2 reduction scenario until 2050, is consistent with leading studies on this topic. Our work thus summarizes the key insights of previous works and can serve as a validated and ready-to-use platform for other modelers to examine additional hypotheses.

Hydrogen supply chain scenarios for the decarbonisation of a German multi-modal energy system

Analysing hydrogen supply chains is of utmost importance to adequately understand future energy systems with a high degree of sector coupling. Here, a multi-modal energy system model is set up as linear programme incorporating electricity, natural gas as well as hydrogen transportation options for Germany in 2050. Further, different hydrogen import routes and optimised inland electrolysis are included. In a sensitivity analysis, hydrogen demands are varied to cover uncertainties and to provide scenarios for future requirements of a hydrogen supply and transportation infrastructure. 80% of the overall hydrogen demand of 150 TWh/a emerge in Northern Germany due to optimised electrolyser locations and imports, which subsequently need to be transported southwards. Therefore, a central hydrogen pipeline connection from Schleswig-Holstein to the region of Darmstadt evolves already for moderate demands and appears to be a no-regret investment. Furthermore, a natural gas pipeline reassignment potential of 46% is identified.

Multi-input, Multi-output Hybrid Energy Systems

Summary Jurisdictions and industries are setting ambitious goals to decarbonize energy systems. Low-cost wind, solar, and natural gas and the resultant dynamic electric grid require energy technologies to adapt in order to meet key attributes for modern energy systems: resilience, reliability, security, affordability, flexibility, and sustainability. When considering energy sources independently and competitively, value-added synergies among energy technologies may be overlooked for meeting demanding, multidimensional requirements. This paper presents novel concepts for tightly coupled hybrid energy systems that leverage capabilities of diverse energy generators, including renewable, nuclear, and fossil with carbon capture, to provide power, heat, mobility, and other energy services. The paper also presents a framework for engineering-based modeling and analysis for complex optimization of energy generation, transmission, services, processes and products, and market interactions. New modeling capabilities are needed to adequately represent multi-input, multi-output tightly coupled hybrid energy systems that utilize multiple feedstocks to create multiple products and services in novel and synergistic ways through increased coordination of energy systems and tightly coupled hybrid system configurations.

Agent Based Modeling in Energy Systems: Parametrization of Coupling Points

Future multimodal energy systems (MES) including heat, gas and electricity sectors will be equipped with control systems, which have some degree of autonomy, and are adaptive to their environment. Smart control systems are able to communicate with other systems and other autonomous controllers. The resulting systems can be analyzed as a complex adaptive system (CAS), which has been successfully investigated using agent based modeling (ABM) in the past. In this study, the operational behavior of a MES using different agent parametrizations for coupling points is investigated. These properties can be categorized as fast-acting agents and slow-acting as well agents with and without dead-band and saturation. The result of every scenario points out the temporal evolution of pressure in gas, temperature in heat and voltage in electricity sectors. The bottom-up perspective allocates agents’ parametrizations to the whole system behavior. The study shows the effect of dead-band, saturation and the gain of coupling points controller on the MES. In addition, the role of observers in analyzing systems in CAS paradigm is discussed. The results pave the way for setting up proper agents’ parameters and designing proper observers.

Modeling framework for planning and operation of multi-modal energy systems in the case of Germany

In order to reach the goals of the United Nations Framework Convention on Climate Change, a stepwise reduction of energy related greenhouse gas emissions as well as an increase in the share of renewable energies is necessary. For a successful realization of these changes in energy supply, an integrated view of multiple energy sectors is necessary. The coupling of different energy sectors is seen as an option to achieve the climate goals in a cost-effective way. In this paper, a methodical approach for multi-modal energy system planning and technology impact evaluation is presented. A key feature of the model is a coupled consideration of the sectors electricity, heat, fuel and mobility. The modeling framework enables system planners to optimally plan future investments in a detailed transition pathway of the energy system of a country, considering politically defined climate goals. Based on these calculations, in-depth analyses of energy markets as well as electrical transmission and distribution grids can be performed using the presented optimization models. Energy demands, conversion and storage technologies in households, the Commerce, Trade and Services (CTS) area and the industry are modeled employing a bottom-up modeling approach. The results for the optimal planning of the German energy system until 2050 show that the combination of an increased share of renewable energies and the direct electrification of heat and mobility sectors together with the use of synthetic fuels are the main drivers to achieve the climate goals in a cost-efficient way.

Integrated Planning and Evaluation of Multi-Modal Energy Systems for Decarbonization of Germany

For a successful realization of the energy transition and a reduction of greenhouse gas emissions, an integrated view of multiple energy sectors (electricity, heat and mobility) is necessary. The coupling of different energy sectors is seen as an option to achieve the climate goals in a cost-effective way. In this paper, a methodical approach for multi-modal energy system planning and technology impact evaluation is presented. A key feature of the model is a coupled consideration of sectors electricity, heat and mobility. Energy demands, conversion and storage technologies in households, the Commerce, Trade and Services (CTS) area and the industry are modelled employing a bottom-up modelling approach. The model can be used for the calculation of a detailed transition pathway of energy systems taking into account politically defined climate goals. Based on these calculations, in-depth analyses of energy markets as well as transmission and distribution grids can be performed.

Analyzing controller conflicts in multimodal smart grids - framework design

In future energy systems dominated by distributed energy resources, additional flexibility potential will be unlocked by interlinking the infrastructures of different energy systems. Direct and indirect coupling of different energy systems like power grids, gas and heat infrastructures leads to multimodal energy systems. Combined with an ongoing pervasion of the resulting interconnected system with information and communication technology (ICT), multimodal smart grids evolve. The pervasion of the system with autonomous controllers leads on to the development of a distributed adaptive system. From an engineering perspective, it shows the desired characteristics regarding scalability and self-stabilization. Unlike these desired aspects, other effects can emerge from the distributed and adaptive nature of this system: Autonomous controllers might counteract, thus leading to instable system states. From the perspective of distributed systems research, these controller conflicts can thus be understood as unintended effects of emergence. In this short paper, we present design decision for a framework that will be developed for the evaluation of controller conflicts in multimodal smart grids. The concept of technical emergence will be applied to deterministically simulate controller conflicts generated by autonomous controllers of interlinked infrastructures.

Towards integrated multi-modal municipal energy systems: An actor-oriented optimization approach

Against the backdrop of a changing political, economic and ecological environment, energy utilities are facing several challenges in many countries. Due to an increasing decentralization of energy systems, the conventional business could be undermined. Yet the reliable integration of small-scale renewable technologies and associated system transformations could represent an opportunity as well. Municipal energy utilities might play a decisive role regarding successful transition. For better decision-making, they need to investigate under which conditions certain novel business cases can become a sustainable part of their future strategy. The development of the strategy is a challenging task which needs to consider different conditions as business portfolio, the customer base, the regulatory framework as well as the market environment. Integrated Multi-Modal Energy System (IMMES) models are able to capture necessary interactions. This research introduces a model-driven decision support system called Integrated Resource Planning and Optimization (IRPopt). Major aim is to provide managerial guidance by simulating the impact of business models considering various market actors. The mixed-integer linear programming approach exhibits a novel formal interface between supply and demand side which merges technical and commercial aspects. This is achieved by explicit modeling of municipal market actors on one layer and state-of-the-art technology components on another layer as well as resource flow relations and service agreements mechanism among and between the different layers. While this optimization framework provides a dynamic and flexible policy-oriented, technology-based and actor-related assessment of multi-sectoral business cases, the encapsulation in a generic software system supports the facilitation. Based on the actor-oriented dispatch strategy, flexibility potential of community energy storage systems is provided to demonstrate a real application.

Project-level multi-modal energy system design - Novel approach for considering detailed component models and example case study for airports

The current situation, which is driven by environmental concerns and increased air traffic, forces airport operators to examine their energy systems in an integrated approach. In order to optimize total expenditures, demands of energy in all forms must be considered. This paper introduces a novel method for the optimal design of multi-modal energy systems, which will be put to further use in the European Union Horizon 2020 MODER project. The optimization problem was formulated as mixed-integer linear programming based on a superstructure approach, including all feasible state-of-the-art technologies. Part-load efficiencies as well as the influence of ambient conditions on available output capacities were considered. The model took into account several types of energy storages, i.e., electrochemical, thermal and water storages. For fifteen locations, the optimal set of technologies, their capacity and operation was identified. Results showed that for this load range, combined heat and power plants were economically very attractive. Furthermore, photovoltaic energy was a viable option, even without designated feed-in tariff. Last but not least, compression chillers with chilled water storages offered an attractive option for enhanced flexibility. Combined total cost savings by using both the described method and on-site generation of up to 61% were achieved.