Mobile energy storage devices (MESDs) operate as medium- or large-sized batteries that can be loaded onto electric trucks and connected to charging stations to provide various ancillary services for distribution grids. This paper proposes a new strategy for MESD operation, in which their power outputs and paths are co-optimally scheduled to minimize the total energy loss in both power and transportation networks. The distances moved by MESDs and time at different locations are modeled using a set of linear equations, considering the time-varying traffic flow. The linear transit model is integrated with linearized constraints to support the reliable operation of the distribution grid. In particular, an optimal scheduling problem is formulated considering the maximum limits on incremental variations in bus voltages and line power flows for active and reactive power outputs of MESDs. A mixed-integer linear programming solver can be readily applied to the optimization problem, ensuring the global optimality of the solution. Simulation case studies are carried out under various power and transportation network conditions. The results of these case studies confirm that the proposed strategy using MESDs is effective in reducing total energy losses, compared to conventional methods using stationary batteries and plug-in electric vehicles.
Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks
SYSU-CMU Joint Institute of Engineering（中山大学-卡内基梅隆大学联合工程学院）；Carnegie Mellon University（卡内基梅隆大学）；School of Electronics and Information Technology, SYSU（中山大学电子与信息工程学院）；Scott Institute for Energy Innovation, Carnegie Mellon University（卡内基梅隆大学斯科特能源创新研究所）
The increasing trend of transportation electrification presents investors the opportunity to provide charging services to Electric Vehicle (EV) owners via the energy purchased from the wholesale electricity market. This will benefit EV owners with the availability of competitive rates compared to the regulated utility time-of-use (TOU) rates. The fundamental questions addressed in this paper are 1) will EV owners benefit from the additional choice of Electric Vehicle Charging Stations (EVCSs) compared to home charging? 2) is there any profitable market opportunity for charging stations while t…
Electric power network expanded rapidly in recent decades due of the excessive need of electricity in every aspect of life, including critical infrastructures such as medical services, and transportation and communication systems. Natural disasters are one of the major reasons of electricity outage. It is extremely important to restore electrical energy in the shortest time possible after a disaster. This paper proposes a decision support method for electric system operators to restore electricity to the critical loads in a distribution system after an earthquake. The proposed method employs M…
Joint Transportation and Charging Scheduling in Public Vehicle Systems - A Game Theoretic Approach
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；Department of Computer Science and Engineering, Shanghai Jiao Tong University（上海交通大学计算机科学与工程系）；Electrical Engineering Department, Columbia University（哥伦比亚大学电气工程系）；Department of Electrical Engineering, Columbia University（哥伦比亚大学电气工程系）
Deep energy decarbonization cannot be achieved without high penetration of renewables. At higher renewable energy penetrations, the variability and intermittent nature of solar photovoltaic (PV) electricity can cause ramping issues with existing fossil fuel generation, requiring longer term energy storage to increase the reliability of grid operation. A proton exchange membrane electrolyzer can produce H2and serves as a utility controllable load. The produced H2 can then be stored and converted back into electricity, or mixed with natural gas, or used as transportation fuel, or chemical feedst…
A modeling framework is presented to investigate trade-offs among decarbonization from increased low-carbon electricity generation and electrification of heating and vehicles. The model is broadly applicable but relies on high-fidelity parameterization of existing infrastructure and anticipated electrified loads; this study applies it to New York State where detailed data is available. Trade-offs are investigated between end use electrification and renewable energy deployment in terms of supply costs, generation and storage capacities, renewable resource mix, and system operation. Results indi…
Electricity storage systems (ESS) are hailed by many scholars and practitioners as a key element of the future electricity systems and a key step toward the transition to renewables . Nonetheless, the global speed of ESS implementation is relatively slow, and among possible reasons is the lack of viable business models. We developed an agent-based model to simulate the behavior of ESS within the Dutch electricity market. We adopted an exploratory modeling analysis (EMA) approach to investigate the effects of two specific business models on the value of ESS from the perspective of both investor…
Planning to support widespread transportation electrification depends on detailed estimates for the electricity demand from electric vehicles in both uncontrolled and controlled or smart charging scenarios. We present a modeling approach to rapidly generate charging estimates that include control for large-scale scenarios with millions of individual drivers. We model uncontrolled charging demand using statistical representations of real charging sessions. We model the effect of load modulation control on aggregate charging profiles with a novel machine learning approach that replaces tradition…
In the existing literatures for the risk evaluation of electricity-gas integrated energy system (EGIES), the impacts of gas leakage in pipelines are ignored. This paper presents a method to incorporate the failure modes of gas pipeline leakage in EGIES risk evaluation. A Markov state transition model of gas pipeline with multi-state and multi-mode transition process, and a bi-level Monte Carlo sampling method for this model are developed. A stochastic topology change based network model of EGIES considering the pipeline leakage failure modes is presented. The risk indices for EGIES based on th…
The high penetration of transportation electrification and its associated charging requirements magnify the interdependency of the transportation and power distribution systems. The emergent interdependency requires that system operators fully understand the status of both systems. To this end, a visualization tool is presented to illustrate the interdependency of battery bus transit and power distribution systems and the associated components. The tool aims at monitoring components from both systems, such as the locations of electric buses, the state of charge of batteries, the price of elect…
Perimeter control involves monitoring network-wide traffic and regulating traffic inflow to alleviate hypercongestion. Implementation of transit priority with perimeter control measures, which allow transit into a controlled area without queuing at the perimeter boundary, is an effective strategy in bimodal transportation systems. However, travelers' behavior changes in response to perimeter control strategies, such as shifts in their departure times and transportation modes, have not been fully investigated. Therefore, important questions remain, such as the use of transit during perimeter co…
Multi-technology co-optimization approach for sustainable hydrogen and electricity supply chains considering variability and demand scale
University of Southern California（南加州大学）；Korea Advanced Institute of Science and Technology (KAIST)（韩国科学技术院）；Korea Institute of Energy Research（韩国能源研究院）
Sector coordination between heat and electricity systems has been identified has an energy-efficient and cost-effective way to transition towards a more sustainable energy system. However, the coordination of sequential markets relies on the exchange of sensitive information between the market operators, namely time series of consumers' loads. To address the privacy concerns arising from this exchange, this paper introduces a novel privacy-preserving Stackelberg mechanism (w-PPSM) which generates differentially-private data streams with high fidelity. The proposed w-PPSM enforces the feasibili…
A key obstacle to increasing renewable energy penetration in the power grid is the lack of utility-scale storage capacity. Transportation electrification has the potential to overcome this obstacle since Electric Vehicles (EVs) that are not in transit can provide battery storage as a service to the grid. This is referred to as EV-Power grid integration, and could potentially be a key milestone in the pathway to decarbonize the electricity and the transportation sectors. We first show that if EV-Power grid integration is not done carefully, then contrary to improving the cost efficiency of oper…
Averting the effects of anthropogenic climate change requires a transition from fossil fuels to low-carbon technology. A way to achieve this is to decarbonize the electricity grid. However, further efforts must be made in other fields such as transport and heating for full decarbonization. This would reduce carbon emissions due to electricity generation, and also help to decarbonize other sources such as automotive and heating by enabling a low-carbon alternative. Carbon taxes have been shown to be an efficient way to aid in this transition. In this paper, we demonstrate how to to find optimal…
The new technologies emerging in the energy sector pose new requirements for both the regulation and operation of the electricity grid. Revised tariff structures and the introduction of local markets are two approaches that could tackle the issues resulting from the increasing number of active end-users. However, a smooth transition from the traditional schemes is critical, thus creating the need for architecture that can be implemented in the current circumstances. This paper proposes a local market concept and a corresponding dynamic tariff system, which can be operated parallel to the curre…
The transition to renewable energy systems causes increased decentralization of the energy supply. Solar parks are built to increase renewable energy penetration and to supply local communities that become increasingly self-sufficient. These parks are generally installed in rural areas where electricity grid distribution capacity is limited. This causes the produced energy to create grid congestion. Temporary storage can be a solution. In addition to batteries, which are most suitable for intraday storage, hydrogen provides a long-term storage option and can be used to overcome seasonal mismat…
RWTH Aachen University（亚琛工业大学）；University of Applied Sciences Duesseldorf（杜塞尔多夫应用技术大学）
Assessing the effects of the energy transition and liberalization of energy markets on resource adequacy is an increasingly important and demanding task. The rising complexity in energy systems requires adequate methods for energy system modeling leading to increased computational requirements. Furthermore, with complexity, uncertainty increases likewise calling for probabilistic assessments and scenario analyses. To adequately and efficiently address these various requirements, new methods from the field of data science are needed to accelerate current methods. With our systematic literature …
Texas A&M University（德克萨斯农工大学）；San Diego State University（圣地亚哥州立大学）；University of Southern California（南加州大学）；Princeton University（普林斯顿大学）；DeepMind（深度思维）；Arizona State University（亚利桑那州立大学）；Stanford University（斯坦福大学）
The transition towards carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation. The transition to a carbon-neutral electric grid poses significant challenges to conventional paradigms of modern grid planning and operation. Much of the challenge arises from the scale of the decision making and the uncertainty associated with the energy supply and demand. Artificial Intelligence (AI) could potentially have a transformativ…
Envisioning a future 100% electrified transportation sector, this paper uses socio-economic, demographic, and geographic data to assess electric energy demand from commuter traffic. We explore the individual mode choices, which allows to create mode-mix scenarios for the entire population, and quantify the electric energy demand for each scenario using technical specifications of battery and electric drives technology in combination with different charging scenarios. Using data sets for New York City, our results highlight the need for infrastructure investments, the usefulness of flexible cha…
We propose a new forward electricity market framework that admits heterogeneous market participants with second-order cone strategy sets, who accurately express the nonlinearities in their costs and constraints through conic bids, and a network operator facing conic operational constraints. In contrast to the prevalent linear-programming-based electricity markets, we highlight how the inclusion of second-order cone constraints improves uncertainty-, asset- and network-awareness of the market, which is key to the successful transition towards an electricity system based on weather-dependent ren…
Strategizing Equitable Transit Evacuations: A Data-Driven Reinforcement Learning Approach
School of Sustainable Engineering and the Built Environment, Arizona State University（亚利桑那州立大学可持续工程与建筑环境学院）；University of California, Berkeley（加州大学伯克利分校）
