The problem of distributing gas through a network of pipelines is formulated as a cost minimization subject to nonlinear flow-pressure relations, material balances, and pressure bounds. The solution method is based on piecewise linear approximations of the nonlinear flow-pressure relations. The approximated problem is solved by an extension of the Simplex method. The solution method is tested on real-world data and compared with alternative solution methods.

The gas transmission problem solved by an extension of the simplex algorithm

Mobile power sources (MPSs), including electric vehicle fleets, truck-mounted mobile energy storage systems, and mobile emergency generators, have great potential to enhance distribution system (DS) resilience against extreme weather events. However, their dispatch is not well investigated. This paper implements resilient routing and scheduling of MPSs via a two-stage framework. In the first stage, i.e., before the event, MPSs are pre-positioned in the DS to enable rapid pre-restoration, in order to enhance survivability of the electricity supply to critical loads. DS network is also proactively reconfigured into a less impacted or stressed state. A two-stage robust optimization model is constructed and solved by the column-and-constraint generation algorithm to derive first-stage decisions. In the second stage, i.e., after the event, MPSs are dynamically dispatched in the DS to coordinate with conventional restoration efforts, so as to enhance system recovery. A novel mixed-integer programming model that resolves different timescales of MPS dispatch and DS operation, coupling of road and power networks, etc., is formulated to optimize dynamic dispatch of MPSs. Case studies conducted on IEEE 33-node and 123-node test systems demonstrate the proposed method’s effectiveness in routing and scheduling MPSs for DS resilience enhancement.

Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement

The frequency of extreme events (e.g., hurricanes, earthquakes, and floods) and man-made attacks (cyber and physical attacks) has increased dramatically in recent years. These events have severely impacted power systems ranging from long outage times to major equipment (e.g., substations, transmission lines, and power plants) destructions. This calls for developing control and operation methods and planning strategies to improve grid resilience against such events. The first step toward this goal is to develop resilience metrics and evaluation methods to compare planning and operation alternatives and to provide techno-economic justifications for resilience enhancement. Although several power system resilience definitions, metrics, and evaluation methods have been proposed in the literature, they have not been universally accepted or standardized. This paper provides a comprehensive and critical review of current practices of power system resilience metrics and evaluation methods and discusses future directions and recommendations to contribute to the development of universally accepted and standardized definitions, metrics, evaluation methods, and enhancement strategies. This paper thoroughly examines the consensus on the power system resilience concept provided by different organizations and scholars and existing and currently practiced resilience enhancement methods. Research gaps, associated challenges, and potential solutions to existing limitations are also provided.

/pdf/power-system-resilience-current-practices-challenges-and-3p0fxnyf6d.pdf

Power System Resilience: Current Practices, Challenges, and Future Directions

Mobile energy storage systems (MESSs) provide promising solutions to enhance distribution system resilience in terms of mobility and flexibility. This paper proposes a rolling integrated service restoration strategy to minimize the total system cost by coordinating the scheduling of MESS fleets, resource dispatching of microgrids, and network reconfiguration of distribution systems. The integrated strategy takes into account damage and repair to both the roads in transportation networks and the branches in distribution systems. The uncertainties in load consumption and the status of roads and branches are modeled as scenario trees using Monte Carlo simulation method. The operation strategy of MESSs is modeled by a stochastic multi-layer time-space network technique. A rolling optimization framework is adopted to dynamically update system damage, and the coordinated scheduling at each time interval over the prediction horizon is formulated as a two-stage stochastic mixed-integer linear program with temporal–spatial and operation constraints. The proposed model is verified on two integrated test systems, one is with Sioux Falls transportation network and four 33-bus distribution systems, and the other is the Singapore transportation network-based test system connecting six 33-bus distribution systems. The results demonstrate the effectiveness of MESS mobility to enhance distribution system resilience due to the coordination of mobile and stationary resources.

Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration

The reliability evaluation of integrated power-gas systems (IPGS) becomes critical due to the high dependency of the two energy systems. Once a contingent incident happens in one system, the other system will accordingly be affected. In this paper, a detailed model for the IPGS is presented with the consideration of the power-to-gas devices and gas storages. Furthermore, a sequential Monte Carlo (SMC) simulation is utilized to evaluate the reliability of the IPGS. In particular, the gas storage life reliability model is considered to characterize the charging and discharging performance. Moreover, an optimal load shedding model is used to coordinate the load shedding of the IPGS. What's more, new reliability indices are given to display the reliability of the IPGS. Finally, the proposed model is tested on an integrated IEEE 24-bus power system and 20-node gas system and an integrated IEEE RTS 96 power system and 40-node gas system. The results show the effectiveness of the proposed model.

Reliability Evaluation for Integrated Power-Gas Systems With Power-to-Gas and Gas Storages

Transportable energy storage systems (TESSs) have great potential to enhance resilience of distribution systems (DSs) against large area blackouts. A joint post-disaster restoration scheme for TESS and generation scheduling in microgrids (MGs) and network reconfigurations is proposed to minimize the total system cost, including customer interruption cost, generation cost, and TESS related costs. A temporal–spatial TESS model which is related to both transportation networks and DSs is proposed to represent the difference between TESS and ESS in terms of flexibility and cost reduction of ESS sharing among MGs. The proposed restoration problem is formulated as a mixed-integer linear programming with considering various network and TESS constraints. The proposed model and scheme are tested in a modified 33-bus test system with three MGs and four TESSs. The results verify that a distribution system with TESS is more resilient compared with conventional ESS because of the benefit from total cost reduction.

https://dr.ntu.edu.sg/bitstream/10356/89545/2/Transportable%20Energy%20Storage%20for%20More%20Resilient%20Distribution%20Systems%20With%20Multiple%20Microgrids.pdf

Transportable Energy Storage for More Resilient Distribution Systems With Multiple Microgrids

To realize high efficient energy conversion among multiple energy carriers in market environment, the hybrid ac/dc microgrid is embedded as the electrical hub for energy hubs (EHs), and a stochastic day-ahead bidding strategy is proposed for the energy hub operators (EHOs). The electricity, heating, and cooling are managed to balance the operational cost and thermal service quality, while participating into the day-ahead market and real-time market. The uncertainties of prices, electrical loads, and ambient temperature are depicted by scenario trees, and are managed by a two-stage stochastic optimization scheme to minimize the expected and conditional value at the risk of operational cost. This stochastic optimization problem is reformulated to a linear programming (LP) problem under given conditions. In addition, a chance constraint is proposed to relax the quality of thermal services, and a two-stage chance constrained stochastic programming is formulated accordingly. It is further reformulated to a mixed integer LP problem. Simulations have been carried out on an EH with multiple types of energy generation, conversion, and storage systems. Results have verified the effectiveness of the proposed method, providing efficient bidding curves to the EHO through the stochastic management. Sensitive analysis shows that the proposed strategy can balance the operational cost and service quality via the adjustment of chance constraints.

Strategic Bidding of Hybrid AC/DC Microgrid Embedded Energy Hubs: A Two-Stage Chance Constrained Stochastic Programming Approach

Battery swapping-charging system (BSCS) is a promising solution to provide better battery swapping service to electric vehicles. To achieve the optimal operation of BSCSs, a closed-loop supply chain-based BSCS model is proposed to realize the combined operation of battery charging stations and battery swapping stations (BSSs) while the quality of battery swapping service at BSSs is ensured with a network calculus-based service model. The battery logistics within the BSCS is modeled based on a time-space network (TSN) technique. The charging and the logistics of depleted batteries and well-charged batteries are optimally managed to maximize the revenue of the BSCS. The optimization problem is formulated as a mixed-integer linear programming model with various TSN and operation constraints. Random-permuted alternating direction method of multipliers is applied as a heuristic to solve the problem in a distributed way. Simulation results verify the feasibility of the proposed model and the heuristic solution with small optimality losses and less computation time.

Distributed Operation Management of Battery Swapping-Charging Systems

Mobile energy storage systems (MESSs) provide promising solutions to enhance distribution system resilience in terms of mobility and flexibility. This paper proposes a rolling integrated service restoration strategy to minimize the total system cost by coordinating the scheduling of MESS fleets, resource dispatching of microgrids and network reconfiguration of distribution systems. The integrated strategy takes into account damage and repair to both the roads in transportation networks and the branches in distribution systems. The uncertainties in load consumption and the status of roads and branches are modeled as scenario trees using Monte Carlo simulation method. The operation strategy of MESSs is modeled by a stochastic multi-layer time-space network technique. A rolling optimization framework is adopted to dynamically update system damage, and the coordinated scheduling at each time interval over the prediction horizon is formulated as a two-stage stochastic mixed-integer linear program with temporal-spatial and operation constraints. The proposed model is verified on two integrated test systems, one is with Sioux Falls transportation network and four 33-bus distribution systems, and the other is the Singapore transportation network-based test system connecting six 33-bus distribution systems. The results demonstrate the effectiveness of MESS mobility to enhance distribution system resilience due to the coordination of mobile and stationary resources.

Shuhan Yao

Papers

Transportable Energy Storage for More Resilient Distribution Systems With Multiple Microgrids

Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration

Strategic Bidding of Hybrid AC/DC Microgrid Embedded Energy Hubs: A Two-Stage Chance Constrained Stochastic Programming Approach

Distributed Operation Management of Battery Swapping-Charging Systems

Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration