The significant growth of gas-fired power plants and emerging power-to-gas (PtG) technology has intensified the interdependency between electricity natural gas systems. This paper proposes a robust co-optimization scheduling model to study coordinated optimal operation two energy proposed minimizes total costs systems, while considering system key uncertainties dynamics. Because limitation on exchanging private data challenge in managing complex models, is tackled via alternating direction...

In the production environment, a large part of microservice failures are related to complex and dynamic interactions runtime environments, such as those multiple instances, environmental configurations, asynchronous microservices. Due complexity dynamism these failures, it is often hard reproduce diagnose them in testing environments. It desirable yet still challenging that can be detected faults located at environment allow developers resolve efficiently. To address this challenge, paper,...

As the sharp growth of gas-fired power plants and new emergence power-to-gas (PtG) technology intensify interdependence between electricity natural gas systems, it is imperative to co-optimize two systems for improving overall efficiency. This paper presents a long-term robust co-optimization planning model interdependent minimizing total investment operation costs. Beside generators, transmission lines, suppliers, pipelines, PtGs compressor stations are also considered as candidates...

Recent revolution of the electricity distribution sector, especially a deeper penetration gas-fired distributed generations (DGs), intensifies interdependence on natural gas systems. Such integrated and systems (IENDS) are facing with significant threats from frequent disasters that cause enormous economic losses. Network hardening is regarded as an effective technique for enhancing resilience IENDSs against disasters. This paper presents trilevel robust optimization-based network model...

This paper proposes a distributionally robust scheduling model for the integrated gas-electricity system (IGES) with electricity and gas load uncertainties, further studies impact of demand response (DR) on energy market clearing, as well locational marginal prices (LMEPs LMGPs). The proposed maximizes base-case social welfare (i.e., revenue from price-sensitive DR loads minus production cost) worst-case expected shedding cost. Price-based DRs are formulated via bidding curves while...

The increasing interdependency of electricity and natural gas systems promotes coordination the two for ensuring operational security economics. This paper proposes a robust day-ahead scheduling model optimal coordinated operation integrated energy while considering key uncertainties power system cost. Energy hub, with collocated gas-fired units, power-to-gas (PtG) facilities, storages, is considered to store or convert one type (i.e., gas) into other form, which could analogously function...

Availability issues of industrial microservice systems (e.g., drop successfully placed orders and processed transactions) directly affect the running business. These are usually caused by various types service anomalies which propagate along dependencies. Accurate high-efficient root cause localization is thus a critical challenge for large-scale systems. Existing approaches use dependency graph based analysis techniques to automatically locate causes. However, these limited due their...

An energy deviation settlement (EDS) mechanism has been proposed to settle the between consumption and contracts in China's forward electricity market. Due high EDS costs of retailers, a mutual insurance (DMI) is put forward, representing an option for retailers reduce through contract transfer. Given this background, optimal alliance strategy maximize utility different types individual retailers. The income model considers cost reduction cooperation analyzed based on transaction theory...

Renewable energy has gradually increased its investment and penetration due to technology innovation cost reduction, turning power system expansion planning problem (SEP) into a complex task. Under this circumstance, paper presents long-term distributionally robust optimization (DRO) based model for systems, which minimizes the total operation costs along with expected penalty of load shedding wind curtailment, while considering uncertainties from data-driven ambiguity set. Besides...

The rapid expansion in scale of power systems and the emergence new smart grid technologies continuously increase computational complexity system simulations. Graphic processing unit (GPU), which features massive concurrent threads excellent floating-point performance, brings opportunities into This paper introduces an advanced GPU-CPU based parallel flow (PF) approach by adopting vectorization parallelization sparse techniques. Specifically, root cause behind sparsity property PF its...

At present, electricity transaction in China is mainly conducted by medium- and long-term market contracts, while the spot has not yet been implemented. An appropriate energy imbalance processing mechanism for power transactions highly demanded maintaining stability of operation, since it supposed to guide participants reduce system imbalances actively provide balancing services. Given this background, a bi-level optimization model developing optimal bidding strategies producer monthly...

With the increasing penetration of renewable energy, designing efficient midterm (i.e., annual) scheduling for multi-source power systems is valuable in providing substantial cost reductions and flexibilities while ensuring system security against uncertainties renewables. This paper presents a risk-averse two-stage stochastic model thermal-hydro-wind short-term generation. A network-constrained clustered unit commitment (NC-CUC) proposed to effectively incorporate operation constraints into...

This paper proposes a distributionally robust chance-constrained (DRCC) model for the clustered generation expansion planning (CGEP) of power systems. The proposed two-stage minimizes first-stage total cost along with second-stage expected penalty worst-case probability distribution renewable energy generation. A unit commitment flexibility constraints is embedded into model, and uncertainty modeled via Wasserstein distance (WD)-based ambiguity set. Demand-side resources (DSR) concentrating...

Migration is the most important seismic data processing method that recovers subsurface images of Earth's interior using surface-recorded volumes obtained from reflection surveys. A reconfigurable coprocessor platform called SPACE (seismic accelerator with engine) field programmable gate array (FPGA) technology proposed in this paper to speed up these computationally demanding and data-intensive migration applications. The characterized by its simple architecture abundant on-board memory...

Before the establishment of spot electricity market in China, an energy imbalance settlement (EIS) mechanism has been proposed as a transitional solution to address imbalances between actual consumption and contracted forward market. It plays crucial role cultivating retailers, maintaining stability balancing account, promoting smooth transition market-oriented reforms. Given this background, novel EIS with piecewise linear penalty pricing scheme is proposed, learning from performance-based...

This paper proposes a data-driven adjustable robust unit commitment (UC) model for integrated electric-heat systems (IEHSs), where the data-driven, and robustness features are endowed by novel uncertainty modeling method. The devised set is intersections of series hyperplanes. It combines merits traditional box-like set, whose underlying computation burden moderate, convex hull formed historical data, which would lead to less conservative operation strategies. boundaries bounding...

As the penetration of renewable energy continues to grow, power system expansion planning needs new techniques balance cost achieve high targets while maintaining a certain level flexibility and reliability in presence uncertainties. Firstly, this paper presents long-term stochastic co-optimization model, for minimizing total investment operation cost. A linearized AC flow model which could accurately retain bus voltages, reactive network losses is implemented better accommodate generation....