14,643 research outputs found
A Heuristic Based Multi-Objective Approach for Network Reconfiguration of Distribution Systems
This paper presents an algorithm for network reconfiguration based on the heuristic rules and fuzzy multi-objective approach with an improved Fast Decoupled load flow algorithm. Multiple objectives are considered to minimize the real power loss, deviation in bus voltages, branch current violation and for load balancing among feeders, while subjected to a radial network structure in which all loads kept energized. These four objectives are modeled with fuzzy sets to evaluate their imprecise nature. Heuristic rules are also incorporated in the algorithm for drastically minimizing the number of tie-switch operations. An improved Fast Decoupled load flow algorithm with Single Matrix Model (FDC-SMM) has been proposed for distribution networks. The proposed algorithm is very effective in dealing with reconfiguration problems of single and multi-feeder networks Keywords: Multi-objective approach, Reconfiguration, Fuzzy set theory, Fast decoupled load flo
An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers
In energy systems with high shares of weather-driven renewable power sources,
gas-fired power plants can serve as a back-up technology to ensure security of
supply and provide short-term flexibility. Therefore, a tighter coordination
between electricity and natural gas networks is foreseen. In this work, we
examine different levels of coordination in terms of system integration and
time coupling of trading floors. We propose an integrated operational model for
electricity and natural gas systems under uncertain power supply by applying
two-stage stochastic programming. This formulation co-optimizes day-ahead and
real-time dispatch of both energy systems and aims at minimizing the total
expected cost. Additionally, two deterministic models, one of an integrated
energy system and one that treats the two systems independently, are presented.
We utilize a formulation that considers the linepack of the natural gas system,
while it results in a tractable mixed-integer linear programming (MILP) model.
Our analysis demonstrates the effectiveness of the proposed model in
accommodating high shares of renewables and the importance of proper natural
gas system modeling in short-term operations to reveal valuable flexibility of
the natural gas system. Moreover, we identify the coordination parameters
between the two markets and show their impact on the system's operation and
dispatch
Preparing HPC Applications for the Exascale Era: A Decoupling Strategy
Production-quality parallel applications are often a mixture of diverse
operations, such as computation- and communication-intensive, regular and
irregular, tightly coupled and loosely linked operations. In conventional
construction of parallel applications, each process performs all the
operations, which might result inefficient and seriously limit scalability,
especially at large scale. We propose a decoupling strategy to improve the
scalability of applications running on large-scale systems.
Our strategy separates application operations onto groups of processes and
enables a dataflow processing paradigm among the groups. This mechanism is
effective in reducing the impact of load imbalance and increases the parallel
efficiency by pipelining multiple operations. We provide a proof-of-concept
implementation using MPI, the de-facto programming system on current
supercomputers. We demonstrate the effectiveness of this strategy by decoupling
the reduce, particle communication, halo exchange and I/O operations in a set
of scientific and data-analytics applications. A performance evaluation on
8,192 processes of a Cray XC40 supercomputer shows that the proposed approach
can achieve up to 4x performance improvement.Comment: The 46th International Conference on Parallel Processing (ICPP-2017
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