1,778,405 research outputs found
rashti-alireza/Cpi: v2.5
No full textIn this release:
Improving output order.
Adding simplification flags for various situations.
Able to use FullSimplify function in Mathematica
TEP : Transmission Expansion Planning
No full textFor more details please refer to Chapter 9 (Gcode9.1), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Springer, 2017. This chapter provides a solution for some transmission network operation and planning studies in GAMS
EDsensitivity : Sensitivity Analysis in Economic Load Dispatch
No full textFor more details please refer to Chapter 3 (Gcode3.2), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Springer, 2017. This chapter provides the instruction on how to model the economic dispatch problem of different power plants. Different power plant technologies will be discussed, such as thermal power, wind turbine, CHP, and hydro power plants in GAMS
Optimal Economic dispatch of Power system
No full textFor more details please refer to Chapter 3 (Gcode3.1), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Springer, 2017. This chapter provides the instruction on how to model the economic dispatch problem of different power plants. Different power plant technologies will be discussed, such as thermal power, wind turbine, CHP, and hydro power plants in GAMS
MultiperiodDCOPF24bus : Multi-period DC-OPF for IEEE 24-bus network considering wind and load shedding
No full textFor more details please refer to Chapter 6 (Gcode6.7), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Springer, 2017. This chapter provides a solution for optimal power flow OPF problem in GAMS. Different OPF models are investigated, such as single and multi-period DC-AC optimal power flow
MOED : Multi-objective Economic-Environmental Load Dispatch
No full textFor more details please refer to Chapter 3 (Gcode3.4), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Spriner, 2017. This chapter provides the instruction on how to model the economic dispatch problem of different power plants. Different power plant technologies will be discussed, such as thermal power, wind turbine, CHP, and hydro power plants in GAMS
Low-energy standby-sparing for hard real-time systems
Get PDFTime-redundancy techniques are commonly used in real-time systems to achieve fault tolerance without incurring high energy overhead. However, reliability requirements of hard real-time systems that are used in safety-critical applications are so stringent that time-redundancy techniques are sometimes unable to achieve them. Standby sparing as a hardware redundancy technique can be used to meet high reliability requirements of safety-critical applications. However, conventional standby-sparing techniques are not suitable for low-energy hard real-time systems as they either impose considerable energy overheads or are not proper for hard timing constraints. In this paper we provide a technique to use standby sparing for hard real-time systems with limited energy budgets. The principal contribution of this work is an online energy management technique which is specifically developed for standby-sparing systems that are used in hard real-time applications. This technique operates at runtime and exploits dynamic slacks to reduce the energy consumption while guaranteeing hard deadlines. We compared the low-energy standby-sparing (LESS) system with a low-energy time redundancy system (from a previous work). The results show that for relaxed time constraints, the LESS system is more reliable and provides about 26% energy saving as compared to the time-redundancy system. For tight deadlines when the time redundancy system is not sufficiently reliable (for safety-critical application), the LESS system preserves its reliability but with about 49% more energy consumptio
PMU-cost : Min Cost PMU allocation for IEEE 14 network without considering zero injection nodes
No full textFor more details please refer to Chapter 8 (Gcode8.2), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Springer, 2017. This chapter provides a solution for increasing the power system observability by allocation of Phasor Measurement Units (PMU) problem in GAMS
MultiperiodACOPF24bus : Multi-period AC-OPF for IEEE 24-bus network considering wind and load shedding
No full textFor more details please refer to Chapter 6 (Gcode6.7), of the following book: Soroudi, Alireza. Power System Optimization Modeling in GAMS. Springer, 2017. This chapter provides a solution for optimal power flow OPF problem in GAMS. Different OPF models are investigated, such as single and multi-period DC-AC optimal power flow
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