LC compensators based on transmission loss minimization for nonlinear loads

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. Copyright @ 2004 IEEEThis paper presents a method employing the penalty function search algorithm to determine the LC compensator value for the optimal power factor correction in nonsinusoidal systems. The objective of the proposed method is to minimize the transmission loss while the power factor and efficiency are taken as constraints and utilized in order to solve the multiobjective optimization problem by transforming it into a single objective one. Examples show that the load nonlinearity can have a significant impact on optimal compensator sizes

The role of smart sensor networks for voltage monitoring in smart grids

The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In a Smart Grid platform, distributed voltage monitoring is one of the main issues to address. In this field, the application of traditional hierarchical monitoring paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of Distribution Generation Systems (DGS) require more scalable, more flexible control and regulation paradigms. To try to overcome these challenges, this paper proposes the concept of a decentralized non-hierarchal voltage monitoring architecture based on intelligent and cooperative smart entities. These devices employ traditional sensors to acquire local bus variables and mutually coupled oscillators to assess the main variables describing the global grid state

A filter design approach to maximize ampacity of cables in nonsinusoidal power systems

This paper presents an optimal design of the C-type passive filters for the effective utilization of the power cables under nonsinusoidal conditions based on maximization of the harmonic derating factor (HDF) of a power cable, where maintaining the load true power factor at an acceptable range is desired. According to IEEE Standard 519, the total harmonic distortions of the voltage and current measured at the point of common coupling are taken into account as main constraints of the proposed approach. The presented numerical results show that the proposed approach provides higher current carrying capacity, or ampacity of the cables under nonsinusoidal conditions when compared to the traditional approaches based on minimization of the current total harmonic distortion and maximization of the true load power factor. A numerical case study is presented to demonstrate the proposed approach

Computational Intelligence Applications in Smart Grids: Enabling Methodologies for Proactive and Self Organizing Power Systems

This book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids. From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response). In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility

Effect of connecting shunt capacitor on nonlinear load terminals

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. Copyright @ 2003 IEEEThe use of terminal shunt capacitance has different effects on the displacement factor and distortion factor components of the power factor. These effects are considered for nonlinear loads with ideal supply, and also where the supply impedance exists but is small compared with the load impedance. Optimization of the displacement factor is found to result in reduction of the distortion factor to a minimum value

A reliability based model for generation and transmission expansion planning

This paper presents a mixed integer linear multi-objective model based on information gap decision theory (IGDT), which is used to solve coordinated multiyear generation and transmission expansion planning (G&TEP) problems. The model maximizes the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission, and fuel availability are considered. A multi-objective method called the ε-constraint method is used here to maximize the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24 bus IEEE test system. The numerical results show the good performance of the model

Comparison between the Conventional Methods and PSO Based MPPT Algorithm for Photovoltaic Systems

Since the output characteristics of Photovoltaic (PV) system depends on the ambient temperature, solar radiation and load impedance, its maximum Power Point (MPP) is not constant. Under each condition PV module has a point at which it can produce its MPP. Therefore, a Maximum Power Point Tracking (MPPT) method is needed to uphold the PV panel operating at its MPP. This paper presents comparative study between the conventional MPPT methods used in (PV) system: Perturb and Observe (P&O), Incremental Conductance (IncCond), and Particle Swarm Optimization (PSO) algorithm for (MPPT) of (PV) system. To evaluate the study, the proposed PSO MPPT is implemented on a DC-DC converter and has been compared with P&O and INcond methods in terms of their tracking speed, accuracy and performance by using the Matlab tool Simulink. The simulation result shows that the proposed algorithm is simple, and is superior to the P&O and IncCond methods

Electrical performance study of a large area multicrystalline silicon solar cell using a current shunt and a micropotentiometer

In this paper, a new technique using a Current Shunt and a Micropotentiometer has been used to study the electrical performance of a large area multicrystalline silicon solar cell at outdoor conditions. The electrical performance is mainly described by measuring both cell short circuit current and open circuit voltage. The measurements of this cell by using multimeters suffer from some problems because the cell has high current intensity with low output voltage. So, the solar cell short circuit current values are obtained by measuring the voltage developed across a known resistance Current Shunt. Samples of the obtained current values are accurately calibrated by using a Micropotentiometer (μpot) thermal element (TE) to validate this new measuring technique. Moreover, the solar cell open circuit voltage has been measured. Besides, the cell output power has been calculated and can be correlated with the measured incident radiation

A goal programming methodology for multiobjective optimization of distributed energy hubs operation

This paper addresses the problem of optimal energy flow management in multicarrier energy networks in the presence of interconnected energy hubs. The overall problem is here formalized by a nonlinear constrained multiobjective optimization problem and solved by a goal attainment based methodology. The application of this solution approach allows the analyst to identify the optimal operation state of the distributed energy hubs which ensures an effective and reliable operation of the multicarrier energy network in spite of large variations of load demands and energy prices. Simulation results obtained on the 30 bus IEEE test network are presented and discussed in order to demonstrate the significance and the validity of the proposed method