This paper addresses the problems associated with power management of the grid containing renewable power systems and proposes a method for enhancing its operational power management. Since renewable energy provides uncertain and uncontrollable energy resources, the renewable power systems can only generate irregular power. This power irregularity creates problems affecting the grid power management process and influencing the parallel operations of conventional power plants on the grid. To demonstrate this power management method for this type of grid, weatherdependent wind and photovoltaic power systems are chosen an example. This study also deals with other uncertain quantities which are system loads. In this example, the management method is based on adapting short-term weather and load forecasting data. The new load demand curve (NLDC) can be produced by merging the loads with the power generated from the renewable power systems. The NLDC is used for setting the loads for the baseload power plants and knowing when other plants are needed to increase or decrease their supplies to the grid. This will decrease the irregularity behavior effects of the renewable power system and at the same time will enhance the smoothing of the power management for the grid. The aim of this paper is to show the use of the weather and load forecasting data to achieve the optimum operational power management of the grid contains renewable power systems. An illustrative example of such a power system is presented and verified by simulation.
This paper presents a new methodology for eliminating the influence of the power fluctuations of the renewable power systems. The renewable energy, which is to be considered an uncertain and uncontrollable resource, can only provide irregular electrical power to the power grid. This irregularity creates fluctuations of the generated power from the renewable power systems. These fluctuations cause instability to the power system and influence the operation of conventional power plants. Overall, the power system is vulnerable to collapse if necessary actions are not taken to reduce the impact of these fluctuations. This methodology aims at reducing these fluctuations and makes the generated power capability for covering the power consumption. This requires a prediction tool for estimating the generated power in advance to provide the range and the time of occurrence of the fluctuations. Since most of the renewable energies are weather based, as a result a weather forecast technique will be used for predicting the generated power. The reduction of the fluctuation also requires stabilizing facilities to maintain the output power at a desired level. In this study, a wind farm and a photovoltaic array as renewable power systems and a pumped-storage and batteries as stabilizing facilities are used, since they are best suitable for compensating the fluctuations of these types of power suppliers. As an illustrative example, a model of wind and photovoltaic power systems with battery energy and pumped hydro storage facilities for power fluctuation reduction is included, and its power fluctuation reduction is verified through simulation.
This paper consists of four parts: (1) The word-level representations of digital circuits which included (a) word-level arithmetic representation, (b) word-level sum-of-products representation, and (c) word-level Reed-Muller representation. (2) The three word-level nano ICs circuit designs. (3) The introduction of the vector Boolean derivative. (4) The fault detection in word-level digital circuits using the vector Boolean derivative. The formulas for deriving tests for detecting stuck-at-0 (s-a-0) and stuck-at-1(s-a-1) are given word-level digital circuit presented in in any of the three representations.
One of the promising emerging nanotechnologies is the molecular quantum-dot cellular automata (QCA). A considerable amount of attention has been given to the 2D 2-dot QCA circuit designs and simulations at the bit level by Hook and Lee. The purpose of this paper is two-fold: (1) to introduce a new 3D QCA lattice structure, formed by 2-dot QCA cells, and (2) to present a word-level QCA NanoIC design method using this 3D 2-dot QCA architecture, which uses a slice of the lattice to implement one bit of the word data. For example, for an 8-bit word, there will be 8 slices of 2-dot QCA lattice embedded in the NanoIC.