Computational intelligence applications to crisis management in power systems

In emergency conditions, power system operators deal with large amounts of data. Due to psychological stress, operators may not be able to adequately respond to critical conditions and make correct decisions. Mistakes can damage expensive power system equipment or worse lead to major emergencies. Intelligent systems can play an advisory role suggesting the necessary actions to be taken to deal with a given emergency as well as identifying failures of protection systems and circuit breakers. This paper outlines some experience obtained at the University of Tasmania in developing intelligent systems for power systems security. An expert system for clearing overloads applies the network sensitivity factors to reschedule power generation, reconfigure networks and shed loads. An expert system for voltage control is developed for detecting voltage violations and providing a set of control actions to solve voltage problems. Neural networks are used to identify multiple failures of protection and circuit breakers

Distributed Generation Control using Protection Principles

In a distribution system, it is essential to maintain the voltage variation within a specified limit for satisfactory operation of connected customers' equipment. Normally, this goal is achieved by controlling the operation of compensating devices, such as load tap changing transformers, shunt capacitors, series capacitors, shunt reactors, and static VAr compensators. However, technical and regulatory developments are encouraging a greater number of small generator units, known as Distributed Generation (DG), and this has the potential to significantly affect voltage control systems. This paper presents an adaptive voltage control technique which incorporates DG systems into the voltage control system. The control scheme uses On-load Tap Changing Transformer (OLTC) and DG for voltage corrections, both are driven by advanced Line Drop Compensators (LDC). At the substation, the LDC is employed to control step up or step down decisions of the OLTC, while another LDC will be used at DG connection point to set DG parameters. Also, for a more cost-effective system, voltage control action coordination is proposed using magnitude grading and time grading. The control approach is tested on a modified distribution system with load variations that are stochastic in time and location. The results show that the integration of these magnitude grading and time grading, protection principles have considerably reduced the DG energy required to achieve the desired control

Sequential modular position and momentum measurements of a trapped ion mechanical oscillator

The non-commutativity of position and momentum observables is a hallmark feature of quantum physics. However this incompatibility does not extend to observables which are periodic in these base variables. Such modular-variable observables have been suggested as tools for fault-tolerant quantum computing and enhanced quantum sensing. Here we implement sequential measurements of modular variables in the oscillatory motion of a single trapped ion, using state-dependent displacements and a heralded non-destructive readout. We investigate the commutative nature of modular variable observables by demonstrating no-signaling-in-time between successive measurements, using a variety of input states. In the presence of quantum interference, which we enhance using squeezed input states, measurements of different periodicity show signaling-in-time. The sequential measurements allow us to extract two-time correlators for modular variables, which we use to violate a Leggett-Garg inequality. The experiments involve control and coherence of multi-component superpositions of up to 8 coherent, squeezed or Fock state wave-packets. Signaling-in-time as well as Leggett-Garg inequalities serve as efficient quantum witnesses which we probe here with a mechanical oscillator, a system which has a natural crossover from the quantum to the classical regime.Comment: 6 pages, 3 figures and supplemental informatio

Wideband laser locking to an atomic reference with modulation transfer spectroscopy

We demonstrate that conventional modulated spectroscopy apparatus, used for laser frequency stabilization in many atomic physics laboratories, can be enhanced to provide a wideband lock delivering deep suppression of frequency noise across the acoustic range. Using an acousto-optic modulator driven with an agile oscillator, we show that wideband frequency modulation of the pump laser in modulation transfer spectroscopy produces the unique single lock-point spectrum previously demonstrated with electro-optic phase modulation. We achieve a laser lock with 100 kHz feedback bandwidth, limited by our laser control electronics. This bandwidth is sufficient to reduce frequency noise by 30 dB across the acoustic range and narrows the imputed linewidth by a factor of five.Comment: 11 pages, 3 figures, 1 table; v2: additional laser frequency noise data demonstrating greater linewidth reduction, many textual improvements, accepted for publication in Optics Expes

Short term wind power forecasting using hybrid intelligent systems

This panel paper summarizes the current trends in wind power development and describes a proposed approach for short term wind power forecasting using a hybrid intelligent system