This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model.

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Online Short-term Solar Power Forecasting

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to process static, simple optimization problem. Modification PSO is developed for solving the basic PSO problem. The observation and review 46 related studies in the period between 2002 and 2010 focusing on function of PSO, advantages and disadvantages of PSO, the basic variant of PSO, Modification of PSO and applications that have implemented using PSO. The application can show which one the modified or variant PSO that haven’t been made and which one the modified or variant PSO that will be developed.

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Particle Swarm Optimization: Technique, System and Challenges

https://vbn.aau.dk/ws/files/206009396/Correction.pdf

Practical operation strategies for pumped hydroelectric energy storage (PHES) utilising electricity price arbitrage

Phasor measurement units (PMUs) are rapidly being deployed in electric power networks across the globe. Wide-area measurement system (WAMS), which builds upon PMUs and fast communication links, is consequently emerging as an advanced monitoring and control infrastructure. Rapid adaptation of such devices and technologies has led the researchers to investigate multitude of challenges and pursue opportunities in synchrophasor measurement technology, PMU structural design, PMU placement, miscellaneous applications of PMU from local perspectives, and various WAMS functionalities from the system perspective. Relevant research articles appeared in the IEEE and IET publications from 1983 through 2014 are rigorously surveyed in this paper to represent a panorama of research progress lines. This bibliography will aid academic researchers and practicing engineers in adopting appropriate topics and will stimulate utilities toward development and implementation of software packages.

Synchrophasor Measurement Technology in Power Systems: Panorama and State-of-the-Art

Experimental validation of a real time energy management system for microgrids in islanded mode using a local day-ahead electricity market and MINLP

Indian power industry is undergoing deregulation at a rapid rate. In this transition phase, it is now essential to design the most appropriate market and suitable pricing schemes for the power sector. In this article, a restructured electricity market model for future Indian power market is explained which is based on the institutional frame work – The Indian Electricity Act 2003. The activities of the three-tier market model and the entities involved in the power trading are discussed. Inter-regional and intra-regional congestion management scheme that provide comparable access to all users of the transmission system is proposed. Method for estimation of transmission charges to wheel electrical energy through transmission utilities is also proposed. The method is tested with a five region eleven zone Indian power system model and the results are illustrated.

Market operations in future Indian restructured power system scenario

The fault ride through capability and fast controller action makes doubly fed induction generator based wind energy conversion system to actively participate in power oscillation damping. This arti...

Coordinated reactive power and crow bar control for DFIG-based wind turbines for power oscillation damping:

Fault detection in novel distribution systems has been a big challenge with increasing distributed generation. Addition of non-linear devices has increased the rate of fault occurrence and thus a need to identify and rectify the fault with in a short interval. Inclusion of smart devices such as smart meters and PMU(s) can help a lot in reducing the fault detection time. Since most of the fault detection algorithms use iteration and a number of assumptions of the network topology, often the difference between the calculated fault distance and the real fault distance is huge. In the case of micro grid a single fault can result in more than one fault directions. Using petri nets can be of great use for fault detection as it has some major advantages. Petri nets don't use iterations and can precisely narrow down the fault depending upon the input data. A distribution network has been taken and simulated for both single and multiple fault instance. The algorithm was found to be simple and efficient. It can take information from protection device too which in aver all makes it a much more cost efficient method to challenge fault detection.

Detection, localization and fault diagnosis using PetriNets for smart power distribution grids

With the expected surge of Electric Vehicles (EV) in the market in the near future, a threat to the grid is anticipated Introducing EVs in the grid serves as an additional load thus arising the need for increased generation which increases the total fuel cost An optimization algorithm has been proposed to minimize the total fuel cost by performing Economic Load Dispatch (ELD) of the committed generators and by optimizing the reactive power flow (Q ev ) from EV to grid Implementation of this algorithm leads to an improvement in the voltage profile and decrease in the losses in the system The proposed algorithm gives optimal values of reactive power that must flow from EV to grid and it also gives optimal real power generation of the committed generators System studies have been performed at different penetration levels and the results have been compared At higher penetration levels the improvement in the grid parameters has been found to be more significant

Optimal generation and reactive power scheduling of plug-in electric vehicles in V2G environment

Power System Security is a major concern in real time operation. Conventional method of security evaluation consists of performing continuous load flow and transient stability studies by simulation program. This is highly time consuming and infeasible for on-line application. Pattern Recognition (PR) is a promising tool for on-line security evaluation. This paper proposes a Support Vector Machine (SVM) based binary classification for static and transient security evaluation. The proposed SVM based PR approach is implemented on New England 39 Bus and IEEE 57 Bus systems. The simulation results of SVM classifier is compared with the other classifier algorithms like Method of Least Squares (MLS), Multi- Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA) classifiers.

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K. Shanti Swarup

Papers

Market operations in future Indian restructured power system scenario

Coordinated reactive power and crow bar control for DFIG-based wind turbines for power oscillation damping:

Detection, localization and fault diagnosis using PetriNets for smart power distribution grids

Optimal generation and reactive power scheduling of plug-in electric vehicles in V2G environment

Power System Security Assessment using Binary SVM Based Pattern Recognition