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.

/pdf/online-short-term-solar-power-forecasting-1ljgpbshkb.pdf

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.

/pdf/particle-swarm-optimization-technique-system-and-challenges-1t22wy4m1r.pdf

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

https://www.ee.iitb.ac.in/~npsc2008/NPSC_CD/Data/Oral/BIC3/p27.pdf

Bidding strategy for pumped-storage plant in pool-based electricity market

This study proposes a novel method based on mathematical morphology (MM) for islanding detection in micro-grid integrated with distributed generation (DG). The method uses basic MM operators like dilate erode difference filter (DEDF) to operate on three-phase voltage and current signals on target DG location. These filter output values are fed to a new operator defined as the average of the difference between maximum and minimum value of DEDF at each structuring element called K V and K I . Accordingly, a new operator called the MM ratio index (MM RI) of K I to K V is derived. The MM RI computed is used to track the islanding condition from non-islanding condition. Additionally, to further aid the islanding detection, a mathematical morphological operator close open difference filter on negative sequence voltage is computed, which is passed through a difference operator D. The proposed method is analysed extensively to efficiently detect islanding in electrical power distribution network integrated with DG.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2015.0910

Mathematical morphology-based islanding detection for distributed generation

Hybrid DE–SQP algorithm for non-convex short term hydrothermal scheduling problem

This paper develops bidding strategy for operating multiunit pumped-storage power plant in a day-ahead electricity market. Based on forecasted hourly market clearing price, the objective is to self-schedule and maximize the expected profit of the pumped-storage plant, considering both spinning and nonspinning reserve bids and meeting the technical operating constraints. Evolutionary tristate particle swarm optimization (ETPSO) based approach is proposed to solve the problem, combining basic particle swarm optimization (PSO) with tristate coding technique and genetics-based mutation operation. The discrete characteristic of a pumped-storage plant is modeled using tristate coding technique and mutation operation is used for faster convergence. The proposed model is adaptive for nonlinear 3-D relationship between the power produced, the energy stored, and the head of the associated reservoir. The proposed approach is applied for a practical utility consisting of four units. Simulation results for different operating cycles of the storage plant indicate the attractive properties of ETPSO approach with highly optimal solution and robust convergence behavior.

K. Shanti Swarup

Papers

Bidding strategy for pumped-storage plant in pool-based electricity market

Mathematical morphology-based islanding detection for distributed generation

Hybrid DE–SQP algorithm for non-convex short term hydrothermal scheduling problem

Evolutionary Tristate PSO for Strategic Bidding of Pumped-Storage Hydroelectric Plant

Artificial neural network using pattern recognition for security assessment and analysis