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

In competitive power markets, the reliable and continuous supply required for maintaining the power market’s economic sustainability and the same is also useful for receiving a correct economic signal by the various market players Some ancillary services are required to decrease the fluctuations created by wind power plants and maintain continuity reliability of supply to the end-use customers in the power market This paper presents an optimal bidding strategy for effective coordination of wind power plant (WPP) and pumped storage plant (PSP) in day-ahead energy and ancillary services like spinning reserve (SR) and fast responsive reserve (FRR) in the power market The coordinated operation of PSP with WPP has been considered to decrease the intermittency of available wind power supplied to the grid The obtained revenue in both cases (SR and FRR) are compared The results demonstrate that the coordination of PSP and WPP reduces the imbalances in bids, penalties in the day-ahead ancillary service, and energy markets (AS & EMs) with simultaneous maximum revenue achieved by both PSP and WPP

Optimal Bidding Strategy with Ancillary Services in Hybrid Competitive Markets

The integration of renewable energy sources into power systems changes the transient and fault current characteristics of the conventional grid. The variation in the system response during grid disturbance like sudden load changes or fault would cause the failure of traditional protection and control. Since the operating condition of DFIG depends on the characteristics of the grid and its control, the short circuit current in the system becomes more complex. This paper analyzes the short circuit characteristics of DFIG and develops an analytical expression for the three phase fault current. Depending on the severity of the fault in terms of voltage drop, the fault current responses are developed with and without crow bar resistance. The power swings that originates in the system when the fault is cleared are also analyzed in the paper. The transient simulation studies are performed in PSCAD/EMTDC by integrating DFIG to WSCC system. Case studies are performed to analyze the impact of location of fault to the power swing and fault current contribution.

Impact of DFIG based wind energy conversion system on fault studies and power swings

The addition of distributed PV sources to low voltage distribution networks instigate issues to various operational parameters of the network. With modern smart inverters having controllable settings for voltage and power injection these issues can be alleviated. An Intelligent method utilising smart inverter functionalities of a PV source in a distribution network is proposed in present work to minimise, the power import from the grid, reduce network losses and minimise the magnitude of voltage violation. The optimal settings depend on load and generation variables. In order to reduce computational complexity, a scenario-based method is used to handle these stochastic components in the system. A Non-Sorted Genetic Algorithm (NSGA) is used for optimising the smart inverters parameters. The proposed scheme is envisaged to be realised by a Distribution Management System (DMS) which measures and coordinates all the smart inverters within the distribution feeder.

An intelligent methodology to improve distribution system operational parameters utilising smart inverter functionalities of PV sources

This paper gives Interval Linear Programming (ILP) approach based solution to optimal relay coordination problem for microgrid scenario. Relay coordination in microgrids is complex because of varied fault current magnitude and direction due to existence of Distributed Generation (DG). Over-current relays are feasible and economic choice of protection for distribution systems connected with DG. The coordinated relay settings must account to all possible fault scenarios in both grid connected and isolated microgrid modes of operation. Inadequate fault current levels from grid connected to isolated mode is the major cause of miscoordination in the microgrid network. This paper systematically formulates the relay coordination problem for microgrid scenario as linear interval optimization problem. The feasibility of ILP method in including all the fault scenarios and operating modes of microgrid by representing the variables as intervals are combined to find the optimal overcurrent relay settings. The results show the effectiveness of this method. The programming is done using optimization tool box available in Matlab.

Optimal relay coordination for microgrids using interval linear programming approach

Distance relay maloperates due to various reasons, like dc offset in current waveforms, capacitive voltage transformer transients, remote-end in-feed in the presence of fault resistance, power swings and loading. dc offset in current waveforms results in overreach, causing distance relay to operate for faults outside its protected zone. There are many offset removal filters proposed by researchers in literature, but it is found, that the same ideas fail to penetrate as a filter into today's Intelligent Electronic Devices (IED). The objective of this paper is not to propose a new filter, but to provide insights into testing and validating those DC offset removal filters, which are not focused till now. This paper provides the additional factor to be considered for validating filters, which are proposed for dc offset removal and this is done by comparing the performance of three dc offset removal filters, digital mimic filter (dmf), patented filter (pf) to remove dc offset and double differentiator filter (ddf) which are currently used by relay manufacturers.

K. Shanti Swarup

Papers

Optimal Bidding Strategy with Ancillary Services in Hybrid Competitive Markets

Impact of DFIG based wind energy conversion system on fault studies and power swings

An intelligent methodology to improve distribution system operational parameters utilising smart inverter functionalities of PV sources

Optimal relay coordination for microgrids using interval linear programming approach

Insights into testing and validation of DC offset removal filters in numerical distance protection