PV powered universities[edit | edit source]

Grid parity and self-consumption with photovoltaic systems under the present regulatory framework in Spain: The case of the University of Jaén Campus[1][edit | edit source]

Abstract The cut-off of any subsidy or feed-in tariff that incentives the installation of new renewable energy systems which are close to the grid parity, is a reality in most of the European countries, but in the recent years the grid parity has worsened because of the global economic crisis. In the case of Spain, in addition to the economic problems, the photovoltaic sector has been dramatically damaged through a changeable regulatory framework, an excessive bureaucracy and the inclusion of additional fees or possible back-up tolls that are very prejudicial for the deployment of this sector. Nowadays, the current Spanish legislation mentions the possibility of self-consumption (totally or partially) of the electricity generated by PV or any renewable energy systems but, up to the date of this work, the law that regulates the administrative, technical and economic conditions for the net-metering of the electrical energy produced within the consumer׳s network, is still under a draft stage. In this paper it is analyzed the case of the University of Jaen, where it has been identified and simulated several PV systems on the roofs and parking lots of the University Campus, and considering the current electrical tariffs (hourly defined for the case of high power and high voltage consumers), it has been done a cost and economic analysis. As a result, it has been obtained an average Levelised Cost of Energy around 0.125 € kWh−1, a discount payback time of 17.5 years or less, a positive Net Present Value and a nominal Internal Rate of Return of 8.48% in the worst case. Beyond that, it has been carried out a sensitivity analysis of the factors that have more influence in the profitability of these systems, like the initial investment cost, the PV electricity yield, additional taxes and the variations in the electricity price market.

  • The methods used for economic analysis in this paper are the net present value, the discounted payback time, and the internal rate of return
  • The PV electricity cost production has been estimated through the concept of Levelised cost of electricity in order to compare photovoltaic technology with other sources of energy
  • The most sensitive parameter with influence in the variation of the LCOE is considered to be the initial investment cost per Kwp of PV grid-connected system

Green Campus #x2014; Energy management system[2][edit | edit source]

Abstract The aim of this paper is to describe and discuss about the main objectives and functions of the Energy Management System (EMS) of the Green Campus Smart Grid (GCSG). The main objectives of the Green Campus Smart Grid project are to realise fully functional smart grid (SG) environment, to demonstrate the functions of the smart grid and to function as a test platform for further smart grid related research. The EMS is responsible for controlling the smart grid devices and applications connected to the smart grid environment. By gathering the information from these devices to the EMS database, it can optimise the operation of the devices by accessing single database? and increase energy efficiency of the smart grid. The database also serves research purposes by offering access to long term data of the devices connected to the smart grid environment.

  • All of the data includes information about estimated load curves, stationary loads connected to the smart grid, priority of the loads, and weather forecasts are processed in Energy Management System

Design microgrid for a distribution network: A case study of the University of Queensland[3][edit | edit source]

Abstract With more and more distributed generators (photovoltaic and wind) and distributed energy resources being integrated into power networks, traditional electricity grids may be replaced by smaller and more efficient grids called microgrids. Especially in recent years, there has been a significant increase in photovoltaic (PV) installations in Australia. As such, potential for microgrids to continue supply power to loads during a blackout was evident. However, microgrids have posed a concern for utilities as they do not provide utilities the same ability as the conventional grid to regulate microgrid voltage and frequency, and later possibly interfere with restoration of normal electricity supply. This paper investigates the feasibility of forming a microgrid in the University of Queensland for continuous electricity supply during power outage by utilizing its PV and storage systems. A simple but effective load shedding algorithm based on existing schemes and future technologies has been implemented. It also demonstrates how microgrid resynchronization can be achieved.

  • The intermittency of PV power supply may threaten microgrid integrity; therefore, in order to maintain system voltage and frequency within limits, loads are to be shed according to its priority
  • Under frequency load shedding works by disconnecting predefined loads when system frequency drops below a set threshold value
  • Genetic algorithm is used for load shedding and it fulfills all restrictions set by designer, minimizes disconnection of loads, and prevents disconnection of high priority loads
  • Smart buildings has enabled crucial information such as local real time electricity consumption and generation to be gathered; therefore, engineers will be able to make better decisions regarding switching of loads or changing power generation in real time
  • As soon as normal supply of power resumes, it is necessary for the microgrid to resynchronize with the main grid as microgrid operation in the long run is not sustainable
  • The most common closed loop method for resynchronization is the synchronously rotating frame phase locked loop
  • An effective load shedding algorithm is the key to maintaining microgrid integrity by ensuring balance between power supplied and demanded
  • As real power output from the PV arrays can not be controlled power mismatch may occur, and in order to count for power mismatch, a user defines apparent power safety margin and real power margin, and they are applied to the battery storage system
  • When utility supply return, the main circuit breaker cannot be closed instantly due to phase difference in voltage waveforms. Instead microgrid frequency is increased or decreased to minimize the phase difference

New experimental method for measuring power characteristics of photovoltaic cells at given light irradiation[4][edit | edit source]

Abstract U-I characteristics - or electric power - as function of electrical voltage or current - of a solar panel (PV cell or panel) gives important information for developers, engineers and users. From this reason to get U-I plot or characterization of the electric power of a solar panel plays important role at the tests. In this paper a new and easy experimental method for U-I measurement (indirectly measured electric power data) for PV cells will be introduced. The new idea describes a simple, fast and reliable way how to get U-I characteristics - or power properties - of PV cells in a laboratory at a university using basic experimental tools.

  • In order to specify the optimum value of the operating point the maximum power output of the PV panel has to be determined at given and constant irradiation
  • One of the most general specific functions for description of a PV cell is the U-I (voltage-current) characteristics which belongs to given light irradiation
  • The mechanical holder for PV panels is called as adjustable measurement stand. The holder is a rotating and tilting mechanical stand, and rotation around the vertical axis is possible in 360 degree
  • The minimum azimuth angle is 30 degree and the maximum is around 90
  • In this article outlets for electrical signals of the PV tables are positioned in inner laboratory using cable connections, and for each PV panel a user friendly measurement place was designed and built on the laboratory wall. The measurement places give output voltage signals of the PVs through special inverters for the users, this way users can connect their meter and measure the voltage data

Comparison of power generation from solar panel with various climate conditionand selection of best tilt angles in Ulaanbaatar[5][edit | edit source]

Abstract The tilt angle of the photovoltaic (PV) array is the key to an optimum power generation. Solar panels or PV arrays are most efficient, when they are perpendicular to the sun's rays. Optimal tilt angle of solar panel are different at places of the earth. In Ulaanbaatar that is coldest capital city, the optimal tilt angle is 30 degrees in summer and 60 degrees in winter. By the calculation, the average tilt angle of the solar panel in Ulaanbaatar that can produce annually large amount energy is around 45 degrees. But 45 degrees of tilt angle are not so suitable due to snow and ice accumulation on the solar panel during winter in Ulaanbaatar.

  • If the tilt angel of solar panel is around 45 degrees the snow and accumulation on the solar panel will not be melted by sun's rays and will not be blown by wind
  • Daily power generation without snow and ice accumulation on the solar panels is three times larger than solar panels with snow and ice accumulation
  • Snow and ice will not be accumulated on the solar panel surface when the tilt angel of the solar panel is around 60 degrees in Ulaanbaatar
  • The power generation from PV modules is affected by tilt angel, irradiance, and module temperature

A simple formula for estimating the optimum tilt angles of photovoltaic panels[6][edit | edit source]

Abstract This paper presents a new approach to computing the optimal tilt angle for photovoltaic (PV) panels. The influence of cloudy conditions on the tilt angle is explored. It is demonstrated that more energy can be extracted from the PV system in cloudy conditions when the tilt angle of the panel is decreased compared to when the panel is aimed to be facing directly normal to the sun. Validation for fixed tilt, south-facing panels and for 2-axis tracking panels is presented by numerical simulations.

  • It has been demonstrated that more energy can be extracted from the PV system in cloudy conditions when the tilt angel of the panel is decreased
  • The benefits of simplified formulas are that the tilt angels can be calculated based on historically known quantities, and there will be increased PV harvesting energy yield due to higher PV energy output in cloudy conditions

Lightning protection of PV systems[7][edit | edit source]

Abstract Lightning strikes can affect photovoltaic (PV) generators and their installations, involving also the inverter's electronics. It is therefore necessary to evaluate the risk connected to lightning strikes in order to adopt the correct protective measures for the system. The Standard IEC (EN) 62305-2 reports the procedures for the risk calculation and for the choice of proper lightning protection systems. Usually the technical guidelines suggest protecting with SPDs (surge protective devices) both DC and AC sides of the PV installation. The paper estimates overvoltages due to lightning discharges and evaluates the actual need of lightning protection measures on the basis of the results of the risk analysis and of the protection costs. The paper in the first part presents the procedure for the evaluation of the risk connected to lightning strikes according to the Standard IEC EN 62305-2; then it applies the procedure to typical PV installations, analyzing risks and risk components which have to be kept into account. In the second part the paper studies the surge overcurrents to be expected on LV systems, induced voltages caused by direct flashes and by flashes near the PV installation. Approximated equations for the calculation of induced voltages and currents are given for different types of LPS (lightning protection systems) and lightning flashes. In the last part of the paper the methodology is applied as an example to a practical case and some conclusions are given.

  • The installation of PV modules on buildings does not increase the risk of a lightening strike, but there may be an increased damage for the electric installation of the building
  • Due to the wiring of the PV lines inside the buildings, strong conducted and radiated interferences may result from lightening currents
  • Installation of overvoltage protection is important on both sides of the power electronic device
  • To reduce the risk of damages due to the lightening strike a coordinated SPD system, and an external LPS could be installed

Economic feasibility study of a 16 kWp grid connected PV system at Green Energy Research Centre (GERC), UiTM Shah Alam[8][edit | edit source]

Abstract Photovoltaic systems are currently being considered as competitive sources of power energy around the world including Malaysia. However, the main problem hampering the expansion of solar energy is its high cost per kWh. This research is carried out to study the economic feasibility of a 16kWp grid connected photovoltaic (PV) system at Green Energy Research Center (GERC), UiTM Shah Alam. The PV system comprises of 1) A 6 kWp single phase PV system and 2) A 10kWp three phase PV system. The analysis is carried out considering the system will be sold to power utility and paid at the Feed-in tariff (FiT) set by Sustainable Energy Development Authority Malaysia (SEDA). A financial model is developed to calculate the expected Net Present Value (NPV) and Internal Rate of Return (IRR) of the project over its expected lifetime. The effects of uncertainties i.e. solar irradiance, investment cost, discount rate and inverter failure on the profitability of the PV system are studied using 1) sensitivity analysis and 2) probabilistic analysis. Sensitivity analysis shows that the profitability of the PV project is most affected by solar irradiation followed by FiT, investment cost and discount rate. The probabilistic analysis shows that considering the current FiT and with no inverter failure, the confidence level of getting the IRR greater than Minimum Acceptable Rate of Return (MARR) of 12% is 75%. On the other hand, for the case with inverter failure, the confidence level of getting the IRR greater than 12% is 25%.

  • A feasibility study is performed to investigate whether the project would be profitable or not considering various uncertainties over its lifetime
  • Financial model used in this study is the discounted cash-flow method which calculates the net present value and the internal rate of return of the investment
  • The effects of uncertainties on the profitability of investment are analyzed using sensitivity analysis and probabilistic analysis
  • A risk assessment technique is also incorporated in the model to calculate the confidence level of getting the NPV and IRR greater than the target value

Economical Design of Utility-Scale Photovoltaic Power Plants With Optimum Availability[9][edit | edit source]

Abstract This paper presents an algorithm for the economical design of a utility-scale photovoltaic (PV) power plant via compromising between the cost of energy and the availability of the plant. The algorithm inputs are the plant peak power and the price of inverters with respect to their power ratings. The outputs are the optimum inverter ratings and the interconnection topology of PV panels. This paper introduces the effective levelized cost of energy (LCOE) (ELCOE) index as the core of the proposed design algorithm. ELCOE is an improved index based on the conventional LCOE that includes the availability of a power plant in economical assessments. The conventional LCOE index determines centralized topology (e.g., 1-MW inverter for a 1-MW PV power plant) for minimizing the energy generation cost, whereas based on ELCOE, a multistring topology (e.g., a 1-MW PV plant consists of fifty 20-kW inverters) despite of higher investment cost becomes the economically winning topology. Given the price of commercially available PV inverters at present, the case studies in this paper show that, for 0.1–100-MW PV power plants, the economical ratings of inverters range from 8 to 100 kW. The recently installed PV power plants confirm the feasibility of the calculations based on the suggested algorithm.

  • PV plant has four topologies: centralized, ac modular, string, and multistring
  • The type of PV invertes and there interconnection methods have impact on features of PV power plants in terms of efficiency, investment cost, and reliability in energy generation

Measurement of spectral sensitivity of PV cells[10][edit | edit source]

Abstract PV based large scale energy generation has spread significantly. In spite of similar technical parameters the amount of yearly produced energy may differ by notable percents. It results from the operation of solar trackers and also from the different spectral behavior of the different PV panel types. In this paper we introduce a novel on site spectral sensitivity measurement method. The spectral characteristic is recalculated from separate power maximum measurements, where the measurements are made by spectrally different natural irradiation (sunrise, noon, foggy, cloudy, etc.).

  • The efficiency of transformation of the infrared radiation into electricity is low. Also efficiency of the whole spectra is 6-7% of the amorphous cells, 15-17% of the crystalline cells
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Authors Negin Heidari
License CC-BY-SA-3.0
Language English (en)
Related 3 subpages, 4 pages link here
Impact 696 page views
Created January 24, 2014 by Negin Heidari
Modified February 23, 2024 by Felipe Schenone
  1. D.L. Talavera, J. de la Casa, E. Muñoz-Cerón, G. Almonacid, Grid parity and self-consumption with photovoltaic systems under the present regulatory framework in Spain: The case of the University of Jaén Campus, Renewable and Sustainable Energy Reviews, Volume 33, May 2014, Pages 752-771, ISSN 1364-0321.
  2. H. Makkonen, J. Partanen, V. Tikka, P. Silventoinen, and J. Lassila, "Green Campus #x2014; Energy management system," in 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013), 2013, pp. 1–4.
  3. C. T. T. Ho, R. Yan, T. K. Saha, and S. E. Goodwin, "Design microgrid for a distribution network: A case study of the University of Queensland," in 2013 IEEE Power and Energy Society General Meeting (PES), 2013, pp. 1–5.
  4. A. Varga, E. Racz, and P. Kadar, "New experimental method for measuring power characteristics of photovoltaic cells at given light irradiation," in 2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI), 2013, pp. 405–409.
  5. E. Adiyasuren, U.-O. Damba, and B. Tsedensodnom, "Comparison of power generation from solar panel with various climate conditionand selection of best tilt angles in Ulaanbaatar," in 2013 8th International Forum on Strategic Technology (IFOST), 2013, vol. 2, pp. 519–521.
  6. S. W. Quinn and B. Lehman, "A simple formula for estimating the optimum tilt angles of photovoltaic panels," in 2013 IEEE 14th Workshop on Control and Modeling for Power Electronics (COMPEL), 2013, pp. 1–8.
  7. E. Pons and R. Tommasini, "Lightning protection of PV systems," in 2013 4th International Youth Conference on Energy (IYCE), 2013, pp. 1–5.
  8. N. Y. Dahlan, M. El Azizi Mohammed, W. N. A. W. Abdullah, and Z. M. Zain, "Economic feasibility study of a 16 kWp grid connected PV system at Green Energy Research Centre (GERC), UiTM Shah Alam," in 2013 IEEE Business Engineering and Industrial Applications Colloquium (BEIAC), 2013, pp. 125–130.
  9. Z. Moradi-Shahrbabak, A. Tabesh, and G. R. Yousefi, "Economical Design of Utility-Scale Photovoltaic Power Plants With Optimum Availability," IEEE Transactions on Industrial Electronics, vol. 61, no. 7, pp. 3399–3406, Jul. 2014.
  10. P. Kadar and A. Varga, "Measurement of spectral sensitivity of PV cells," in 2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics (SISY), 2012, pp. 549–552.
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