Joao M. G. Figueiredo1*, Jose M. G. Sa da Costa2

1 CEM-IDMEC, Universidade Evora, R. Romao Ramalho, 59; 7000-671 Evora, Portugal
2 IDMEC-IST — Technical University Lisbon, Av. Rovisco Pais; 1049-001 Lisboa, Portugal
* Corresponding Author, jfig@uevora. pt
Abstract

The growing concerns of global warming and depleting oil/gas reserves have made it
inevitable to seek energy from renewable energy resources. The positive impacts of an
increasing share of renewable energy on the mitigation of climate changes are indisputable.

This paper proposes the optimization of the electric energy production by photovoltaic cells through the development of an intelligent sun-tracking system. The developed solution has many advantages in relation to similar existing devices, as this system is autonomous regarding the information needed to process the optimal orientation and is intelligent in a way that it performs on-line monitoring of the photovoltaic energy production.

An experimental prototype was built and field results have proven the good performance of the developed tracking system.

The observed increase in power generation, in relation to other PV-systems, without tracking devices, is of similar magnitude (ca. 25%) as for other usual tracking solutions. However, this system has a relative advantage, as it measures exactly the controlled variable: the actual PV-power generation.

Keywords: Photovoltaic Cells, Tracking Systems, Intelligent Sensors, Supervisory Control.

1. Introduction

The use of new efficient photovoltaic solar cells has emerged as an important solution in energy conservation and demand-side management during the last decades. Owing to their initial high costs photovoltaic solar cells have not yet been an attractive alternative for electricity users who are able to buy cheaper electrical energy from the utility grid. However they have been used, as the wind turbines have been used, for water pumping and air conditioning in remote and isolated areas, where utility power is not available or is too expensive to transport.

Although solar cell prices have decreased considerably during the last years due to new developments in the film technology and manufacturing process [1], photovoltaic arrays are still considered rather expensive compared with the utility fossil fuel generated electricity prices. After building such an expensive renewable energy system, the user naturally wants to operate the photovoltaic infrastructure at its highest conversion efficiency by continuously utilizing the maximum available output power.

Nowadays photovoltaic energy has a low efficiency ratio concerning the complete distribution chain from production to consumption (ca. 12%). In optimized environments (materials, electric inverters, tracking systems, etc) an input of 1000W of solar incident energy can bring ca. 190W in electricity (efficiency of 19%). This low performance ratio implies big Earth surface consumption when it is intended to install industrial photovoltaic units with significant production impact (50MW — 100MW). Today it is being built in Portugal a photovoltaic plant with 64MW production capacity which occupies an huge area of ca. 400 ha (4 Km2).

The more relevant side effect of the low efficiency of photovoltaic systems is its poor competition related to traditional combustibles in both economical and financial aspects.

It is urgent to improve the production efficiency of electricity from the Sun as this energetic source is the most powerful in our planet, and it is expected that the Sun will become the main electricity production source by the year 2100, according to the study presented by the German Advisory Council on Global Change [2].

Owing to changes in the solar radiation energy and the cell operating temperature, the output power of a solar array is not constant at all times. Consequently, a maximum solar power tracking controller is always needed in any scheme with solar cell arrays to ensure maximum utilization. Therefore, works to solve the problems on maximum power point (MPP) tracking have always been a hot topic for photovoltaic array utilization systems. A logical MPP tracking search algorithm using normalized current, voltage and power at the work points that corresponds to the maximum power point values for different operating conditions was introduced earlier by the same authors [3, 4]. A on-line controller to track the MPPs under changing illumination was described in

[5].

An optimization approach using fuzzy was given in [6] for PV water pumping systems. Other MPP tracking controllers can be found in [7, 8].

In this paper an intelligent sun-tracking system for efficiency maximization referring photovoltaic energy production is developed. The developed tracking system is innovative in relation to the usual sun tracking systems available in the market.

The usual available solutions for tracking systems rely on the knowledge of the geographical position of the solar panel on the earth surface. With this knowledge it is possible to know the relative position of the sun, on a time basis, according to the well known solar tables [9]. Modern solutions incorporate a GPS system to calculate the position of the solar panel on the Earth surface. The orientations to be followed by the photovoltaic panel, on a regular time-base, are then pre­programmed, on an open loop approach.

There are significant efforts on the optimization of sun tracking systems as it is documented by several registered international patents. These solutions are based either on the above described principle either on the quantification of the received solar energy, either on the maximization of the solar incident radiation through the use of light concentration lens [10], [11].

The solution developed in this paper is innovative related to the above referred approaches as this system is autonomous regarding the information needed to process the optimal orientation and it is intelligent in a way that it monitors, on a real-time base, the photovoltaic energy production and it avoids systematic failures coming from changes on the assumed values (position, initial infrastructure orientation, cleanness of the photovoltaic cells, etc.).

2. Developed System