Design and Development of Laboratory Single-Axis PV Module Tracker

Solar energy is an integral part of the renewable energy industry. Advanced solar farms actively track solar movement and update solar panel angles to maximize the system’s output power. Cal Poly boasts its own Solar Farm that features a single-axis tracking system. Single-axis tracking aims to get panels as close to perpendicular as possible given the panel arrangements and given the time of year. Single-axis tracking is a more robust measurement and tracking option. Single-axis tracking systems usually only have East-West panel arc movement, following the sun’s rotation. Dual-axis trackers have both East-West and North-South panel arc movements. Dual-axis systems have the ability to shift their North-South angle to better face the sun as the seasons change, based on GPS location. Solar panels generate the most power when receiving the highest light intensity. Single-axis systems generally cost less than Dual-axis. One less axis of motion translates to fewer mechanical parts, fewer motor controllers, and ultimately a more durable system. To account for the inability to directly face the sun year round, students will study how to eliminate inter-row shading between panels to maximize power production. To observe and improve the single-axis tracking system, a laboratory model of the solar farm will be created. Identical solar panels to the Cal Poly panels will be integrated with a solar tracking embedded system. The system will be tested on available test panels in conjunction with a specialized angle tracking measurement network. Students will alter and study the system, accommodating for variables that are not accounted for in the current static algorithm. The new testing system will allow students to study the issues present in the farm and to develop a proposal to improve the power production performance at the farm. In addition, students will learn the fundamentals of single-axis tracking. The laboratory model will be adaptable regardless of the location and terrain of the solar farm, and will tilt the panels in the most optimal angle for the network of arrays in a typical farm

Probabilistic Signature Based Framework for Differential Fault Analysis of Stream Ciphers

Differential Fault Attack (DFA) has received serious attention in cryptographic literature and very recently such attacks have been mounted against several popular stream ciphers for example Grain v1, MICKEY 2.0 and Trivium, that are parts of the eStream hardware profile. The basic idea of the fault attacks consider injection of faults and the most general set-up should consider faults at random location and random time. Then one should identify the exact location and the exact timing of the fault (as well as multi bit faults) with the help of fault signatures. In this paper we consider this most general set-up and solve the problem of fault attack under a general framework, where probabilistic signatures are exploited. Our ideas subsume all the existing DFAs against the Grain family, MICKEY 2.0 and Trivium. In the process we provide improved fault attacks for all the versions of Grain family and also for MICKEY 2.0 (the attacks against Trivium are already quite optimal and thus there is not much scope to improve). Our generalized method can also take care of the cases where certain parts of the keystream bits are missing for authentication purpose. In particular, we show that the unsolved problem of identifying the faults in random time for Grain 128a can be solved in this manner. Our techniques can easily be applied to mount fault attack on any stream cipher of similar kind