WELCOME TO THE SWRE. Software for Renewable Energy - Bay Area. 23Feb12 Meetup: Intro to SWRE

Transcription

1 WELCOME TO THE SWRE Software for Renewable Energy - Bay Area 23Feb12 Meetup: Intro to SWRE 1

2 AGENDA 7:00 to 7:20 - snack-up and socialize 7:20 to 8:00 - presentation 8:00 to 8:30 - follow-up discussion 8:30 to 9:00 - grab another drink and continue getting to know your brethren 2

3 GROUND RULES Eat and drink throughout Interrupt me at any time Share your experiences and opinions and details of your favorite projects (past and present) Stay around and chat after the presentation 3

4 WHO ARE WE? Software (SW) professionals/amateurs/hobbyists Renewable Energy (RE) industry observers/professionals/fanboys people who passionately care about the impact of RE on our lives, the planet, the other 7 billion people we live with people who want to use their skills and experience in an industry that really matters no offense... but do we really need another mobile ad-driven geo-aware nano coupon-clipping synergy farmville social gaming app or do we need to do our part to make RE make financial sense for everyone in the world? 4

5 OUR GOALS! Make RE a sexy industry for SW professionals (or even just the Energy Industry, in general) Why doesn t one of the worlds largest, most profitable 1, most dynamic, most complicated industries get more love? We are a group of people who passionately care about our SW projects and also RE s place in the future Yet, I feel like we meet and cross-pollinate less than SW professionals in other industries There are web 2.0 hack-a-thons nearly every week here in the Bay area. When was the last time you heard about an energy 2.0 hack-athon? 1: 5

6 !OUR GOALS Religious debates (too many other meetup groups devolve into these dogmatic arguments): Python vs. Perl; Windows vs. Linux; Django vs. RoR; compiled vs. interpreted; simple scripts vs. full-on OOP; Emacs vs. vi; git vs. SVN Further, we don t want to crown one RE sub industry (solar, wind, hydro, bio fuels, etc.) as king... all need to grow and all need more skilled SW experts to do so 6

7 WHO AM I? I m Dave I studied CompEng and CS I started a company called Elevated Systems which currently does some SW consulting I ve spent about 6 years playing with RE almost all in or around the solar industry... I will always be skewed towards solar I ve spent about 3 years playing with Intelligent Transportation Systems (ITS) vehicle-to-vehicle and vehicle-to-infrastructure safety applications I have biases: SW: C++, Python, Django, PyQt, jquery, Linux, Mac RE: Solar, SmartGrid, EVs 7

8 WHO ARE YOU? Name Company (optional) What thrills you the most about SW? RE? What s a recent project you ve worked on that you re excited about? 8

9 WHERE DOES SW LIVE IN RE? Everywhere: controls, factory automation, data management and visualization, system modeling, financial modeling... But I ve got 2 specific examples based on personal experiences: system modeling AND data collection/management/ visualization What are yours? 9

10 EX: SYSTEM MODELING Problem Statement: Simulate the power production of a solar field. mathematically model a solar cell represent all of the attributes: open-circuit voltage (Voc), short-circuit current (Isc), max power (Pmp), series resistance (Rs) build that up into a panel number of cells, optical losses, wiring resistive losses, etc. put panels and combiners and inverters together into a field more losses to model... so much wire simulate the performance of that field throughout the course of the year tweak some variables and repeat (maybe even optimize?!) 10

11 EX: SYSTEM MODELING - BASIC class SiSolarCell(object): Isc_amps = 0.05 Voc_volts = 0.6 R_series_ohms = class Panel(object): cell_array = [SiSolarCell()]*40 optical_loss_percent = 0.95 resistive_loss_percent = 0.95 class Field(object): panel_array = [Panel()]*100 resistive_loss_percent = 0.95 inverter_max_voltage_volts =

12 EX: SYSTEM MODELING - NOW W/ OOP class SiSolarCell(object): Isc_amps = 0.05 Voc_volts = 0.6 R_series_ohms = class SuntechSolarCell(SiSolarCell): Isc_amps = 0.07 class TrinaSolarCell(SiSolarCell): R_series_ohms = class SuntechPanel(Panel): cell_array = [SuntechSolarCell()]*40 class TrinaPanel(Panel): cell_array = [TrinaSolarCell()]*45 class Field(object): panel_array = [SuntechPanel(), TrinaPanel]*100 resistive_loss_percent = 0.95 inverter_max_voltage_volts =

13 EX: SYSTEM MODELING - RECAP What s next? simulate production performance in various weather conditions, mounting strategies, etc. add in financial costs set some hard constraints and some variables (number of panels, number of inverters, etc.) and optimize Who cares? (aka: where to work) System Integration companies Engineering Procurement and Construction (EPC) firms Residential Full Service Providers (like SolarCity) Which tools to use? Python (bias alert!!), Matlab, Excel (with VB) anything with some basic OOP capabilities, GUI construction, and graphing/reporting packages 13

14 EX: DATA MANAGEMENT Problem Statement: Collect and analyze the actual power production of a solar field. collect data from various sources, sensors (ex: irradiance sensors, inverters, tracking sensors) transport that data off-site to some data archive visualize data in some central portal for field owner/operator/stakeholders provide some remote control mechanisms... bring some parts of the field online/offline (maybe through trackers or inverters) alert stakeholders of problems at the field analyze data to spot performance trends over time (weather, soiling, cell degradation) 14

15 EX: DATA MANAGEMENT - COLLECT Start with an embedded PC in the field or just an embedded micro controller (PIC, Atmel/Arduino) Interface with sensors using some common industrial protocols (RS232, RS485, MODBUS, CAN, analog voltages) irradiance sensors and weather stations inverters Write an program to periodically collect all data Automatically respond to certain field conditions ex: high-wind stow Skills needed: embedded systems programming, communications protocols knowledge, maybe even some circuit design 15

16 EX: DATA MANAGEMENT - TRANSPORT Start with a connection to the internet maybe we need cellular or satellite service (M2M) Package up collected data (XML, JSON, etc.) Setup an encrypted channel to DB (SSH, VPN, SSL, etc.) Push to DB server use raw SQL transactions, RPCs, or maybe a modern REST interface Skills needed: networking knowledge, data compression and security knowledge, DB knowledge 16

17 EX: DATA MANAGEMENT - ANALYZE Build a GUI application or web application to access the DB and visualize collected data Take the next step to help the user see trends in their data more clearly using data mining and analysis techniques Skills needed: GUI programming, basic data analysis, web application development (front-end and back-end: HTML, CSS, JS, PHP, RoR, Django,.NET, Java, web operations, etc.) 17

18 EX: DATA MANAGEMENT - RECAP What s next? make the data accessible on a mobile application use data trends to drive engineering decisions (long term soiling has much greater production impacts on module X than Z) Who cares? (aka: where to work) field owners and financial stakeholders field installers RE data aggregators (FatSpaniel/PowerOne, Draker Labs, ArgusOn, etc.) 18

19 NEXT MEETUP IDEAS Not so technical: crash course in policies that matter to SWRE members Federal laws and mandates, CA laws (ex: AB32) meta discussions about RE industry what s the state-of-the-art for various technologies? does renewable == clean? RE growth is driven by finance... why should we care? More technical: fault tolerance and reliability in SW for RE how to build a DB schema for RE data Your ideas will probably be better... 19

20 QUESTIONS 20