Artificial intelligence for photovoltaic systems

Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods

GIS-based Software Infrastructure to Model PV Generation in Fine-grained Spatio-temporal Domain

Nowadays, we are moving forward to more sustainable societies, where a crucial issue consists on reducing footprint and greenhouse emissions. This transition can be achieved by increasing the penetration of distributed renewable energy sources together with a smarter use of energy. To achieve it, new tools are needed to plan the deployment of such renewable systems by modelling variability and uncertainty of their generation profiles. In this paper, we present a distributed software infrastructure for modelling and simulating energy production of Photovoltaic (PV) systems in urban context. In its core, it performs simulations in a spatio-temporal domain exploiting Geographic Information Systems together with meteorological data to estimate Photovoltaic generation profiles in real operating conditions. This solution provides results in real-sky conditions with different time-intervals: i) yearly, ii) monthly and iii) sub-hourly. To evaluate the accuracy of our simulations, we tested the proposed software infrastructure in a real world case study. Finally, experimental results are presented and compared with real energy production data collected from PV systems deployed in the case study area

Rural electrification in central america and east africa, two case studies of sustainable microgrids

This paper deals with the electrification of rural villages in developing countries using Sustainable Energy Systems. The rural electrification feasibility study is done using Hybrid Optimization Model for Electric Renewable PRO (HOMER PRO). The HOMER PRO energy modelling software is an optimization software improved by U.S. National Renewable Energy Laboratory. It helps in designing, comparing and optimizing the design of power generation technologies. In this paper, two rural electrification case studies are modelled and analysed using HOMER PRO. Technical and economic evaluation criteria are applied to study the feasibility of a micro-hydro plant in El Díptamo (Honduras), and a hybrid plant composed of photovoltaic module arrays, Diesel generators, and flow batteries, in a small island on Victoria Lake. For both cases, we show the results of the studies of the daily and yearly loads, of the resources available in the area and the economic evaluation of the chosen plants configuration

Impacts of new technologies on load profiles

Desires to reduce reliance on fossil fuels and reduce greenhouse gas emissions, as well a period of technological development and falling technology prices, has led to increased interest in the use of new technologies in the energy sector. This paper, resulting from the GREEN Grid research program, presents initial analysis on the effects of three emerging technologies on the load profiles experienced by electricity distribution businesses. These three technologies are distributed photovoltaic generation, electric vehicles, and home energy storage systems. Widespread adoption of these technologies has the potential to cause a number of effects in the power system due to changing load profiles and the subsequently changing power flows. This paper presents modelling work firstly of the impacts of photovoltaic generation on load profiles. Regional variations in solar insolation and population density are taken into account. Secondly, the load of electric vehicle charging is modelled under different electric vehicle uptake and charging methodology scenarios. Thirdly the ability of EDB controlled energy storage systems to reduce peak load both with, and without, PV generation is modelled. The conventional notion that PV generation has no ability to reduce peak loads is tested, with results showing that while largely true there are some scenarios which challenge that notion. In the case of high rates of electric vehicle uptake and uncontrolled charging it is shown that a significant increase in the evening peak is to be expected. With more considered rates of electric vehicle uptake and charging delayed until late evening, either controlled or incentivized with night rate tariffs, it is shown that load impacts are minimal. Initial modelling of home battery energy storage systems show great promise in ability to reduce daily peaks given deployment in substantial numbers

Case study 2. Model validation using existing data from PV generation on selected New Zealand schools

Solar energy is abundant, free and non-polluting. Solar energy can offset the consumption of fossil fuels, greenhouse gas emission reduction targets and contribute to meeting the fast-growing energy demands. The use of solar energy for electricity generation from photovoltaic (PV) panels has increased but is still not a widely utilised technology in New Zealand. This research approximated the potential solar energy that could be harvested from the rooftops of existing residential buildings in a case study city. This research is divided into two work strands, each involving a case study. The first strand investigated if a model could be developed, using existing data sources to determine the solar harvesting potential from the rooftops of existing residential buildings. The second strand involved the validation of the solar PV prediction model proposed in the first strand of the research, to test the reliability of the modelling outcomes. Invercargill City was selected as the study city for case study 1. Invercargill is the southernmost city in New Zealand so represents a worst case scenario. The method involved merging computer-simulation of solar energy produced from PV modelling and mapping incoming solar radiation data from north facing residential rooftop area. The work utilised New Zealand statistical census map of population and dwelling data, as well as digital aerial map to quantify the efficient roof surface area available for PV installations. The solar PV potential was calculated using existing formulas to investigate the contribution of roof area to the solar PV potential in buildings using roof area and population relationship. The estimated solar PV potential was 82,947,315 kWh per year generated from the total solar efficient roof surface area of 740,504 m². This equates to approximately 60.8% of the residential electricity used in Invercargill’s urban area, based on the 7,700 kWh typical annual electricity consumptions per household. The result represents an immense opportunity to harvest sustainable energy from Invercargill’s residential rooftops. To verify the accuracy of the developed method for predicting the PV outputs, the model was applied to actual generation data from grid-connected solar photovoltaic (PV) systems that are installed in New Zealand schools under the Schoolgen programme (Case Study 2). A total of 66 Schoolgen PV rooftop models were incorporated in the analysis. At this stage, the actual system parameters including size, panel type and efficiency were included in the analysis. The performance prediction and analysis outcome showed the parameters and operating conditions that affect the amount of energy generated by the PV systems. This part of the research showed the area where the PV model can be improved. The predicted generation from the model was found to be lower than the actual generation data. Schoolgen systems operating at over 0.75 performance ratio were found to be underestimated. This indicated that most Schoolgen PV systems were operating at higher capacities than predicted by the default value of system losses. The analysis demonstrated the effects of PV technology type, site orientation, direction and tilted angle of the panels on the ability to generate expected amount of potential capacity based on solar resource availability in different site scenarios. This in turn has provided more in depth analysis of the research and served to expand the area for improvements in the design of the model

Integrating power flow modelling with building simulation

The inclusion of photovoltaic facades and other local sources of both heat and power within building designs has given rise to the concept of embedded generation: where some or all of the heat and power demands are produced close to the point of use. This paper describes recent work to simulate the heat and power flows associated with both an embedded generation system and the building it serves. This is achieved through the development of an electrical power flow model and its integration within the ESP-r simulation program

Simulation of nanostructure-based high-efficiency solar cells: challenges, existing approaches and future directions

Many advanced concepts for high-efficiency photovoltaic devices exploit the peculiar optoelectronic properties of semiconductor nanostructures such as quantum wells, wires and dots. While the optics of such devices is only modestly affected due to the small size of the structures, the optical transitions and electronic transport can strongly deviate from the simple bulk picture known from conventional solar cell devices. This review article discusses the challenges for an adequate theoretical description of the photovoltaic device operation arising from the introduction of nanostructure absorber and/or conductor components and gives an overview of existing device simulation approaches.Comment: Invited paper, accepted for publication in IEEE Journal of Selected Topics in Quantum Electronic

Cakar ayam shaping machine

Cakar ayam (Figure 7.1) is one of the Malay traditional cookies that are made from sliced sweet potatoes deep-fried in the coconut candy. In current practice of moulding the cookies, the fried sweet potatoes are molded using traditional manual tools, which are inefficient and less productive for the mass production purposes. “Kuih cakar ayam” associated with the meaning of the idiom means less messy handwriting has a somewhat negative connotation .This cookies may just seem less attractive in shape but still likeable . In fact, this cookie is considered a popular snack even outside the holiday season. The choice of the name of this cookie is more to shape actually resembles former chicken scratches made by the paw the ground while foraging. The value of wisdom, beauty and creativity of the Malays is clearly evident through the Malay cookie. Although it is attacked by the invention of modern cakes that look far more interesting, these cakes will be able to survive a long time until now

Assessment of PV Systems Performance in the Madeira Island Using Typical Meteorological Year Data

This paper focus on the development of an algorithm using Matlab to generate Typical Meteorological Years from weather data of eight locations in the Madeira Island and to predict the energy generation of photovoltaic systems based on solar cells modelling. Solar cells model includes the effect of ambient temperature and wind speed. The analysis of the PV system performance is carried out through the Weather Corrected Performance Ratio and the PV system yield for the entire island is estimated using spatial interpolation tools

Modelling and simulation of small-scale embedded generation systems

Advances in heat and power production are leading to a revolution in how buildings are perceived as an energy system. The rapid development of fuel cells, photovoltaic facades, cogeneration and the evolution of ducted windturbines allows the designer to envisage a building providing much of its own heat and power through local embedded generation (EG). However, the addition of heat and power production to the building increases it complexityas an energy system. New design issues must be addressed such as the integration of EG with traditional HVAC and power systems; optimal demand and supply matching; demand side management and its impact on environmentalperformance; interaction of the EG system with the local electricity network, etc