Your energy connection

Your energy connection is a South Carolina Energy Office publication on topics related to energy conservation and renewable energy in the state.

Photovoltaic power forecast modeling with artificial neural networks

Dissertação de Mestrado, Engenharia Eletrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

Avaliação do potencial energético de cana (Arundo donax L.) no Algarve

Dissertação de Mestrado, Energias Renováveis e Gestão de Energia, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

Optimization of Energy Distribution in Solar Panel Array Configurations by Graph Theory and Minkowski’s Paths

Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time. In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.

Induction of Microalgal Lipids for Biodiesel Production in Tandem with Sequestration of High Carbon Dioxide Concentration

There is no doubt that sufficient energy supply is indispensable for the fulfillment of our fossil fuel crises in a stainable fashion. There have been many attempts in deriving biodiesel fuel from different bioenergy crops including corn, canola, soybean, palm, sugar cane and vegetable oil. However, there are some significant challenges, including depleting feedstock supplies, land use change impacts and food use competition, which lead to high prices and inability to completely displace fossil fuel [1-2]. In recent years, use of microalgae as an alternative biodiesel feedstock has gained renewed interest as these fuels are becoming increasingly economically viable, renewable, and carbon-neutral energy sources. One reason for this renewed interest derives from its promising growth giving it the ability to meet global transport fuel demand constraints with fewer energy supplies without compromising the global food supply. In this study, Chlorella protothecoides microalgae were cultivated under different conditions to produce high-yield biomass with high lipid content which would be converted into biodiesel fuel in tandem with the mitigation of high carbon dioxide concentration. The effects of CO2 using atmospheric and 15% CO2 concentration and light intensity of 35 and 140 µmol m-2s-1 on the microalgae growth and lipid induction were studied. The approach used was to culture microalgal Chlorella protothecoides with inoculation of 1×105 cells/ml in a 250-ml Erlenmeyer flask, irradiated with cool white fluorescent light at ambient temperature. Using these conditions we were able to determine the most suitable operating conditions for cultivating the green microalgae to produce high biomass and lipids. Nile red dye was used as a hydrophobic fluorescent probe to detect the induced intracellular lipids. Also, gas chromatograph mass spectroscopy was used to determine the CO2 concentrations in each culture flask using the closed continuous loop system. The goal was to study how the 15% CO2 concentration was being used up by the microalgae during cultivation. The results show that the condition of high light intensity of 140 µmol m-2s-1 with 15% CO2 concentration obtain high cell concentration of 7 x 105 cells mL-1 after culturing Chlorella protothecoides for 9 to 10 day in both open and closed systems respectively. Higher lipid content was estimated as indicated by fluorescence intensity with 1.3 to 2.5 times CO2 reduction emitted by power plants. The particle size of Chlorella protothecoides increased as well due to induction of lipid accumulation by the cells when culture under these condition (140 µmol m-2s-1 with 15% CO2 concentration).

A Cost Analysis Of Carbon Dioxide Emission Reduction Strategies For New Plants In Michigan's Electric Power Sector

This thesis attempts to find the least-cost strategy to reduce CO2 emission by replacing coal by other energy sources for electricity generation in the context of the proposed EPA’s regulation on CO2 emissions from existing coal-fired power plants. An ARIMA model is built to forecast coal consumption for electricity generation and its CO2 emissions in Michigan from 2016 to 2020. CO2 emission reduction costs are calculated under three emission reduction scenarios- reduction to 17%, 30% and 50% below the 2005 emission level. The impacts of Production Tax Credit (PTC) and the intermittency of renewable energy are also discussed. The results indicate that in most cases natural gas will be the best alternative to coal for electricity generation to realize CO2 reduction goals; if the PTC for wind power will continue after 2015, a natural gas and wind combination approach could be the best strategy based on the least-cost criterion.

Sustainable Energy Production in the United States: Life Cycle Assessment of Biofuels and Bioenergy

The United States of America is making great efforts to transform the renewable and abundant biomass resources into cost-competitive, high-performance biofuels, bioproducts, and biopower. This is the key to increase domestic production of transportation fuels and renewable energy, and reduce greenhouse gas and other pollutant emissions. This dissertation focuses specifically on assessing the life cycle environmental impacts of biofuels and bioenergy produced from renewable feedstocks, such as lignocellulosic biomass, renewable oils and fats. The first part of the dissertation presents the life cycle greenhouse gas (GHG) emissions and energy demands of renewable diesel (RD) and hydroprocessed jet fuels (HRJ). The feedstocks include soybean, camelina, field pennycress, jatropha, algae, tallow and etc. Results show that RD and HRJ produced from these feedstocks reduce GHG emissions by over 50% compared to comparably performing petroleum fuels. Fossil energy requirements are also significantly reduced. The second part of this dissertation discusses the life cycle GHG emissions, energy demands and other environmental aspects of pyrolysis oil as well as pyrolysis oil derived biofuels and bioenergy. The feedstocks include waste materials such as sawmill residues, logging residues, sugarcane bagasse and corn stover, and short rotation forestry feedstocks such as hybrid poplar and willow. These LCA results show that as much as 98% GHG emission savings is possible relative to a petroleum heavy fuel oil. Life cycle GHG savings of 77 to 99% were estimated for power generation from pyrolysis oil combustion relative to fossil fuels combustion for electricity, depending on the biomass feedstock and combustion technologies used. Transportation fuels hydroprocessed from pyrolysis oil show over 60% of GHG reductions compared to petroleum gasoline and diesel. The energy required to produce pyrolysis oil and pyrolysis oil derived biofuels and bioelectricity are mainly from renewable biomass, as opposed to fossil energy. Other environmental benefits include human health, ecosystem quality and fossil resources. The third part of the dissertation addresses the direct land use change (dLUC) impact of forest based biofuels and bioenergy. An intensive harvest of aspen in Michigan is investigated to understand the GHG mitigation with biofuels and bioenergy production. The study shows that the intensive harvest of aspen in MI compared to business as usual (BAU) harvesting can produce 18.5 billion gallons of ethanol to blend with gasoline for the transport sector over the next 250 years, or 32.2 billion gallons of bio-oil by the fast pyrolysis process, which can be combusted to generate electricity or upgraded to gasoline and diesel. Intensive harvesting of these forests can result in carbon loss initially in the aspen forest, but eventually accumulates more carbon in the ecosystem, which translates to a CO2 credit from the dLUC impact. Time required for the forest-based biofuels to reach carbon neutrality is approximately 60 years. The last part of the dissertation describes the use of depolymerization model as a tool to understand the kinetic behavior of hemicellulose hydrolysis under dilute acid conditions. Experiments are carried out to measure the concentrations of xylose and xylooligomers during dilute acid hydrolysis of aspen. The experiment data are used to fine tune the parameters of the depolymerization model. The results show that the depolymerization model successfully predicts the xylose monomer profile in the reaction, however, it overestimates the concentrations of xylooligomers.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Life cycle assessment of residual forestry biomass chips at a power plant: a Portuguese case study

The residual forest biomass (RFB) sector has been experiencing strong development at European level and particularly in Portugal mainly due to the increase of energy production from renewable sources. The aim of this study is to assess the environmental impacts of eucalyptus RFB chips production chain in Portugal. The environmental and economic impact comparison of the processes included in the production chain is presented as well. The environmental impacts were calculated by the life cycle assessment approach described in the ISO 14040 series of standards. The production chain assessed included all processes from eucalyptus forest until the delivery of RFB chips at the power plant. The main conclusion of this study is that eucalyptus wood production is the process that presents the greatest environmental impact through the product life cycle.

An Islanding Detection Method based on Impedance Estimation and Grid Identification for Grid-Tie Distributed Power Generation Systems

Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.

Modelling of a Stirling engine with parabolic dish for thermal to electric conversion of solar energy

Stirling engines with parabolic dish for thermal to electric conversion of solar energy is one of the most promising solutions of renewable energy technologies in order to reduce the dependency from fossil fuels in electricity generation. This paper addresses the modelling and simulation of a solar powered Stirling engine system with parabolic dish and electric generator aiming to determine its energy production and efficiency. The model includes the solar radiation concentration system, the heat transfer in the ther- mal receiver, the thermal cycle and the mechanical and electric energy conversion. The thermodynamic and energy transfer processes in the engine are modelled in detail, including all the main processes occur- ring in the compression, expansion and regenerator spaces. Starting from a particular configuration, an optimization of the concentration factor is also carried out and the results for both the transient and steady state regimes are presented. It was found that using a directly illuminated thermal receiver with- out cavity the engine efficiency is close to 23.8% corresponding to a global efficiency of 10.4%. The com- ponents to be optimized are identified in order to increase the global efficiency of the system and the trade-off between system complexity and efficiency is discussed.

Design of an Efficient Hybrid System for Electricity Production with Supervisory Control

This chapter aims to develop a new method for the economical evaluation of Hybrid Systems for electricity production. The different types of renewable sources are specifically evaluated in the economical performance of the overall equipment. The presented methodology was applied to evaluate the design of a photovoltaic-wind-diesel hybrid system to produce electricity for a community in the neighbourhood of Luanda, Angola. Once the hybrid generator is selected, it is proposed to provide the system with a supervisory control strategy to maximize its operating efficiency.

Revisiting compressed air energy storage.

The use of renewable energies as a response to the EU targets defined for 2030 Climate Change and Energy has been increasing. Also non-dispatchable and intermittent renewable energies like wind and solar cannot generally match supply and demand, which can also cause some problems in the grid. So, the increased interest in energy storage has evolved and there is nowadays an urgent need for larger energy storage capacity. Compressed Air Energy Storage (CAES) is a proven technology for storing large quantities of electrical energy in the form of high-pressure air for later use when electricity is needed. It exists since the 1970’s and is one of the few energy storage technologies suitable for long duration (tens of hours) and utility scale (hundreds to thousands of MW) applications. It is also one of the most cost-effective solutions for large to small scale storage applications. Compressed Air Energy Storage can be integrated and bring advantages to different levels of the electric system, from the Generation level, to the Transmission and Distribution levels, so in this paper a revisit of CAES is done in order to better understand what and how it can be used for our modern needs of energy storage.