THE NOT-SO-GREEN RENEWABLE ENERGY: PREVENTING WASTE DISPOSAL OF SOLAR PHOTOVOLTAIC (PV) PANELS

This Comment provides a background on solar power and PV technology, identifies the toxic components of PV products, and explains how disposal of PV waste poses a threat to the environment. Part II also illustrates how poor management of electronic waste (e-waste) in the U.S. has resulted in environmental pollution - a preventable consequence that can be avoided for the PV industry. Part III advocates a recycling and life-cycle-management approach to regulation because it provides a more sustainable future for the solar industry. Part IV discusses federal and state hazardous waste regulations and demonstrates how these laws are ineffective to regulate PV waste, primarily because they exclude most PV products from regulation and promote disposal over recycling. Part V discusses proposed regulations in California that would modify its hazardous waste program to allow alternative management options. It explains why California should proceed with its proposed regulations that foster reclamation and recycling of solar panels and aim to reduce the volume of hazardous waste entering landfills. Part VI describes how states should take the next step to prevent a future PV waste problem by enacting extended producer responsibility (EPR) laws that focus on the life cycle of PV products and encourages states to subsidize these regimes. That Part also describes the European approach to PV waste management, which is based on a voluntary EPR system and explains why mandatory EPR laws may be required for the U.S

Life cycle assessment of marine power systems onboard roll-on/roll-off cargo ships : framework and case studies

PhD ThesisA study into the environmental impact of marine power systems was performed in proximity with the defined research objectives: (i) present an overview on Annex VI The International Convention for the Prevention of Pollution from Ships, cargo ships, marine power systems and technologies; (ii) review life cycle assessment (LCA) methodology development; (iii) develop an LCA framework for marine power systems; (iv) carry out case studies to determine environmental impact, significant components and critical processes; (v) apply scenario analysis to investigate the sensitivity of the results to selected parameters; and (vi) compare power systems under study to verify their environmental benefits. Built upon literature and the proposed LCA framework, LCA case studies on conventional, retrofit and new-build power systems were performed using a bottom-up integrated system approach, where data were gathered and LCA models were created for individual technologies using GaBi software. Life cycle impact assessment was performed using CML2001, International Reference Life Cycle Data System (ILCD) and Eco-Indicator99 to estimate the environmental impact of the systems. It was found that disposing metal scrap of significant components was the principal cause of ecotoxicity potential, which was the impact category that showed the top two highest indicator results; and operating diesel engines and auxiliary generators or diesel gensets was mainly accounted for other impact categories. When compared with the conventional system, both retrofit and new-build systems consumed less fuels and released less emissions during operation but involved more materials and energy during other life cycle phases, leading to a decline in most impact categories to the detriment of a few burdens. The life cycle of marine power systems must be planned, managed and monitored appropriately for reduced environmental implications. Further research should address limitations presented in this study and explore other factors that might affect the environmental burdens of marine power systems.Research presented in this thesis was delivered for a European Commission funded FP7 project ‘INOvative Energy MANagement System for Cargo SHIP’ (INOMANS²HIP, grant agreement no: 266082)

Heuristic strategies for NFV-enabled renewable and non-renewable energy management in the future IoT world

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The ever-growing energy demand and the CO2 emissions caused by energy production and consumption have become critical concerns worldwide and drive new energy management and consumption schemes. In this regard, energy systems that promote green energy, customer-side participation enabled by the Internet of Things (IoT) technologies, and adaptive consumption mechanisms implemented on advanced communications technologies such as the Network Function Virtualization (NFV) emerge as sustainable and de-carbonized alternatives. On these modern schemes, diverse management algorithmic solutions can be deployed to promote the interaction between generation and consumption sides and optimize the use of available energy either from renewable or non-renewable sources. However, existing literature shows that management solutions considering features such as the dynamic nature of renewable energy generation, prioritization in energy provisioning if needed, and time-shifting capabilities to adapt the workloads to energy availability present a complexity NP-Hard. This condition imposes limits on applicability to a small number of energy demands or time-shifting values. Therefore, faster and less complex adaptive energy management approaches are needed. To meet these requirements, this paper proposes three heuristic strategies: a greedy strategy (GreedyTs), a genetic-algorithm-based solution (GATs), and a dynamic programming approach (DPTs) that, when deployed at the NFV domain, seeks the best possible scheduling of demands that lead to efficient energy utilization. The performance of the algorithmic strategies is validated through extensive simulations in several scenarios, demonstrating improvements in energy consumption and processing of demands. Additionally, simulation results reveal that the heuristic approaches produce high-quality solutions close to the optimal while executing among two and seven orders of magnitude faster and with applicability to scenarios with thousands and hundreds of thousands of energy demands.This work was supported by the Ministerio de Ciencia e Innovación of the Spanish Government under Project PID2019-108713RB-C51. The work of Christian Tipantuña was supported in part by the Escuela Politécnica Nacional and in part by Secretaría de Educación Superior, Ciencia, Tecnología e Innovación (SENESCYT).Peer ReviewedPostprint (published version

Proceedings: Fourth Parabolic Dish Solar Thermal Power Program Review

The results of activities within the parabolic dish technology and applications development program are presented. Stirling, organic Rankine and Brayton module technologies, associated hardware and test results to date; concentrator development and progress; economic analyses; and international dish development activities are covered. Two panel discussions, concerning industry issues affecting solar thermal dish development and dish technology from a utility/user perspective, are also included

Assessment and Exploitation of the Inherent Value of Waste Electrical and Electronic Equipment (WEEE) for Circular Economy

Waste electrical and electronic equipment (WEEE) represents a global environmental and resource-efficiency crisis. However, WEEE is a valuable urban mine of economically, strategically and environmentally important materials e.g. precious metals (PMs) and critical raw materials (CRMs). Economic value derived from WEEE can drive solutions to the ‘WEEE problem’ which are conducive to circular economy, enhance global resource-efficiency, and generate environmental and social benefits. This thesis examines the value of WEEE, and methods for its exploitation to the benefit of global sustainability. The ‘WEEE problem’ is examined in the context of global sustainability, considering environmental & resource-efficiency implications and linear resources use by the electrical & electronic equipment (EEE) industry. Solutions are considered which exploit WEEE as an ‘urban mine’ and embrace circular economy.Within this context, recycling potential of future WEEE is evaluated through projections of PM & Cu content of PCBs, based on temporal trends in historic RAM modules. CRMs are then identified in WEEE and methods of enhancing their recovery through intervention in pre-processing stages of recycling are evaluated. An industrial symbiosis process which recovers Pt from waste thermocouples for use in solar cells is presented as an example of the greater value generation potential offered by circular economy and the potential of such processes to overcome barriers to CRM recovery. Challenges and opportunities in lifecycle optimisation of printable photovoltaics for circular economy is considered as a means of enhancing the industrial ecology of this industry to avoid WEEE generation, reduce primary materials demand and enhance the value derived from these technologies at all stages of their lifecycles. Appropriate battery selection for solar off-grid systems in South Africa is then considered, demonstrating that greater value can be derived from EEE for local economies if compatibility of technologies with local skills and infrastructure for in-use and EoL management

A forecast of the Cloud

IT ses ofta som en del av lösningen för att uppnå ett hållbart samhälle genom till exempel minskat resande, optimering av industri- och jordbruksprocesser, intelligenta elmätare och smarta hem. Något man sällan reflekterar över är att ITbranschen själv också bidrar till elanvändningen. Ett nytt fenomen inom IT-världen är molnet som ger möjlighet till som det verkar outtömliga resurser i form av lagrings- och beräkningskapacitet, konstant uppkoppling och snabb överföring. Det finns många definitioner av molnet men om man ser på det materiellt består det av datahallar i olika storlek samt fasta och trådlösa nätverk som drar el dygnet runt. Om användningen av molntjänster ökar – hur mycket kommer elanvändningen öka och med den också den globala uppvärmningen? I denna studie kommer molnet definieras, materialiseras och kvantifieras för att kunna bedöma dess elbehov idag och i framtiden. Lagar och regler för energieffektivisering kommer undersökas och framtida prognoser tas fram genom tillväxtmodeller. De huvudsakliga resultaten är: - Det finns inga lagar för hur energieffektiva datahallar måste vara, även om det görs en del inom området på frivillig basis och företag tar på sig egna miljömål. Europeiska unionen inkluderade vissa delar av servrar i ekodesigndirektivet år 2014 vilket visar på att problemet har börjat tas upp. - Användningen av molnet kommer öka explosionsartat i framtiden och det finns stor potential för energieffektivisering när det gäller lagring, bearbetning och överföring av data. Beroende på hur mycket som energieffektiviseras kan molnet komma att konsumera mellan 5 000 och 10 000 TWh år 2040. Detta kan jämföras med hela IT-branschen som 2010 drog mellan 700 och 1 000 TWh. Om man jämför molnet och traditionell IT är molnet oftast mer energieffektivt bland annat därför att resurser förbrukas efter behov och servrar utnyttjas optimalt. Det finns alltså ännu större potential för energieffektivisering om hela IT-sektorn inkluderas. - Om inte energieffektivisering sker alls kommer molnets energiförbrukning öka bortom greppbara magnituder. Det finns dock också studier som pekar på att den totala energikonsumtionen kan minska sett från idag, även om användningen av molnet ökar, då teknik med mycket bättre energiprestanda håller på att utvecklas. - Då dagens lagstiftning inte täcker in energieffektivisering ligger ett stort ansvar på företag att göra detta på frivillig basis, vilket till viss del motiveras av att de sparar pengar genom att energieffektivisera. Det är dock mycket viktigt att denna energiåtgång uppmärksammas och att den inte tillåts skena iväg i framtiden.Information and communication technology (ICT) is often seen as part of the solution for a sustainable society, for example through reduced travel, optimization of industrial and agricultural processes, smart meters and smart homes. However, something usually left unconsidered is the electricity consumption of ICT itself. A new phenomenon of the ICT industry is the Cloud that enables seemingly inexhaustible resources in terms of storage and computing capacity, constant connection and fast transfer. There are many definitions of cloud but if looked at from a material point of view it consists of data centers in different sizes as well as wired and wireless networks that consumes electricity. If usage of cloud services increase - how much will electricity consumption and with it global warming increase? In this study the cloud is defined, materialized and quantified in order to estimate its electricity demand today and in the future. Laws and regulations for energy efficiency will be examined and future forecasts are created with the use of growth models. The main results are: - There are no regulations of how energy efficient data centers must be, even though some companies set their own environmental goals and voluntary projects are carried out. The European Union included some parts of servers in the Ecodesign Directive in 2014, which shows that the problem has begun to be addressed. - The usage of the cloud will increase dramatically in the future and there is great potential to improve energy efficiency in terms of storage, processing and transmission of data. Depending on how energy efficient the cloud will be it can consume between 5 000 and 10 000 TWh in 2040. This can be compared to the entire ICT industry which consumed between 700 and 1 000 TWh in 2010. If the cloud is compared with traditional IT it is usually more energy efficient as resources are pooled and used when needed and servers are utilized optimally. Therefore there is even greater potential for improving energy efficiency if the entire ICT sector is included. - If there are no energy efficiency improvements at all the cloud’s energy consumption will increase beyond graspable magnitudes. However, there are also studies that indicate that the total energy consumption can decrease in the future, even though the use of the cloud increases, due to new efficient technologies currently under development. - As current regulations do not include energy efficiency of data centers, a huge responsibility is placed at companies to do this on a voluntary basis. The companies do however have a self-interest to improve energy efficiency as it saves them money - but is it enough? It is very important that this energy consumption is recognized and is not allowed to increase out of control in the future.Den ökande användningen av onlinetjänster medför att elkonsumtionen från datahallar och nätverk kommer skjuta i höjden om vi inte energieffektiviserar. Idag saknas det generellt lagar om hur effektiva datacenter måste vara. Ett enormt ansvar läggs på att företag själva är förutseende och satsar på energieffektiv teknik. Det finns dock stora möjligheter att spara energi, både för datahallar och nätverk - om viljan finns

Contributions to energy-aware demand-response systems using SDN and NFV for fog computing

Ever-increasing energy consumption, the depletion of non-renewable resources, the climate impact associated with energy generation, and finite energy-production capacity are important concerns worldwide that drive the urgent creation of new energy management and consumption schemes. In this regard, by leveraging the massive connectivity provided by emerging communications such as the 5G systems, this thesis proposes a long-term sustainable Demand-Response solution for the adaptive and efficient management of available energy consumption for Internet of Things (IoT) infrastructures, in which energy utilization is optimized based on the available supply. In the proposed approach, energy management focuses on consumer devices (e.g., appliances such as a light bulb or a screen). In this regard, by proposing that each consumer device be part of an IoT infrastructure, it is feasible to control its respective consumption. The proposal includes an architecture that uses Network Functions Virtualization (NFV) and Software Defined Networking technologies as enablers to promote the primary use of energy from renewable sources. Associated with architecture, this thesis presents a novel consumption model conditioned on availability in which consumers are part of the management process. To efficiently use the energy from renewable and non-renewable sources, several management strategies are herein proposed, such as the prioritization of the energy supply, workload scheduling using time-shifting capabilities, and quality degradation to decrease- the power demanded by consumers if needed. The adaptive energy management solution is modeled as an Integer Linear Programming, and its complexity has been identified to be NP-Hard. To verify the improvements in energy utilization, an optimal algorithmic solution based on a brute force search has been implemented and evaluated. Because the hardness of the adaptive energy management problem and the non-polynomial growth of its optimal solution, which is limited to energy management for a small number of energy demands (e.g., 10 energy demands) and small values of management mechanisms, several faster suboptimal algorithmic strategies have been proposed and implemented. In this context, at the first stage, we implemented three heuristic strategies: a greedy strategy (GreedyTs), a genetic-algorithm-based solution (GATs), and a dynamic programming approach (DPTs). Then, we incorporated into both the optimal and heuristic strategies a prepartitioning method in which the total set of analyzed services is divided into subsets of smaller size and complexity that are solved iteratively. As a result of the adaptive energy management in this thesis, we present eight strategies, one timal and seven heuristic, that when deployed in communications infrastructures such as the NFV domain, seek the best possible scheduling of demands, which lead to efficient energy utilization. The performance of the algorithmic strategies has been validated through extensive simulations in several scenarios, demonstrating improvements in energy consumption and the processing of energy demands. Additionally, the simulation results revealed that the heuristic approaches produce high-quality solutions close to the optimal while executing among two and seven orders of magnitude faster and with applicability to scenarios with thousands and hundreds of thousands of energy demands. This thesis also explores possible application scenarios of both the proposed architecture for adaptive energy management and algorithmic strategies. In this regard, we present some examples, including adaptive energy management in-home systems and 5G networks slicing, energy-aware management solutions for unmanned aerial vehicles, also known as drones, and applicability for the efficient allocation of spectrum in flex-grid optical networks. Finally, this thesis presents open research problems and discusses other application scenarios and future work.El constante aumento del consumo de energía, el agotamiento de los recursos no renovables, el impacto climático asociado con la generación de energía y la capacidad finita de producción de energía son preocupaciones importantes en todo el mundo que impulsan la creación urgente de nuevos esquemas de consumo y gestión de energía. Al aprovechar la conectividad masiva que brindan las comunicaciones emergentes como los sistemas 5G, esta tesis propone una solución de Respuesta a la Demanda sostenible a largo plazo para la gestión adaptativa y eficiente del consumo de energía disponible para las infraestructuras de Internet of Things (IoT), en el que se optimiza la utilización de la energía en función del suministro disponible. En el enfoque propuesto, la gestión de la energía se centra en los dispositivos de consumo (por ejemplo, electrodomésticos). En este sentido, al proponer que cada dispositivo de consumo sea parte de una infraestructura IoT, es factible controlar su respectivo consumo. La propuesta incluye una arquitectura que utiliza tecnologías de Network Functions Virtualization (NFV) y Software Defined Networking como habilitadores para promover el uso principal de energía de fuentes renovables. Asociada a la arquitectura, esta tesis presenta un modelo de consumo condicionado a la disponibilidad en el que los consumidores son parte del proceso de gestión. Para utilizar eficientemente la energía de fuentes renovables y no renovables, se proponen varias estrategias de gestión, como la priorización del suministro de energía, la programación de la carga de trabajo utilizando capacidades de cambio de tiempo y la degradación de la calidad para disminuir la potencia demandada. La solución de gestión de energía adaptativa se modela como un problema de programación lineal entera con complejidad NP-Hard. Para verificar las mejoras en la utilización de energía, se ha implementado y evaluado una solución algorítmica óptima basada en una búsqueda de fuerza bruta. Debido a la dureza del problema de gestión de energía adaptativa y el crecimiento no polinomial de su solución óptima, que se limita a la gestión de energía para un pequeño número de demandas de energía (por ejemplo, 10 demandas) y pequeños valores de los mecanismos de gestión, varias estrategias algorítmicas subóptimos más rápidos se han propuesto. En este contexto, en la primera etapa, implementamos tres estrategias heurísticas: una estrategia codiciosa (GreedyTs), una solución basada en algoritmos genéticos (GATs) y un enfoque de programación dinámica (DPTs). Luego, incorporamos tanto en la estrategia óptima como en la- heurística un método de prepartición en el que el conjunto total de servicios analizados se divide en subconjuntos de menor tamaño y complejidad que se resuelven iterativamente. Como resultado de la gestión adaptativa de la energía en esta tesis, presentamos ocho estrategias, una óptima y siete heurísticas, que cuando se despliegan en infraestructuras de comunicaciones como el dominio NFV, buscan la mejor programación posible de las demandas, que conduzcan a un uso eficiente de la energía. El desempeño de las estrategias algorítmicas ha sido validado a través de extensas simulaciones en varios escenarios, demostrando mejoras en el consumo de energía y el procesamiento de las demandas de energía. Los resultados de la simulación revelaron que los enfoques heurísticos producen soluciones de alta calidad cercanas a las óptimas mientras se ejecutan entre dos y siete órdenes de magnitud más rápido y con aplicabilidad a escenarios con miles y cientos de miles de demandas de energía. Esta tesis también explora posibles escenarios de aplicación tanto de la arquitectura propuesta para la gestión adaptativa de la energía como de las estrategias algorítmicas. En este sentido, presentamos algunos ejemplos, que incluyen sistemas de gestión de energía adaptativa en el hogar, en 5G networkPostprint (published version

Accommodating a High Penetration of PHEVs and PV Electricity in Residential Distribution Systems

Global warming is threatening the world’s delicate ecosystems to the point where the extinction of numerous species is becoming increasingly likely. Experts have determined that avoiding such a disaster requires an 80% reduction in the 1990 levels of global greenhouse gas emissions by 2050. The problem has been exacerbated by the booming demand for electrical energy. This situation creates a complex dilemma: on the one hand, energy sector emissions must be decreased; on the other, electrical energy production must be increased to meet the growing demand. The use of renewable emission-free sources of electrical energy offers a feasible solution to this dilemma. Solar energy in particular, if properly utilized, would be an effective means of meeting worldwide electricity needs. Another viable component of the solution is to replace gasoline-powered vehicles with plug-in hybrid electric vehicles (PHEVs) because of their potential for significantly reducing greenhouse gas emissions from the transportation sector. It was once believed that integrating solar electricity into distribution systems would be relatively straightforward; however, when the penetration level of photovoltaic (PV) systems began to increase, power utilities faced new and unexpected problems, which arose primarily due to the weak chronological coincidence between PV array production and the system peak demand. PV arrays produce their peak output at noon, during low demand periods, resulting in individual instances when the net PV production exceeds the system net demand. Power then flows from low voltage (LV) to medium voltage (MV) networks. Such reverse power flow results in significant over voltages along distribution feeders and excessive power losses. For PHEVs, the situation is the direct opposite because peak demand periods coincide closely with the hours during which the majority of vehicles are parked at residences and are thus probably being charged. This coincidence causes substantial distribution equipment overloading, hence requiring costly system upgrades. Although extensive research has been conducted with respect to the individual impacts of PV electricity and PHEVs on distribution networks, far too little attention has been paid to studying the interaction between these two technologies or the resulting aggregated impacts when both operate in parallel. The goal of the research presented in this thesis is to fill this gap by developing a comprehensive benchmark that can be used to analyze the performance of the distribution system under a high penetration of both PV systems and PHEVs. However, the uncertainties associated with existing electrical loads, the PHEV charging demand, and the PV array output complicate the achievement of this goal and necessitate the development of accurate probabilistic models to express them. The establishment of such models and their use in the development of the proposed benchmark represent core contributions of the research presented in this thesis. Assessing the anticipated impacts of PHEVs and PV electricity on distribution systems is not the only challenge confronting the electricity sector. Another issue that has been tackled by numerous researchers is the formulation of solutions that will facilitate the integration of both technologies into existing networks. The work conducted for this thesis presents two different solutions that address this challenge: a traditional one involving the use of energy storage systems (ESSs), and an innovative one that hinges on a futuristic novel bilayer (AC-DC) distribution system architecture. In the first solution, the author proposes using ESSs as a possible means of mitigating the aggregated impacts of both PV electricity and PHEVs. This goal can be achieved by storing PV electricity generated during low demand periods, when reverse power flow is most likely to occur, in small-scale dispersed ESSs located at secondary distribution transformers. Thereafter, this energy is then reused to meet part of the PHEV charging demand during peak periods when this demand is most likely to overload distribution equipment. While this solution would kill two birds with one stone, the uncertainties inherent in the system make its implementation difficult. In this respect, a significant contribution of the work presented in this thesis is the use of the previously developed probabilistic benchmark to determine the appropriate sizes, locations, and operating schedules of the proposed ESSs, taking into account the different sources of uncertainty in the system. In the second solution, the author proposes a novel bilayer (AC-DC) architecture for residential distribution systems. With the proposed architecture, the distribution system becomes a bilayer system composed of the traditional AC layer for interfacing with existing system loads, plus an embedded DC layer for interfacing with PV arrays and PHEVs. A centralized bidirectional converter links the two layers and controls the power flow between them. The proposed solution offers a reasonable compromise that enables existing networks to benefit from both AC and DC electricity, thus metaphorically enjoying the best of both worlds. As with the first solution, the uncertainties that characterize the distribution system also create obstacles to the implementation of the proposed architecture. Another important contribution of the research presented in this thesis is the design and validation of the proposed bilayer system, with consideration of these different uncertainties. Finally, the author compares the strengths and weaknesses of both solutions to determine the better alternative