Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach

We propose a system level approach to value the impact on costs of the integration of intermittent renewable generation in a power system, based on expected breakeven cost and breakeven cost risk. To do this, we carefully reconsider the definition of Levelized Cost of Electricity (LCOE) when extended to non-dispatchable generation, by examining extra costs and gains originated by the costly management of random power injections. We are thus lead to define a ‘system LCOE’ as a system dependent LCOE that takes properly into account intermittent generation. In order to include breakeven cost risk we further extend this deterministic approach to a stochastic setting, by introducing a ‘stochastic system LCOE’. This extension allows us to discuss the optimal integration of intermittent renewables from a broad, system level point of view. This paper thus aims to provide power producers and policy makers with a new methodological scheme, still based on the LCOE but which updates this valuation technique to current energy system configurations characterized by a large share of non- emissions, the proposed methodology can be used as powerful tool of analysis for assessing environmental and energy policies

Quantifying the Value of Renewable Energy as a Hedge Against the Volatility of Natural Gas Prices in Wisconsin

This research study investigated whether adding renewable energy to the grid in Wisconsin would lower or maintain electricity prices through 2050. Since Wisconsin adopted a plan to become carbon neutral by 2050, this study explored different paths to achieving this goal. This study examined three different paths or scenarios, specifically base case, optimal, and carbon-free, using an Excel-built toolkit. The toolkit allowed the researcher to customize all major assumptions, making it a practical tool that could assist electric utilities in the future in determining whether additional renewable energy would indeed lower and stabilize electricity prices. Applying different statistical tools to the scenarios, the study discovered that the base case scenario would achieve 25 percent renewable energy by 2050 with the projected electricity price of 14.5 cents per kilowatt hour (kWh), the optimal model would create 33 percent renewable energy with the electricity price of 16.9 cents per kWh, and the carbon-free scenario would create 100 percent renewable energy by 2050 with the projected electricity price of 21 cents per kWh. The hedging premium exhibits higher volatility than the natural gas prices as the coefficient of variance (COV) exhibits the volatility of the hedging costs at 883.33, meaning the end users need to pay a 1-cent premium per kWh. Assuming that Wisconsin’s grid has a medium capacity to absorb large quantities of renewable energy, this study estimates that under the base case scenario, adding one kilowatt of renewable energy decreases the price of electricity by 1.4 cents per kWh. The optimal scenario keeps the electricity prices almost the same, 0.03 cents per kWh, compared to the no additional renewable energy scenario. Under the carbon-free scenario, the most aggressive scenario in terms of adding renewables, electricity prices are estimated to rise an average of 3 cents per kWh

Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Open accessThis paper reports a new methodology and results on the forecast of the numerical value of the fat tail(s) in asset returns distributions using the irrational fractional Brownian motion model. Optimal model parameter values are obtained from fits to consecutive daily 2-year period returns of S&P500 index over [1950–2016], generating 33-time series estimations. Through an econometric model,the kurtosis of returns distributions is modelled as a function of these parameters. Subsequently an auto-regressive analysis on these parameters advances the modelling and forecasting of kurtosis and returns distributions, providing the accurate shape of returns distributions and measurement of Value at Risk

Barriers to Renewable Energy Investment in the Indonesian Power Sector

Indonesia has set ambitious targets of increasing the share of renewable energy in electricity supply and reducing greenhouse gas emissions relative to a baseline. But despite abundant renewable energy resources and policies to promote renewable energy, the country has experienced only slow additions in renewable electricity supply. Future expansions in generation capacity are planned to rely heavily on coal-based power supply. This thesis examines the barriers to renewable energy in Indonesia, provides a detailed case study on the effectiveness of specific renewable energy policy instruments in a developing economy context and applies mean variance portfolio (MVP) theory to analyse power supply outcomes. This thesis provides a historical analysis of the effectiveness of policies to incentivise renewable energy supply in the Indonesian electricity sector. Empirical analysis of supply trends covers the period 1990–2015, while perceptions of the effectiveness of regulatory incentives are based on stakeholder interviews conducted in 2011 and 2012. The main finding is that a combination of regulatory uncertainty in the Indonesian power sector, financial weakness of the national electricity utility Perusahaan Listrik Negara (PLN) and ineffective feed-in tariffs have had a dampening effect on renewable energy investment. In the absence of credible, mandatory renewable energy targets for PLN, the utility has prioritised coal and gas over renewables. An important reason being that renewable power projects carry higher upfront investment costs and, until now, have been more expensive per unit of power output. Feed-in tariffs have been rendered ineffective as they were set at levels too low to act as premium prices, with PLN and independent power producers locked into lengthy negotiations over contracts, thus slowing project implementation. Taking the long view, the thesis uses MVP theory to analyse the risk-mitigation potential of renewables in PLN’s future electricity supply mix. This analysis identifies the cost risk trade-off of various electricity mix scenarios and provides a quantitative measure to assess the potential benefits from diversifying energy production. The findings are that the average system costs for various future technologies are in a narrow range, with renewables cheaper than conventional generation technologies, especially when carbon costs are included. The risk of investing in the power sector, defined as cost risk and measured by the standard deviation of past cost streams, differs significantly across generation technologies and is lower for renewables. Energy portfolios containing a large share of renewables combined with energy efficiency measures are now preferable in cost and risk terms, although at higher discount rates the cost advantage is less pronounced. This thesis concludes that policy reforms need to focus on continuing to move towards cost-reflective tariffs to improve PLN’s financial footing. Combined with continued declining costs of renewables, feed-in tariffs could become more effective when set at levels that truly act as premium prices. They could be combined with quantitative instruments such as renewable portfolio standards to help overcome institutional bias against renewables within PLN, especially in a period of transiting towards a cost-effective tariff system and phasing out of subsidies

Sustainable Low-Carbon Isolated Island Electricity Systems - Policy and Investment Impacts Assessed Using System Dynamics

This thesis presents a novel System Dynamics (SD) policy and investment analysis framework for future low-carbon electricity systems, using an electrically isolated island system as its case study. Current electricity systems are undergoing a long-term transition towards reduced fossil fuel use, primarily driven by high fuel costs, environmental concerns and the desire for energy security. These systems are facing a number of evolving policy drivers: most notably, current attempts to pursue higher levels of renewable energy sources, greater energy efficiency and other supporting technologies. Emerging challenges are shaping the low-carbon objectives of future electricity systems and the ensuing implications for future policy and investment decisions. This thesis presents a number of critical policy recommendations allied with longer-term investment observations, evolving from the nexus between the environmental and energy security concerns of an island-based electricity system. Island systems such as São Miguel, are small enough to be understood while being large enough to reveal highly complex structures and inherent time and spatial interactions within and between social, economic and technical factors. It is argued that a systematic SD-based approach can reveal possible system structure trajectories, with such insights assisting the understanding of overall sustainability while recognising emergent challenges and behaviours. The thesis shows that learning-by-doing renewables cost reductions exists but are not very significant in island electricity systems. Additionally, it shows that setting low-carbon policy targets is beneficial for emissions reductions, but meeting these targets too early is either inefficient or impractical if targets are unrealistic. Critical evaluations of endogenous electricity demand growth and the system capacity margin are provided, which highlights consequential policy challenges for island-based systems. The most important and influential low-carbon agendas giving endogenous impacts on electricity demand are elaborated. The thesis also confirms that more effective policies, for sustained renewables uptake and improved investor decision-making for the generation mix, can be achieved. Insights distilled from smaller electricity systems can help frame the outlook of larger systems

An Integrated Energy Economic Interaction Model with Application to Egypt

Traditional bottom-up energy models have been widely applied to date to assess the impact of the future energy technologies over a specific time horizon, quantifying the direct economic and environmental implications caused by the evolution of the energy sector. However, such approaches ignore the interactions that the energy sector has with other sectors in the economy, hence failing in quantifying the global impact associated with their technologies: this may produce an unfortunate bias in the definition of future energy and environmental policies. The present study assesses, on a nationwide economy scale, the economic and environmental impacts due to the optimal future power generation mix in Egypt, by soft-linking a bottom-up, technology-rich model (OSeMOSYS) with a top-down Input-Output Analysis model (IOA, based on the EORA 26 dataset). Based on the OSeMOSYS energy modeling framework, the OSeMOSYS-Egypt model is developed. The least cost power generation mix is determined for two different electricity demand forecasts, based on both the New Policies demand forecast scenario developed by International Energy Agency and the market research performed by Business Monitor International. The robustness of the obtained results is assessed through a sensitivity analysis on the main exogenous parameters, including costs, efficiency and production targets of energy technologies, capital discount rate, water and natural gas resources availability. The evolution of the Egyptian power sector in years 2018 to 2040 is analyzed: results of the bottom-up energy model are adopted as exogenous parameters to the top-down multi-sector model, as a way of coupling the two aforementioned models. It is revealed that Combined Cycles, Wind, and Photovoltaic rooftop systems are viable technologies that should be considered in the future Egypt’s power generation mix. In particular, among Egypt’s abundant renewable energy resources, it is shown that wind power technology comes first in achieving the proposed target on renewables penetration in the country’s generation mix, and it might be a feasible alternative to replace part of the natural gas share. To increase the accuracy of the analysis, the original OSeMOSYS framework has been enhanced by imposing the discount rate on capital investments for the energy technologies, as a time dependent exogenous variable; in developing countries in general and in Egypt in particular, discount rates have been known to fluctuate widely. The derived power generation mix, predicted by the bottom-up model, has been applied to the IOA model in the form of a change in energy technology mix and a change in final demand of electricity. To account for the growth in the national GDP during the temporal planning horizon, an econometric function that relates the growth in GDP to increase in the production of electricity is formulated. Besides the results of the energy model, this approach enables the decision maker to assess the expected primary energy requirements, GHG emissions and water use induced by the evolution of the energy mix in a broader perspective. It is worth to note that, the results of the bottom-up energy optimization model indicates that the anticipated increase in the penetration of renewables in the power generation mix, would decrease the primary non-renewable energy consumption and GHG emissions directly caused by the power generation sector over the considered temporal planning horizon (2018-2040). However, the application of the IOA model reveals that decarbonizing the power sector alone is not sufficient in achieving neither, the decoupling of the GDP growth and the total primary energy consumption, nor the GHG emissions within the Egyptian economy

State Agencies

Dear Mr. Ellis: At your request we have reviewed the 2013 Ten-Year Site Plans ofthe electric utilities. The Department of Economic Opportunity's review focused on potential sites for future power generation, and the compatibility of those sites with the applicable local comprehensive plan, including the adopted future land use map, adjacent land uses, and natural resources on or adjacent to the potential sites. Our review ofthe 2013 Ten-Year Site Plans addressed ten potential power plant sites identified in the Ten-Year Site Plans ofthe following utilities: Florida Power & Light Company, Gulf Power Company, and Seminole Electric Cooperative. None of the potential sites were found to be incompatible with the applicable local comprehensive plan. Should you have any questions regarding these comments, please call Scott Rogers

From Sweden to the world: Analysis of future low-carbon electricity systems

The increasing urgency of addressing climate change, along with the sustained cost declines in wind and solar power, has led to a rapid expansion in their deployment to decarbonize the electricity sector. In cost-optimal scenarios for future low-carbon electricity systems, wind and solar often serve as the cornerstone of electricity supply. Although many studies have investigated a future low-carbon electricity system based on wind and solar, there are still several important aspects that are not well understood for such a future system, e.g., uncertainty in future electricity demand patterns, potential for trade in renewable energy, the spatial scope for resource sharing and the role of nuclear power. This thesis investigates these aspects and their potential impacts on developing a low-carbon electricity system.\ua0\ua0\ua0\ua0\ua0 This thesis reveals that varied electricity demand patterns affect only slightly the electricity system cost for Europe, except for the case of summer peak, where the system cost may increase by up to 8%. The change in demand pattern is generally more consequential to the electricity supply mix than the system cost. Notably, the increased electric cooling demand may change the demand pattern such that the hourly electricity demand is better correlated with the output of solar PV. Through analyzing seven different regions under various CO2 emission targets, this thesis shows that solar PV is the most cost-optimal generation technology for meeting the cooling demand. In addition, to have a more realistic assessment of renewable energy potential, this thesis introduces a new metric “Renewable levelized cost of electricity available for export”, which incorporates heterogeneous discount rates, electricity demand, and land-use requirements. By applying this metric to most of the countries in the world, this thesis shows that countries with significant potential for renewable energy export include the US, China, and Saudi Arabia. Furthermore, this thesis shows that the benefit of an intercontinental super grid, as suggested by the One Sun One World One Grid initiative, is rather limited. Allowing for long-distance intercontinental electricity trade reduces the electricity system cost by 0-5% compared to the case where the continents are isolated from each other. This thesis also shows that integrating different continents always reduces the integration of solar PV, which indicates that an intercontinental super grid is not a cost-effective variation management strategy for solar power. Finally, this thesis shows that including nuclear power in the electricity system reduces the nodal net average system cost by 4% for Sweden. This implies that the economic rationale for Sweden as a country to invest in nuclear power is limited if there is a transition towards a low-carbon electricity system in Europe. This thesis provides practical information about demand profile treatment for modeling practice, introduces a useful metric for renewable energy trade potential assessment, and generates valuable insights about deploying solar PV to power cooling, and investment in super grid and nuclear power

Contribution to the development of mathematical programming tools to assist decision-making in sustainability problems

L'activitat humana està excedint la capacitat de resposta de la Terra, el que pot tenir implicacions perjudicials per al futur benestar humà i del medi ambient. Sens dubte, severs canvis estructurals seran necessaris, el que exigeix prendre solucions eficaces davant els problemes emergents de sostenibilitat. En aquest context, aquesta tesi es centra en dues transformacions clau per re-connectar el desenvolupament humà amb el progrés sostenible: la "seguretat alimentària sostenible", desacoblant la intensificació agrícola de l'ús insostenible dels recursos; i el "model energètic sostenible", donant suport al canvi cap a una economia respectuosa amb el medi ambient. El marc metodològic consisteix a abordar diferents problemes mitjançant el desenvolupament d'eines sistemàtiques de programació matemàtica amb l'objectiu de donar suport a la presa de decisions i la formulació de polítiques conduents a la consecució del desenvolupament sostenible. Aquesta tesi doctoral inclou quatre contribucions principals en forma d'eines de decisió i suport de polítiques prou flexibles com per abordar diferents casos d'estudi. En primer lloc, es proposa una eina multiobjectiu per assignar àrees de cultiu considerant simultàniament criteris productius i mediambientals. En segon lloc, es proposa un model multiperíode per determinar plans de cultiu òptims i subsidis efectius per tal de promoure pràctiques agrícoles sostenibles. En tercer lloc, es proposa una metodologia per a analitzar la sostenibilitat que permet avaluar sistemes muticriteri i proporciona potencials millores d'acord amb els principis de la sostenibilitat. En quart lloc, es proposa un nou enfocament basat en l'optimització d'accions cooperatives amb l'objectiu de promoure i enfortir la cooperació internacional en la lluita contra el canvi climàtic La informació derivada de la investigació, com la presentada en aquesta tesi, pot tenir un paper fonamental en la transició cap a una nova era en la qual l'economia, la societat i el medi ambient coexisteixin com a pilars clau del desenvolupament sostenible.La actividades humanas están excediendo la capacidad de carga de la Tierra, lo que puede potencialmente generar implicaciones perjudiciales para el futuro bienestar humano y del medio ambiente. Sin duda son necesarios profundos cambios estructurales, lo que exige tomar soluciones eficaces ante los problemas emergentes de sostenibilidad. En este contexto, esta tesis se centra en dos transformaciones clave para reconectar el desarrollo humano con el progreso sostenible: la "seguridad alimentaria sostenible", desacoplando la intensificación agrícola del uso insostenible de los recursos; y el " modelo energético sostenible", apoyando el cambio hacia una economía respetuosa con el medio ambiente. El marco metodológico consiste en abordar distintos problemas mediante el desarrollo de herramientas sistemáticas de programación matemática cuyo objetivo es apoyar la toma de decisiones y la formulación de políticas tendentes hacia la consecución del desarrollo sostenible. La tesis incluye cuatro contribuciones principales en forma de herramientas de decisión y apoyo de políticas suficientemente flexibles para abordar diferentes casos de estudio. En primer lugar, se propone una herramienta multiobjetivo para asignar áreas de cultivo considerando simultáneamente criterios productivos y medioambientales. En segundo, se propone un modelo multiperiodo para determinar planes de cultivo óptimos y subsidios efectivos con el fin de promover prácticas agrícolas sostenibles. En tercero, se propone una metodología para realizar análisis de sostenibilidad que permite evaluar sistemas muticriterio y proporciona potenciales mejoras de acuerdo con principios de sostenibilidad. En cuarto lugar, se propone un nuevo enfoque basado en la optimización de acciones cooperativas con el objetivo de promover y fortalecer la cooperación internacional en la lucha contra el cambio climático La información derivada de la investigación, como la presentada en esta tesis, puede desempeñar un papel fundamental en la transición hacia una nueva era en la que la economía, la sociedad y el medio ambiente coexistan como pilares clave del desarrollo sostenible.Impacts from human activities are exceeding the Earth’s carrying capacity, which may lead to irreversible changes posing a serious threat to future human well-being and the environment. There is no doubt that an urgent shift is needed for sustainability, which calls for effective solutions when facing ongoing and emerging sustainability challenges. Against this background, this thesis focuses on two key structural transformations needed to reconnect the human development to sustained progress: the “food security transformation”, through decoupling the intensification of agricultural production from unsustainable use of resources; and the “clean energy transformation”, supporting the transition towards a more environmentally friendly economy. Methodologically, different sustainability issues are tackled by developing systematic mathematical programming tools aiming at supporting sustainable decision and policy-making which ultimately will lead to the development of more efficient mechanisms to foster a sustainable development. This thesis includes four major contributions in the form of decision and policy- support tools which are flexible and practical enough to address different case studies towards a more sustainable agriculture and energy future. First, a multi-objective tool is proposed which allows allocating cropping areas simultaneously maximizing the production and minimizing the environmental impact on ecosystems and resources. Second, a multi-period model is proposed which allows determining optimal cropping plans and effective subsidies to promote agricultural practices beneficial to the climate and the environment. Third, a novel methodology tailored to perform sustainability assessments is proposed which allows evaluating multi-criterion systems and providing improvements targets for such systems according to sustainability principles. Fourth, an optimised cooperative approach is proposed to promote and strengthen international cooperation in the fight against climate change. Research-based work as the one proposed herein may play a major role in the transition towards a new era where the economy, society and the environment coexist as key pillars of sustainable development

Exploring the Emergence of Renewable Energy Grids in Developing Countries with Agent Based Models.

This work presents novel Agent-Based Models that permit flexible conceptualization of the electrification efforts in developing countries. It captures the interacting technological, environmental, and social layers that make up the system and value judgments, preferences and path dependence of decisions made while creating development plans. Reflecting these factors is key as it expands traditional tools used in electrification planning. The work starts through the presentation of a clean-slate scenario with no existing infrastructure or fossil fuel use. This is an appropriate representation of less industrialized countries with large unelectrified areas and concerns for climate change and fuels’ cost and security. In the case of the clean-slate scenario the electricity delivery infrastructure’s cost depends on the level of electricity demand, the available renewable energy potential, and development strategies chosen by stakeholders. In cases with high demand and low electricity potential, a centralized strategy based on renewable resources chosen with the Resource Centrality Index results in the most economic delivery system. On the other hand, high resources and low demand call for a decentralized strategy where communities can get involved in development decisions. Increasing the available resources dramatically lowers the cost of the delivery system and increases the options for inclusive strategies. The case study of Liberia, West Africa, is presented to further develop the tools. Liberia is shown to have enough renewable energy potential to fulfill its rural residential demand. Levelized costs of electricity from decentralized renewable energy projects based on biomass and mini or micro-hydro technologies are within the ability and willingness to pay of rural Liberians. Through the Liberian case study the work shows opportunities for use in multi-objective development where the value-judgments of stakeholders are captured. Objectives such as increasing jobs, creating economic flows within communities, providing equality of development within regions of the country, and minimizing economic costs are evaluated. The model is shown to be a creative and robust tool to plan electrification strategies when considering these goals. The results show how multiple objectives can be used in planning scenarios to ensure ability to pay of rural Liberians and other desired stakeholder benefits.PHDNatural Resources and EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107139/1/jfalfaro_1.pd