Corrective receding horizon EV charge scheduling using short-term solar forecasting

Forecast errors can cause sub-optimal solutions in resource planning optimization, yet they are usually modeled simplistically by statistical models, causing unrealistic impacts on the optimal solutions. In this paper, realistic forecast errors are prescribed, and a corrective approach is proposed to mitigate the negative effects of day-ahead persistence forecast error by short-term forecasts from a state-of-the-art sky imager system. These forecasts preserve the spatiotemporal dependence structure of forecast errors avoiding statistical approximations. The performance of the proposed algorithm is tested on a receding horizon quadratic program developed for valley filling the midday net load depression through electric vehicle charging. Throughout one month of simulations the ability to flatten net load is assessed under practical forecast accuracy levels achievable from persistence, sky imager and perfect forecasts. Compared to using day-ahead persistence solar forecasts, the proposed corrective approach using sky imager forecasts delivers a 25% reduction in the standard deviation of the daily net load. It is demonstrated that correcting day-ahead forecasts in real time with more accurate short-term forecasts benefits the valley filling solution

Meeting Global Cooling Demand with Photovoltaics during the 21st Century

Space conditioning, and cooling in particular, is a key factor in human productivity and well-being across the globe. During the 21st century, global cooling demand is expected to grow significantly due to the increase in wealth and population in sunny nations across the globe and the advance of global warming. The same locations that see high demand for cooling are also ideal for electricity generation via photovoltaics (PV). Despite the apparent synergy between cooling demand and PV generation, the potential of the cooling sector to sustain PV generation has not been assessed on a global scale. Here, we perform a global assessment of increased PV electricity adoption enabled by the residential cooling sector during the 21st century. Already today, utilizing PV production for cooling could facilitate an additional installed PV capacity of approximately 540 GW, more than the global PV capacity of today. Using established scenarios of population and income growth, as well as accounting for future global warming, we further project that the global residential cooling sector could sustain an added PV capacity between 20-200 GW each year for most of the 21st century, on par with the current global manufacturing capacity of 100 GW. Furthermore, we find that without storage, PV could directly power approximately 50% of cooling demand, and that this fraction is set to increase from 49% to 56% during the 21st century, as cooling demand grows in locations where PV and cooling have a higher synergy. With this geographic shift in demand, the potential of distributed storage also grows. We simulate that with a 1 m$^3$ water-based latent thermal storage per household, the fraction of cooling demand met with PV would increase from 55% to 70% during the century. These results show that the synergy between cooling and PV is notable and could significantly accelerate the growth of the global PV industry

Meeting Global Cooling Demand with Photovoltaics during the 21st Century

Space conditioning, and cooling in particular, is a key factor in human productivity and well-being across the globe. During the 21st century, global cooling demand is expected to grow significantly due to the increase in wealth and population in sunny nations across the globe and the advance of global warming. The same locations that see high demand for cooling are also ideal for electricity generation via photovoltaics (PV). Despite the apparent synergy between cooling demand and PV generation, the potential of the cooling sector to sustain PV generation has not been assessed on a global scale. Here, we perform a global assessment of increased PV electricity adoption enabled by the residential cooling sector during the 21st century. Already today, utilizing PV production for cooling could facilitate an additional installed PV capacity of approximately 540 GW, more than the global PV capacity of today. Using established scenarios of population and income growth, as well as accounting for future global warming, we further project that the global residential cooling sector could sustain an added PV capacity between 20-200 GW each year for most of the 21st century, on par with the current global manufacturing capacity of 100 GW. Furthermore, we find that without storage, PV could directly power approximately 50% of cooling demand, and that this fraction is set to increase from 49% to 56% during the 21st century, as cooling demand grows in locations where PV and cooling have a higher synergy. With this geographic shift in demand, the potential of distributed storage also grows. We simulate that with a 1 m$^3$ water-based latent thermal storage per household, the fraction of cooling demand met with PV would increase from 55% to 70% during the century. These results show that the synergy between cooling and PV is notable and could significantly accelerate the growth of the global PV industry

A Reserve-Based Method for Mitigating the Impact of Renewable Energy

The fundamental operating paradigm of today\u27s power systems is undergoing a significant shift. This is partially motivated by the increased desire for incorporating variable renewable energy resources into generation portfolios. While these generating technologies offer clean energy at zero marginal cost, i.e. no fuel costs, they also offer unique operating challenges for system operators. Perhaps the biggest operating challenge these resources introduce is accommodating their intermittent fuel source availability. For this reason, these generators increase the system-wide variability and uncertainty. As a result, system operators are revisiting traditional operating strategies to more efficiently incorporate these generation resources to maximize the benefit they provide while minimizing the challenges they introduce. One way system operators have accounted for system variability and uncertainty is through the use of operating reserves. Operating reserves can be simplified as excess capacity kept online during real time operations to help accommodate unforeseen fluctuations in demand. With new generation resources, a new class of operating reserves has emerged that is generally known as flexibility, or ramping, reserves. This new reserve class is meant to better position systems to mitigate severe ramping in the net load profile. The best way to define this new requirement is still under investigation. Typical requirement definitions focus on the additional uncertainty introduced by variable generation and there is room for improvement regarding explicit consideration for the variability they introduce. An exogenous reserve modification method is introduced in this report that can improve system reliability with minimal impacts on total system wide production costs. Another potential solution to this problem is to formulate the problem as a stochastic programming problem. The unit commitment and economic dispatch problems are typically formulated as deterministic problems due to fast solution times and the solutions being sufficient for operations. Improvements in technical computing hardware have reignited interest in stochastic modeling. The variability of wind and solar naturally lends itself to stochastic modeling. The use of explicit reserve requirements in stochastic models is an area of interest for power system researchers. This report introduces a new reserve modification implementation based on previous results to be used in a stochastic modeling framework. With technological improvements in distributed generation technologies, microgrids are currently being researched and implemented. Microgrids are small power systems that have the ability to serve their demand with their own generation resources and may have a connection to a larger power system. As battery technologies improve, they are becoming a more viable option in these distributed power systems and research is necessary to determine the most efficient way to utilize them. This report will investigate several unique operating strategies for batteries in small power systems and analyze their benefits. These new operating strategies will help reduce operating costs and improve system reliability

Bidding Strategy for Networked Microgrids in the Day-Ahead Electricity Market

In recent years, microgrids have drawn increasing attention from both academic and industrial sectors due to their enormous potential benefits to the power systems. Microgrids are essentially highly-customized small-scale power systems. Microgrids’ islanding capability enables microgrids to conduct more flexible and energy-efficient operations. Microgrids have proved to be able to provide reliable and environmental-friendly electricity to quality-sensitive or off-grid consumers. In addition, during the grid-connected operation mode, microgrids can also provide support to the utility grid. World-widely continuous microgrid deployments indicate a paradigm shift from traditional centralized large-scale systems toward more distributed and customized small-scale systems. However, microgrids can cause as many problems as it solves. More efforts are needed to address these problems caused by microgrids integration. Considering there will be multiple microgrids in future power systems, the coordination problems between individual microgrids remain to be solved. Aiming at facilitating the promotion of microgrids, this thesis investigates the system-level modeling methods for coordination between multiple microgrids in the context of participating in the market. Firstly, this thesis reviews the background and recent development of microgrid coordination models. Problems of existing studies are identified. Motivated by these problems, the research objectives and structure of this thesis are presented. Secondly, this thesis examines and compares the most common frameworks for optimization under uncertainty. An improved unit commitment model considering uncertain sub-hour wind power ramp behaviors is presented to illustrate the reformulation and solution method of optimization models with uncertainty. Next, the price-maker bidding strategy for collaborative networked microgrids is presented. Multiple microgrids are coordinated as a single dispatchable entity and participate in the market as a price-maker. The market-clearing process is modeled using system residual supply/demand price-quota curves. Multiple uncertainty sources in the bidding model are mitigated with a hybrid stochastic-robust optimization framework. What’s more, this thesis further considers the privacy concerns of individual microgrids in the coordination process. Therefore a privacy-preserving solution method based on Dantzig-Wolfe decomposition is proposed to solve the bidding problem. Both computational and economic performances of the proposed model are compared with the performances of conventional centralized coordination framework. Lastly, this thesis provides suggestions on future research directions of coordination problems among multiple microgrids

Message Passing for Integrating and Assessing Renewable Generation in a Redundant Power Grid

A simplified model of a redundant power grid is used to study integration of fluctuating renewable generation. The grid consists of large number of generator and consumer nodes. The net power consumption is determined by the difference between the gross consumption and the level of renewable generation. The gross consumption is drawn from a narrow distribution representing the predictability of aggregated loads, and we consider two different distributions representing wind and solar resources. Each generator is connected to D consumers, and redundancy is built in by connecting R of these consumers to other generators. The lines are switchable so that at any instance each consumer is connected to a single generator. We explore the capacity of the renewable generation by determining the level of "firm" generation capacity that can be displaced for different levels of redundancy R. We also develop message-passing control algorithm for finding switch settings where no generator is overloaded.Comment: 10 pages, accepted for HICSS-4

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Development of optimal energy management and sizing strategies for large-scale electrical storage systems supporting renewable energy sources.

284 p.El desarrollo e integración de las fuentes de energía renovable (RES) conducirá a un futuro energético más sostenible. Las plantas renovables deberán mejorar su participación y operación a través de los mercados de electricidad de una manera más controlada y segura. Además, el diseño actual del mercado está cambiando para permitir una participación inclusiva en mercados de flexibilidad. En este contexto, los sistemas de almacenamiento de energía (ESS) se consideran una de las tecnologías flexibles clave que pueden apoyar la operación de las energías renovables, mediante servicios como: 1) control de la potencia generada, 2) mejora de los errores de predicción, y 3) provisión de servicios auxiliares de regulación de frecuencia. Sin embargo, el desarrollo del almacenamiento ha sido frenado también por sus altos costos. Por lo tanto, esta tesis doctoral aborda el tema del ¿Desarrollo de estrategias óptimas de gestión y dimensionamiento de los sistemas de almacenamiento eléctrico a gran escala como apoyo a fuentes de energía renovable¿, con el objetivo de desarrollar una metodología con una perspectiva global, mediante una estrategia de gestión de energía avanzada (EMS) que aborda la gestión de activos (RES + ESS) a largo plazo y por otro lado, el cálculo del dimensionamiento y operación del almacenamiento a corto plazo (en la operación en tiempo real), para asegurar un marco adecuado que permita evaluar la rentabilidad de la integración del almacenamiento en aplicaciones conectadas a la red. La estrategia de gestión de energía propuesta es validada a través de dos casos de estudio: una planta renovable individual (eólica o solar) con almacenamiento, y un porfolio de renovables y almacenamiento

Development of optimal energy management and sizing strategies for large-scale electrical storage systems supporting renewable energy sources.

284 p.El desarrollo e integración de las fuentes de energía renovable (RES) conducirá a un futuro energético más sostenible. Las plantas renovables deberán mejorar su participación y operación a través de los mercados de electricidad de una manera más controlada y segura. Además, el diseño actual del mercado está cambiando para permitir una participación inclusiva en mercados de flexibilidad. En este contexto, los sistemas de almacenamiento de energía (ESS) se consideran una de las tecnologías flexibles clave que pueden apoyar la operación de las energías renovables, mediante servicios como: 1) control de la potencia generada, 2) mejora de los errores de predicción, y 3) provisión de servicios auxiliares de regulación de frecuencia. Sin embargo, el desarrollo del almacenamiento ha sido frenado también por sus altos costos. Por lo tanto, esta tesis doctoral aborda el tema del ¿Desarrollo de estrategias óptimas de gestión y dimensionamiento de los sistemas de almacenamiento eléctrico a gran escala como apoyo a fuentes de energía renovable¿, con el objetivo de desarrollar una metodología con una perspectiva global, mediante una estrategia de gestión de energía avanzada (EMS) que aborda la gestión de activos (RES + ESS) a largo plazo y por otro lado, el cálculo del dimensionamiento y operación del almacenamiento a corto plazo (en la operación en tiempo real), para asegurar un marco adecuado que permita evaluar la rentabilidad de la integración del almacenamiento en aplicaciones conectadas a la red. La estrategia de gestión de energía propuesta es validada a través de dos casos de estudio: una planta renovable individual (eólica o solar) con almacenamiento, y un porfolio de renovables y almacenamiento