Self-Assembled InAs/GaAs Quantum Dot Solar Cells

Our work focuses on experimental and theoretical studies aimed at establishing a fundamental understanding of the principal electrical and optical processes governing the operation of quantum dot solar cells (QDSC) and their feasibility for the realization of intermediate band solar cell (IBSC). Uniform performance QD solar cells with high conversion efficiency have been fabricated using carefully calibrated process recipes as the basis of all reliable experimental characterization. The origin for the enhancement of the short circuit current density (Jsc) in QD solar cells was carefully investigated. External quantum efficiency (EQE) measurements were performed as a measure of the below bandgap distribution of transition states. In this work, we found that the incorporation of self-assembled quantum dots (QDs) interrupts the lattice periodicity and introduce a greatly broadened tailing density of states extending from the bandedge towards mid-gap. A below-bandgap density of states (DOS) model with an extended Urbach tail has been developed. In particular, the below-bandgap photocurrent generation has been attributed to transitions via confined energy states and background continuum tailing states. Photoluminescence measurement is used to measure the energy level of the lowest available state and the coupling effect between QD states and background tailing states because it results from a non-equilibrium process. A basic I-V measurement reveals a degradation of the open circuit voltage (Voc) of QD solar cells, which is related to a one sub-bandgap photon absorption process followed by a direct collection of the generated carriers by the external circuit. We have proposed a modified Shockley-Queisser (SQ) model that predicts the degradation of Voc compared with a reference bulk device. Whenever an energy state within the forbidden gap can facilitate additional absorption, it can facilitate recombination as well. If the recombination is non-radiative, it is detrimental to solar cell performance. We have also investigated the QD trapping effects as deep level energy states. Without an efficient carrier extraction pathway, the QDs can indeed function as mobile carriers traps. Since hole energy levels are mostly connected with hole collection under room temperature, the trapping effect is more severe for electrons. We have tried to electron-dope the QDs to exert a repulsive Coulomb force to help improve the carrier collection efficiency. We have experimentally observed a 30% improvement of Jsc for 4e/dot devices compared with 0e/dot devices. Electron-doping helps with better carrier collection efficiency, however, we have also measured a smaller transition probability from valance band to QD states as a direct manifestation of the Pauli Exclusion Principle. The non-linear performance is of particular interest. With the availability of laser with on-resonance and off-resonance excitation energy, we have explored the photocurrent enhancement by a sequential two-photon absorption (2PA) process via the intermediate states. For the first time, we are able to distinguish the nonlinearity effect by 1PA and 2PA process. The observed 2PA current under off-resonant and on-resonant excitation comes from a two-step transition via the tailing states instead of the QD states. However, given the existence of an extended Urbach tail and the small number of photons available for the intermediate states to conduction band transition, the experimental results suggest that with the current material system, the intensity requirement for an observable enhancement of photocurrent via a 2PA process is much higher than what is available from concentrated sun light. In order to realize the IBSC model, a matching transition strength needs to be achieved between valance band to QD states and QD states to conduction band. However, we have experimentally shown that only a negligible amount of signal can be observed at cryogenic temperature via the transition from QD states to conduction band under a broadband IR source excitation. Based on the understanding we have achieved, we found that the existence of the extended tailing density of states together with the large mismatch of the transition strength from VB to QD and from QD to CB, has systematically put into question the feasibility of the IBSC model with QDs.

Energy Cooperation in Energy Harvesting Communication Systems

In energy harvesting communications, users transmit messages using energy harvested from nature. In such systems, transmission policies of the users need to be carefully designed according to the energy arrival profiles. When the energy management policies are optimized, the resulting performance of the system depends only on the energy arrival profiles. In this dissertation, we introduce and analyze the notion of energy cooperation in energy harvesting communications where users can share a portion of their harvested energy with the other users via wireless energy transfer. This energy cooperation enables us to control and optimize the energy arrivals at users to the extent possible. In the classical setting of cooperation, users help each other in the transmission of their data by exploiting the broadcast nature of wireless communications and the resulting overheard information. In contrast to the usual notion of cooperation, which is at the signal level, energy cooperation we introduce here is at the battery energy level. In a multi-user setting, energy may be abundant in one user in which case the loss incurred by transferring it to another user may be less than the gain it yields for the other user. It is this cooperation that we explore in this dissertation for several multi-user scenarios, where energy can be transferred from one user to another through a separate wireless energy transfer unit. We first consider the offline optimal energy management problem for several basic multi-user network structures with energy harvesting transmitters and one-way wireless energy transfer. In energy harvesting transmitters, energy arrivals in time impose energy causality constraints on the transmission policies of the users. In the presence of wireless energy transfer, energy causality constraints take a new form: energy can flow in time from the past to the future for each user, and from one user to the other at each time. This requires a careful joint management of energy flow in two separate dimensions, and different management policies are required depending on how users share the common wireless medium and interact over it. In this context, we analyze several basic multi-user energy harvesting network structures with wireless energy transfer. To capture the main trade-offs and insights that arise due to wireless energy transfer, we focus our attention on simple two- and three-user communication systems, such as the relay channel, multiple access channel and the two-way channel. Next, we focus on the delay minimization problem for networks. We consider a general network topology of energy harvesting and energy cooperating nodes. Each node harvests energy from nature and all nodes may share a portion of their harvested energies with neighboring nodes through energy cooperation. We consider the joint data routing and capacity assignment problem for this setting under fixed data and energy routing topologies. We determine the joint routing of energy and data in a general multi-user scenario with data and energy transfer. Next, we consider the cooperative energy harvesting diamond channel, where the source and two relays harvest energy from nature and the physical layer is modeled as a concatenation of a broadcast and a multiple access channel. Since the broadcast channel is degraded, one of the relays has the message of the other relay. Therefore, the multiple access channel is an extended multiple access channel with common data. We determine the optimum power and rate allocation policies of the users in order to maximize the end-to-end throughput of this system. Finally, we consider the two-user cooperative multiple access channel with energy harvesting users. The users cooperate at the physical layer (data cooperation) by establishing common messages through overheard signals and then cooperatively sending them. For this channel model, we investigate the effect of intermittent data arrivals to the users. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. When the users can further cooperate at the battery level (energy cooperation), we find the jointly optimal offline transmit power and rate allocation policy together with the energy transfer policy that maximize the departure region.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

ANALYSIS AND SIMULATION OF ENERGY USE AND COST AT A MUNICIPAL WASTEWATER TREATMENT PLANT

The cost of electricity, a major operating cost of municipal wastewater treatment plants, is related to influent flow rate, power price, and power load. With knowledge of inflow and price patterns, plant operators can manage processes to reduce electricity costs. Records of influent flow, power price, and load are evaluated for Blue Plains Advanced Wastewater Treatment Plant. Diurnal and seasonal trends are analyzed. Power usage is broken down among treatment processes. A simulation model of influent pumping, a large power user, is developed. It predicts pump discharge and power usage based on wet-well level. Individual pump characteristics are tested in the plant. The model accurately simulates plant inflow and power use for two pumping stations [R2 = 0.68, 0.93 (inflow), R2 =0.94, 0.91(power)]. Wet-well stage-storage relationship is estimated from data. Time-varying wet-well level is added to the model. A synthetic example demonstrates application in managing pumps to reduce electricity cost.