Transition towards low-carbon energy systems requires an increase in the volume of renewable Distributed Generation (DG), particularly wind and photovoltaic, connected to distribution networks. To facilitate the connection of renewable DG without the need for expensive and time-consuming network reinforcements, distribution networks should move from passive to active methods of operation, whereby technical network constraints are actively managed in real time. This requires the deployment of control solutions that manage network constraints and, crucially, ensure adequate levels of energy curtailment from DG plants by using other controllable elements to solve network issues rather than resorting to generation curtailment only. This thesis proposes a deterministic distribution Network Management System (NMS) to facilitate the connections of renewable DG plants (specifically wind) by actively managing network voltages and congestion in real time through the optimal control of on-load tap changers (OLTCs), DG power factor and, then, generation curtailment as a last resort. The set points for the controllable elements are found using an AC Optimal Power Flow (OPF). The proposed NMS considers the realistic modelling of control by adopting one-minute resolution time-series data. To decrease the volumes of control actions from DG plants and OLTCs, the proposed approach departs from multi-second control cycles to multi-minute control cycles. To achieve this, the decision-making algorithm is further improved into a risk-based one to handle the uncertainties in wind power throughout the multi-minute control cycles. The performance of the deterministic and the risk-based NMS are compared using a 33 kV UK distribution network for different control cycles. The results show that the risk-based approach can effectively manage network constraints better than the deterministic approach, particularly for multi-minute control cycles, reducing also the number of control actions but at the expense of higher levels of curtailment. This thesis also proposes energy storage sizing framework to find the minimum power rating and energy capacity of multiple storage facilities to reduce curtailment from DG plants. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC OPF across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. The application of the proposed planning framework to a 33 kV UK distribution network demonstrates the importance of embedding real-time control aspects into the planning framework so as to accurately size storage facilities. By using reactive power capabilities of storage facilities it is possible to reduce storage sizes. The combined active management of OLTCs and power factor of DG plants resulted in the most significant benefits in terms of the required storage sizes.

Future aircraft are likely to employ electrically powered actuators for adjusting flight control surfaces, and other high power transient loads. To meet the peak power demands of aircraft electric loads and to absorb regenerated power, an ultracapacitor-based energy storage system is examined in which a bidirectional dual active bridge DC-DC converter is used. This Thesis deals with the analysis, design, development and performance evaluation of the dual active bridge (DAB) converter, which can act as an interface between the ultracapacitor energy storage bank and the aircraft electrical power network. A steady-state analysis is performed for the DAB converter producing equations for the device RMS and average currents and the peak and RMS currents in the coupling inductor. This analysis focuses on understanding converter current shapes and identifying the zero-voltage switching (ZVS) boundary condition. A converter prototype was designed and built and its operation verified through SABER simulations confirming the accuracy of the analysis. Experimental results are included to support the analysis for 7kW, 20 kHz operating conditions giving a measured efficiency of 90%. To enhance the performance of the converter under light-loads, a quasi-square-wave mode of operation is proposed in which a dead-time is introduced either on the transformer primary voltage, or on the transformer secondary voltage, or simultaneously on both transformer primary and secondary. A similar detailed analysis as that for square-wave operation has been undertaken for all three cases and the converter performance was analysed focusing on ZVS operating range, impact of the RMS/peak inductor currents and converter efficiency. The theoretical work was validated through SABER simulations and proof of concept experimental measurements at 1kW, 20 kHz, which resulted in converter efficiency well above 91%. A 9%-17% improvement in efficiency and a 12%-17% improvement in ZVS operating range over square-wave operation are observed for similar operating conditions. Furthermore, a novel bidirectional current control technique for the DAB converter is presented. A SABER simulation has been performed and the converter operation is validated for square-wave and quasi-square-wave modes under steady-state and transient conditions.

The world's energy supply today mainly consists of fossil fuels and nuclear power. Moving away from the use of these energy resources to renewable energy sources is considered a prerequisite for a sustainable future. In order to implement this change, it is necessary for renewable energy sources to be environmentally, technically and economically sustainable. A major challenge encountered in terms of technological sustainability is the intermittent nature of renewable energy sources. As the share of renewable electricity increases in the system, the electricity grid is facing new challenges such as increased instability of the frequency and capacity shortages. In order to meet these new challenges an increased flexibility from electricity users is proposed as a solution. Flexibility can be achieved either by controlling the use of electricity or utilizing energy storages. If different electric loads are to be controlled in a property, data regarding the power use of the loads must first be collected with a high time resolution in order to be able to properly analyze the data. Measures to shift or reduce the power peaks in a property can then be suggested and implemented. A battery storage can help reduce power peaks or shift loads in time and if done on a large scale that would reduce the strain on the entire Swedish grid. One of the ancillary services that the battery could offer is frequency regulation. Using energy storages for such an application could also provide a secondary revenue stream, aside from the revenue stream from peak shaving, and increase the profitability of the storage. Sweden has seen a dramatic increase in electric vehicles over the last decade and charging of the vehicles has become an issue for many property owners as it often creates power peaks. The data collection regarding power use in properties performed in during this thesis showed that valuable data can be collected with the method and material used. With a battery price of 3000 SEK/kWh the payback time for a battery system can be reduced from 17,9 to 7,8 years if it is used for frequency regulation during the night. If power-intensive loads such as electric vehicle charging are added to the model the payback period decreases to 6,1 years. With these results in mind, it can be concluded that the profitability of a battery storage can increase to the extent that the investment is of economic viability. In addition, the investment helps to improve the stability of the Swedish grid. The results are found to be relatively consistent with those of other similar studies. / <p>Digital presentation</p>

Morgongåva is an urban centre in Sweden, with several challenges in the electrical power grid. In order to use the power grid more efficiently, this report investigates potentials of installing a battery energy storage system (BESS). Focus lies on finding economic and technical benefits of reducing power peaks, which occur during high demand hours when transmitting energy is more expensive. This method is referred to as peak shaving. Further, economic calculations if installing a BESS are based on electricity pricing data. Calculations regarding technical benefits are based on net power demand data. Further, the study shows that the usage of the grid, which was measured with the load factor, would increase and thus allow installation of more power sources and connecting more load to the grid. The load factor was estimated to increase by an average of 2.12 percent each month in 2019. In one year, the economic profit was estimated to be 91,000 kr. The conclusion is that there are economic profits for Sala-Heby Energi of installing a BESS, but more importantly a BESS has technical consequences in the power grid. Where technical benefits are important in order to reach the goals of Agenda 2030 but also to obtain a more reliable grid for the customers. A sensitivity analysis shows that the model is robust. Thus, the conclusion is that Sala-Heby Energi and the local electricity grid in Morgongåva would benefit from installing a BESS.

abstract: In this work, the stacked values of battery energy storage systems (BESSs) of various power and energy capacities are evaluated as they provide multiple services such as peak shaving, frequency regulation, and reserve support in an ‘Arizona-based test system’ - a simplified, representative model of Salt River Project’s (SRP) system developed using the resource stack information shared by SRP. This has been achieved by developing a mixed-integer linear programming (MILP) based optimization model that captures the operation of BESS in the Arizona-based test system. The model formulation does not include any BESS cost as the objective is to estimate the net savings in total system operation cost after a BESS is deployed in the system. The optimization model has been formulated in such a way that the savings due to the provision of a single service, either peak shaving or frequency regulation or spinning reserve support, by the BESS, can be determined independently. The model also allows calculation of combined savings due to all the services rendered by the BESS. The results of this research suggest that the savings obtained with a BESS providing multiple services are significantly higher than the same capacity BESS delivering a single service in isolation. It is also observed that the marginal contribution of BESS reduces with increasing BESS energy capacity, a result consistent with the law of diminishing returns. Further, small changes in the simulation environment, such as factoring in generator forced outage rates or projection of future solar penetration, can lead to changes as high as 10% in the calculated stacked value. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2020

Concentrating solar power (CSP) plant is a promising technology that exploits direct normal irradiation (DNI) from the sun to be converted into thermal energy in the solar field. One of the advantages of CSP technology is the possibility to store thermal energy in thermal energy storage (TES) for later production of electricity. The integration of thermal storage allows the CSP plant to be a dispatchable system which is defined as having a capability to schedule its operation using an innovative dispatch planning tool. Considering weather forecast and electricity price profile in the market, dispatch planning tool uses an optimization algorithm. It aims to shift the schedule of electricity delivery to the hours with high electricity price. These hours are usually reflected by the high demand periods. The implementation of dispatch optimizer can benefit the CSP plants economically from the received financial revenues. This study proposes an optimization of dispatch planning strategies for the parabolic trough CSP plant under two dispatch approaches: solar driven and storage driven. The performed simulation improves the generation of electricity which reflects to the increase of financial revenue from the electricity sale in both solar and storage driven approaches. Moreover, the optimization also proves to reduce the amount of dumped thermal energy from the solar field.

Energy storage attracts attention nowadays due to the critical role it will play in the power generation and transportation sectors. Electric vehicles, as moving energy storage, are going to play a key role in the terrestrial transportation sector and help reduce greenhouse emissions. Bulk hybrid energy storage will play another critical role for feeding the new types of pulsed loads on ship power systems. However, to ensure the successful adoption of energy storage, there is a need to control and optimize the charging/discharging process, taking into consideration the customer preferences and the technical aspects. In this dissertation, novel control and optimization algorithms are developed and presented to address the various challenges that arise with the adoption of energy storage in the electricity and transportation sectors. Different decentralized control algorithms are proposed to manage the charging of a mass number of electric vehicles connected to different points of charging in the power distribution system. The different algorithms successfully satisfy the preferences of the customers without negatively impacting the technical constraints of the power grid. The developed algorithms were experimentally verified at the Energy Systems Research Laboratory at FIU. In addition to the charge control of electric vehicles, the optimal allocation and sizing of commercial parking lots are considered. A bi-layer Pareto multi-objective optimization problem is formulated to optimally allocate and size a commercial parking lot. The optimization formulation tries to maximize the profits of the parking lot investor, as well as minimize the losses and voltage deviations for the distribution system operator. Sensitivity analysis to show the effect of the different objectives on the selection of the optimal size and location is also performed. Furthermore, in this dissertation, energy management strategies of the onboard hybrid energy storage for a medium voltage direct current (MVDC) ship power system are developed. The objectives of the management strategies were to maintain the voltage of the MVDC bus, ensure proper power sharing, and ensure proper use of resources, where supercapacitors are used during the transient periods and batteries are used during the steady state periods. The management strategies were successfully validated through hardware in the loop simulation.

The recent discovery of layered transition metal carbides (MXenes) is one of the most important developments in two-dimensional (2D) materials. Preliminary theoretical and experimental studies suggest a wide range of potential applications for MXenes. The MXenes are prepared by chemically etching ‘A’-layer element from layered ternary metal carbides, nitrides and carbonitrides (MAX phases) through aqueous acid treatment, which results in various surface terminations such as hydroxyl, oxygen or fluorine. It has been found that surface terminations play a critical role in defining MXene properties and affects MXene performance in different applications such as electrochemical energy storage, electromagnetic interference shielding, water purification, sensors and catalysis. Also, the electronic, thermoelectric, structural, plasmonic and optical properties of MXenes largely depend upon surface terminations. Thus, controlling the surface chemistry if MXenes can be an efficient way to improve their properties. This research mainly aims to perform surface modifications of two commonly studied MXenes; Ti2C and Ti3C2, via chemical, thermal or physical processes to enhance electrochemical energy storage properties. The as-prepared and surface modified MXenes have been studied as electrode materials in Li-ion batteries (LIBs) and supercapacitors (SCs). In pursuit of desirable MXene surface, we have developed an in-situ room temperature oxidation process, which resulted in TiO2/MXene nanocomposite and enhanced Li-ion storage. The idea of making metal oxide and MXene nanocomposites was taken to the next level by combining a high capacity anode materials – SnO2 – and MXene. By taking advantage of already existing surface functional groups (–OH), we have developed a composite of SnO2/MXene by atomic layer deposition (ALD) which showed enhanced capacity and excellent cyclic stability. Thermal annealing of MXene at elevated temperature under different atmospheres was carried out and detailed surface chemistry was studied to analyze the change in surface functional groups and its effect on electrochemical performance. Also, we could replace surface functional groups with desirable heteroatoms (e.g., nitrogen) by plasma processing and studied their effect on energy storage properties. This work provides an experimental baseline for surface modification of MXene and helps to understand the role of various surface functional groups in MXene electrode electrochemical performance.

The shortage of energy sources and the global climate change crisis have become critical issues. Solving these problems with clean and sustainable energy sources (solar, wind, tidal, and so on) is a promising solution. In this regard, energy storage techniques need to be implemented to tackle with the intermittent nature of the sustainable energies. Among the next-generation energy storage systems, lithium sulfur batteries has gained prominence due to the low cost, high theoretical specific-capacity of sulfur. Extensive research has been conducted on this battery system. Nevertheless, several issues including the “shuttle effect” and the growth of lithium dendrites still exist, which could cause rapid capacity loss and safety hazards. Several methods are proposed to tackle the challenges in this dissertation, including cathode engineering, interlayer design, and lithium metal anode protection. An asymmetric cathode structure is first developed by a non-solvent induced phase separation (NIPS) method. The asymmetric cathode comprises a nanoporous matrix and ultrathin and dense top layer. The top-layer is a desired barrier to block polysulfides transport, while the sublayer threaded with cationic networks facilitate Li-ions transport and sulfur conversions. In addition, a conformal and ultrathin microporous membrane is electrodeposited on the whole surface of the cathode by an electropolymerization method. This strategy creates a close system, which greatly blocks the LiPS leakage and improves the sulfur utilization. A polycarbazole-type interlayer is deposited on the polypropylene (PP) separator via an electropolymerization method. This interlayer is ultrathin, continuous, and microporous, which defines the critical properties of an ideal interlayer that is required for advanced Li–S batteries. Meanwhile, a self-assembled 2D MXene based interlayer was prepared to offer abundant porosity, dual absorption sites, and desirable electrical conductivity for Li-ions transport and polysulfides conversions. A new 2D COF-on-MXene heterostructures is prepared as the lithium anode host. The 2D heterostructures has hierarchical porosity, conductive frameworks, and lithiophilic sites. When utilized as a lithium host, the MXene@COF host can efficiently regulate the Li+ diffusion, and reduce the nucleation and deposition overpotential, which results in a dendrite-free and safer Li–S battery.

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