Battery Capacity of Deferrable Energy Demand

We investigate the ability of a homogeneous collection of deferrable energy loads to behave as a battery; that is, to absorb and release energy in a controllable fashion up to fixed and predetermined limits on volume, charge rate and discharge rate. We derive bounds on the battery capacity that can be realized and show that there are fundamental trade-offs between battery parameters. By characterizing the state trajectories under scheduling policies that emulate two illustrative batteries, we show that the trade-offs occur because the states that allow the loads to absorb and release energy at high aggregate rates are conflicting

Aspects of autonomous demand response through frequency based control of domestic water heaters

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering in the School of Electrical and Information Engineering, July 2017This dissertation presents the design and testing of controllers intended to provide au- tonomous demand response, through the use of water heater loads and grid frequency measurements. The controllers use measured frequency as an indication of the strain on a utility grid, which allows demand side management to be isolated from any form of central control. Water heaters can operate as exible loads because their power consump- tion can be dispatched or deferred without directly impacting users. These properties make it possible to control individual water heaters based on the functioning of the grid, rather than end user input. The purpose of this research is to ultimately provide a low- cost alternative to a traditional Smart Grid, that will improve the resilience of a grid without negatively impacting users. The controllers presented here focus on ensuring that users receive hot water, while attempting to reduce any imbalance between power generated and power consumed on the grid. Simulations of these controllers in various situations highlight that while the controllers developed respond suitably to variations in the grid frequency and adequately ensure end users receive hot water, the practical bene t of the controllers depends largely on the intrinsic characteristics of the grid.CK201

Models and Optimal Controls for Smart Homes and their Integration into the Electric Power Grid

Smart homes can operate as a distributed energy resource (DER), when equipped with controllable high-efficiency appliances, solar photovoltaic (PV) generators, electric vehicles (EV) and energy storage systems (ESS). The high penetration of such buildings changes the typical electric power load profile, which without appropriate controls, may become a “duck curve” when the surplus PV generation is high, or a “dragon curve” when the EV charging load is high. A smart home may contribute to an optimal solution of such problems through the energy storage capacity, provided by its by battery energy storage system (BESS), heating, ventilation, and air conditioning (HVAC) system, and electric water heater (EWH), and the advanced controls of an home energy management (HEM). The integrated modeling of home energy usage and electric power distribution system, developed as part of this dissertation research, provides a testbed for HEM control methods and prediction of long-term scenarios. A hybrid energy storage system including batteries and a variable power EWH was proposed. It was demonstrated that when the operation of the proposed hybrid energy storage system was coordinated with PV generation, the required battery capacity would be substantially reduced while still maintaining the same functionality for smart homes to operate as dispatchable generators. A newly developed co-simulation framework, INSPIRE+D, enables the dynamic simulation of smart homes and their connection to the grid. The equivalent thermal model of a reference house was proposed with parameters based on the systematic study of experimental data from fully instrumented field demonstrators. Energy storage capacity of HVAC systems was calculated and an equivalent state-of-charge (SOC) was defined. The aggregated HVAC load was calculated based on special HVAC parameters and a sequential DR scheme was proposed to reduce both ramping rate and peak power, while maintaining human comfort according to ASHRAE standards. A long short-term memory (LSTM) method was applied to for the identification of HVAC system from the aggregated data. The generic water heater load curves based on the data retrieved from large experimental projects for resistive EWHs and heat pump water heaters (HPWHs) were created. A community-level digital twin with scalability has been developed to capture the aggregated hot water flow and average hot temperature in the tanks. The potential electricity saving of shifting from EWH to HPWH was calculated. The energy storage capacities for both EWHs and HPWHs were calculated. Long term load prediction by considering different fractions of smart homes with HEM for at the power system was provided based on one of the largest rural field smart energy technology demonstrators located in Glasgow, KY, US. Also demonstrates was the ability of EWH to provide ancillary services while maintaining customer comfort. The minimum participation rates for EWH and batteries were calculated and compared with respect to different peak reduction targets. The aggregated charging load for EV in a community was calculated based on data from the National Travel Household Survey (NHTS). The EV charging and RESS operation were scheduled to reduce the daily utility charge. Building resilience was quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year based on the annual electricity usage of a typical California residence. The influence of factors such as energy use behavioral patterns, BESS capacity, and an availability of EV was evaluated. A concept of generalized energy storage (GES) model for BESS, EWH and HVAC systems was proposed. The analogies, including SOC versus water/indoor temperature differential, were identified and explained, and models-in-the-loop (MIL) were introduced, which were compatible with the Energy Star and Consumer Technology Association (CTA)-2045 general specifications and command types. A case study is included to illustrate that the “energy content” and “energy take” for BESS and EWH. The main original contributions of this dissertation include the comprehensive simulation of the total building energy usage and the development of the co-simulation framework incorporating building and power system simulators. Another contribution of the dissertation is the quantification of building resilience based on the building energy usage model. The dissertation also contributes to the concept of GES which regards the HVAC and EWH as virtual energy storage and their unified controls with BESS. The GES facilitates the employment of industrial standards, e.g., CTA-2045, and the hybrid ESS reduces required BESS capacity. This dissertation contributes to the modeling of aggregated load for EWH, HVAC, and EV using different methods and long term forecasting of power profile at the system level. The aggregated generic load for EWH was calculated based on large amount of field data, the aggregated EV charging load was estimated based on national survey results, and the aggregated HVAC load was simulated based on the modeling of every residences, where the model parameters were populated according to special distributions. The methods based LSTM for the identification of HVAC power from the aggregated load was developed

Experimental Investigation and Evaluation of Future Active Distribution Networks

The UK government’s policy to achieve a 20% renewable energy generation target by 2020, will require significant amounts of SSEG (Small-Scale Embedded Generation) to be connected. In addition to the expected economic and environmental benefits, the anticipated growth in SSEG brings with it numerous challenges for the operation of low voltage and medium voltage distribution networks. At present, there are a number of competing active network management concepts being considered to overcome these challenges and at Durham University a concept defined as the Small Scale Energy Zone (SSEZ) has been proposed and is investigated as part of this research. To further this, a bespoke active low voltage distribution network emulator known as the Experimental SSEZ has been developed by the author. Controllable emulated SSEG, controllable energy storage and controllable emulated load are incorporated into this laboratory. A transformation system has been developed to relate the operation of this system to that of low voltage distribution networks. Centralised and distributed network control systems have been developed for the Experimental SSEZ. These systems were used to evaluate, in conjunction with the relevant literature, the implementation of similar systems on future low voltage distribution networks. Both centralised and distributed control system architectures were found to have their merits. This research should therefore be useful in informing design decisions when developing and implementing active distribution network management systems on LV networks

Enhancement of Controllability in Distribution Grid by Means of Power Electronics Components based Distributed and Centralized Solutions

The contemporary distribution grid is undergoing evolutions for the increased penetration of distributed generation and new types loads. Innovative operation schemes and components should be adopted to cope with the emerging grid issues. Exploiting power electronics (PE) components, operation approaches can address the issues. In this thesis, fast charging station (FCS), energy storage static synchronous compensator (ES-STATCOM), and smart transformer (ST), have been analyzed in the development of solutions to enhance grid controllability. A load-leveling approach has been proposed, using reactive power from the spare capacity of the FCSs, to regulate the grid voltage, eventually to shape the power demand of voltage-sensitive loads, tracking the demand forecast, reducing the mismatch, and keeping a satisfactory charging. This approach is a distributed solution since it coordinates the actuators spread geographically in the grid. A PE based approach employing voltage-correlation coefficients has been proposed to cope with voltage violation. For PE components such as ES-STATCOM and ST, the applied correlation coefficients must be adapted accordingly. Corresponding voltage regulation schemes have been developed. The analysis has illustrated the effectiveness of the proposed schemes and distinguished some significant differences between ES-STATCOMs and STs. The meshed grid configuration can offer more flexibility respecting the radial grid configuration. This work has proposed an ST based meshed grid operation approach as a centralized solution. An operation scheme has been developed, employing a multi-objective operation algorithm to address the emerging issues. Besides, a power quality conditioning scheme has been developed to condition the harmonics in current

Power electronics implementation of dynamic thermal storage as effective inertia in large energy systems

Modern large energy systems such as electricity grids and electrified transportation encounter increasing processed power in multi-physics domains, such as electrical, mechanical, thermal, and chemical. Although many systems are becoming predominantly electrical dependent, an integrated multi-physics energy approach creates additional avenues to higher power density, system efficiency, and reliability. Power electronics, serving as power conversion mechanisms, are key linking subsystems consisting of electronic devices, electro-mechanical units, energy storage, etc. This dissertation first studies the use of power electronic drives to implement dynamic thermal storage as effective inertia in solar-interfaced grid-connected low-energy buildings, as an example of a stationary large energy system. Dynamic management of energy components is used to offset variability of stochastic solar resources. Emphasis is on power electronic HVAC (heating, ventilation, and air-conditioning) drives, which can act as an effective electric swing bus to mitigate solar power variability. In doing so, grid power flows become substantially more constant, reducing the need for fast grid resources or dedicated energy storage such as batteries. The work defines a bandwidth over which such HVAC drives can operate. A practical band-pass filter is realized with a lower frequency bound such that the building maintains consistent temperature, and an upper frequency bound to ensure that commanded HVAC fan speeds do not update arbitrarily fast, avoid acoustic discomfort to occupants, and prevent undue hardware wear and tear. The dissertation then moves onto investigation of a mobile energy system, specifically more electric aircraft (MEA), with the purpose of evaluating thermal inertia’s efficacy in a microgrid-like inertia-lacking electrical system. Thermal energy inherent in the cabin air and aircraft fuel serves as a dynamic management solution to offset stochastic load power in the MEA power system. Power electronic controlled environmental control system (ECS) drives, emulating dynamic thermal inertia, showcase a more constant generator output power, allowing potential to downsize required generator ratings. An operating bandwidth is proposed similar to that of building HVAC systems, subject to additional degrees of constraints unique on MEA. A more sensitive virtual synchronous machine control boosts desirable inertia in sub-seconds scales in the MEA power system. To validate the thermal storage as effective inertia in both stationary and mobile energy systems, comprehensive simulation studies and experimental work are conducted at multiple levels. For the energy-efficient building research platform, building electrical and thermal energy systems modeling is addressed, including solar and HVAC systems as well as batteries and large-scale thermal storage. A lab-scale power system features various update rates of a variable frequency fan drive over stochastic solar data. A full-scale multiple-day case study provides insight on potential grid-side and storage-related benefits. The simulation and experimental studies are supported by 18 months of solar data collected on sub-millisecond time scales as a basis to evaluate efficacy, determine solar frequency-domain content, and analyze mitigation of variability. For the MEA research platform, steady-state and dynamic behaviors of electrical components in the Boeing 787 power systems, including electric machines, power converters, batteries, transformers, and loads, are modeled. In particular, in-depth discussions cover a multi-timescale parametric electrical battery model for use in dynamic electric transportation simulations. An integrated thermal model within electrical components and electrical systems captures temperature variations and ECS thermal dynamics. Simulation studies based on realistic load power demand over a 5-hour mission profile show mitigation of generator power transients while maintaining relatively comfortable cabin temperature bounds. Finally a scaled-down lab power system is implemented on a microcontroller-tied industrial drive to demonstrate feasibility in a potential commercial system