Control of Electric Load Aggregations for Power System Services

In electrical power systems, when the supply from wind or solar-powered generation fluctuates, other resources adjust their power to maintain the system’s balance between demand and supply. Traditionally, gas, coal, and hydro-powered generators have provided this balancing service. In the future, as the proportion of renewable power generation increases, additional balancing resources will be needed. In this work, we develop methods that enable a new resource—aggregations of flexible loads—to provide energy balancing. Load aggregations are a promising resource for transmission-level energy balancing, but this service should not come at the expense of lower-level services and requirements. Specifically, an aggregator’s control should not compromise the loads’ service to the end-user and should not cause operational issues on the distribution network. Thermostatically controlled loads (TCLs), such as air conditioners and water heaters, have user-set temperature limits and cycling constraints that must be satisfied. Distribution networks have loading and voltage constraints to ensure reliable operation. When providing balancing services, aggregators partially synchronize loads, which can cause constraint violations on the distribution network. Third-party aggregators are unaware of conditions on the network and must coordinate with the distribution operator to ensure network reliability. The objective of this dissertation is to develop control methods by which a third-party aggregator can provide energy balancing without disrupting consumers and without causing unsafe conditions on the distribution network. Multiple methods are proposed for identifying and protecting distribution constraints that are at risk of violation due to load control. We conduct a simulation study of realistic distribution networks and find only a small subset of network constraints is at risk of violation. This result implies that network-safe control strategies may need to account for only a subset of network constraints, enhancing computational efficiency. We propose using a ``mode-count algorithm’’ to control a group of TCLs to minimize their impact on an at-risk network constraint. Results show that the mode-count algorithm can effectively reduce the variability of voltage at a constrained distribution node. Developing an online method to identify the set of at-risk constraints is non-trivial; towards this end, we propose an optimization-based method that identifies the network’s most at-risk individual constraint and provides a conservative, global safety constraint on power deviations caused by the aggregator. Because the method is computationally intensive, we develop techniques based on power-flow analysis to reduce the problem size; we are able to reduce the problem size by more than 60% for a test network. Two network-safe control strategies for energy balancing are proposed. Both strategies are hierarchical: the aggregator controls loads to track an energy-balancing signal, and the operator removes particular TCLs from the aggregator’s control when necessary for network safety. The strategies differ in terms of modeling and communication requirements. In a case study, the more complex strategy achieves a root-mean-square tracking error of 0.10% of the TCLs’ baseline power consumption while removing fewer than 1% of TCLs from the aggregator’s control; the other strategy achieves a 0.70% tracking error while removing approximately 15% of TCLs. The two strategies provide options — one better performing, one less costly — for operators and aggregators with different capabilities and preferences. Overall, these strategies enable third-party aggregators to control larger proportions of distribution-network load, enhancing competition in wholesale markets and providing the greater balancing capacities that will be needed by future, low-carbon power systems.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155144/1/sjcrock_1.pd

Large-Scale Invariant Sets for Safe Coordination of Thermostatic Loads

Extended version of ACC 2021 paper.Systems often face constraints at multiple levels. For example, in coordinating a collection of thermostatically controlled loads to provide grid services, the controller must ensure temperature constraints for each load (local constraints) and distribution network constraints (global constraints) are satisfied. In this paper, we leverage invariant sets to ensure safe coordination of systems with both local and global constraints. Specifically, we develop a method for constructing a controlled invariant set for a collection of subsystems, modeled as transition systems, to ensure they indefinitely satisfy the constraints, based on cycles in individual transition systems. Then, we develop a control algorithm that keeps the state inside the maximal controlled invariant set. We apply these algorithms to a demand response problem, specifically, the tracking of a power trajectory (e.g., a frequency regulation signal) by a population of homogeneous air conditioners. The algorithm simultaneously maintains local temperature requirements and aggregate power consumption limits, ensuring the control is nondisruptive to consumers and benign to the distribution network.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166595/1/ACC2021_FInal_LongerVer.pdfSEL

Ancillary services in Smart Grids to support distribution networks in the integration of renewable energy resources

2014 - 2015In recent years, progresses have been made in developing cleaner and more efficient technologies to produce, transmit and distribute energy. Pledges made in the recent summit in Paris (21°conference of the parties - COP21, Paris 2015) and Marrakech (COP22, Marrakech 2016) on climate changes promise to give new impetus to the move towards a lower-carbon and more efficient energy system. Nowadays, mandatory energy efficiency plans are expanding worldwide to cover over a quarter of the total global consumption. Furthermore, renewables represent almost half of the world’s new power generation capacity. The deepening penetration of renewable energy resources (RESs) has forced grid operators to deal with both technical and economic challenges to harness as much green energy as possible from them. Renewable plants, solar photovoltaic (PV) based and wind farms, are often small-medium scale generation plants connected at the distribution network level. The conventional distribution networks were designed to be operated as passive networks but with the continuing integration of RESs must accommodate bi-directional flows. Indeed, the implementation of the Smart Grid into distribution grids will bring about the effective deployment of advances in information and communication technologies (ICT) to improvements in the reliability, resiliency, flexibility and efficiency of such grids. Under the resulting new paradigm, it is possible to identify new roles that the distribution network operator (DNO) can play as well as additional activities and services that the DNO can provide to bring out marked improvements in the distribution grid management arena. The rapid changes in the distribution grid need to be accompanied by associated changes in their operations and provide the flexibility for the operators to evolve from the conventional DNO who manages passive networks to that of the distribution system operator (DSO) to run the new bidirectional flow distribution grid. This thesis is presented within the context of the newly evolving distribution grids managed by their DSOs. The aim of the work is to investigate the feasibility and implementation of the provision of ancillary services able to support current and future DSOs to facilitate improvements in the harnessing of the energy produced by deeper penetrations of RESs into the distribution grids. To this end, specific services must be provided by resources in the distribution network (DN) to provide congestion relief, as well as various ancillary services (AS), such as frequency control, voltage regulation, spinning and non spinning reserves and in some cases energy services from distributed energy resources or DERs. A key contribution of the thesis is to address the potential of three DER types – distributed generations (DGs), demand response and energy storage resources – to provide such services in DNs. Proposed strategies and approaches are tested and validated on real-world DN test systems. In detail, the thesis discusses two proposed decentralised approaches to provide voltage support from DG resources. These approaches’ objective is to avoid active power curtailments or the disconnection of RESs due to rises in voltage that usually occur in periods of high generation and low demand. We take advantage of the inverter that usually interfaces a DG to the DN into which it is integrated to implement a practical control strategy to provide reactive power support, be it either via injection or absorption of vars. Capability curves define the actual operational area that defines the amount of reactive power that is possible to absorb or inject into the grid, making curtailments/disconnections the least frequent solution performed by DSO when contingencies occur. To extend the approach of this control technique, it is possible to coordinate reactive power flows coming from different DG units of an independent power producer (IPP). The idea is to maximise active power production (and, then, reduce curtailments/disconnections) of PV and wind generators by optimising reactive power injections/absorption of DG units connected to different point of the DNs. The first decentralised but coordinated approach calculates the set points of each DG units by using the coefficients of the mixed sensitivity matrix of the network. This method results to be very fast to perform but it requires the calculation of the mixed sensitivity matrix; moreover, in some conditions, it could not give the best solution in terms of reactive power. The second method is based on the solution of a non-linear optimisation problem in order to calculate the active power-reactive power set points. By solving a global problem, the method points out an optimal solution even if the number DG units involved in the control is nontrivial; anyway, a communication framework must be developed for the exchange of information between DSO and IPP. We illustrate each scheme with applications to an actual Italian distribution network and provide a comparative analysis of their performance. To provide ancillary services by demand response resources in the DN, it is necessary to develop new load models. Two alternative formulations of the well-known ZIP model to explicitly represent the dependence of the demand on voltage changes under steady state conditions are presented. These model representations are able to provide acceptable estimates of the impacts of schemes, such as conservation voltage reduction (CVR), on the energy consumption by these loads. More in detail, the study wants to estimate how much demand it is possible to unlock by changing voltage values along the lines. To this end, an experimental study on a next-generation home appliance (a washing machine with digital control and motor drive fed by inverter) is conducted. The time-varying behaviour of domestic appliances is represented by using a discrete-time ZIP model to describe each phase of the appliance operations. The proposed model is capable of modelling the active power absorption of thermostatic loads, which exhibit periodic behaviour that depends on the applied voltage as well as equipment settings and the surrounding environment. To reduce the number of loads to be modelled during a time-series simulation, a time-varying formulation of the ZIP model is presented. It allows the aggregation of ZIP parameters at a given instant in time by using a polynomial structure. This model is tested on a real UK distribution network in order to estimate the amount of demand subject to change when the voltage at the primary substation is modified via an on load tap changer (OLTC). The deployment of energy storage resources (ESRs) for the provision of certain ancillary services is investigated. The focus of the work is specifically on battery energy storage system integrated into PV systems. Two specific situations, under which the battery energy storage system (BESS) provides voltage support at the DN level, are proposed. The BESS is integrated into a PV solar farm. In detail, two controls, in which BESSs are co-located with PV units in order to provide voltage support in DNs, are presented. The former is a sensitivity-based decentralized control approach described above reduces the reactive power needed to maintain the voltage within a specified interval when compared to the case of the same solar PV unit farm without the integrated BESS. The latter ancillary service envisages the possibility to coordinate charging/discharging periods of BESSs co-located with PV units with DSO needs. Assuming that the DSO is able to estimate generation and demand peaks during the day (when the possibility of having voltage rises and voltage drops increases), then it is possible to identify the periods of the day in which the possibility that voltage issues occur is higher. Thus, DSO can require BESSs to provide voltage support in these periods by charging/discharging according to the possibility of having voltage rises/drops. The proposed method is compared with the case in which PV/BESS are operated without supporting network operation. Energy selfconsumption resulted to be comparable; moreover, the opportunity cost is estimated to associate a cost to the proposed ancillary service. The initial design of an analytic framework to assess the deployment of ESRs within a market environment and their performance in terms of reliability, environmental and economic impacts is presented. The rather comprehensive framework provides the capability to represent all the interactions among the embedding environment of the deployed ESR with all other players/stakeholders in the grid and in the markets. The framework has the flexibility to incorporate relevant and appropriate policy issues and policy alternatives as well as to represent new market products to effectively harness ESR capabilities. The framework is able to represent the physical grid, the ESR embedding environment, if any; all resources and loads; the communication of control signals; the broadcast of market information/forecasts/data; submission of ESR offers for provision of various services; the evaluation of all reliability, environmental and economic/financial metrics of interest; attributes and sensor measurements; the physical/financial/information flows between physical resources, market players, asset owners and resource and grid operators. The design of the framework provides an interconnected four-layer framework structure consisting of a separate layer for the physical, information, market and environmental flows with the various interactions among the layers. The four- layer structure can accommodate the consideration of all issues in the operations of ESR deployment. Despite the number of studies available in the literature, there is limited activity in the provision of services in DNs by RESs. Technical issues as well as economic considerations has been addressed in the Thesis that gives significant contributions in the field of voltage regulation by using dispersed resources for reducing the risk of curtailments and maximizing the hosting capacity. This work also contributed to the understanding that decentralised approaches can, in certain case, have similar performance of centralised ones. In addition, the role of load as an active resource in the grid has been investigated. Load models that correlate consumption and voltage have been improved and reformulated. Finally, the role of BESSs in providing ASs in DNs has been demonstrated and a preliminary framework for the assessment of their economics has been presented. [edited by Author]XIV n.s

Quantification and mitigation of the impacts of extreme weather on power system resilience and reliability

Modelling the impact of extreme weather on power systems is a computationally expensive, challenging area of study due to the diversity of threats, complicatedness of modelling, and data and simulation requirements to perform the relevant studies. The impacts of extreme weather – specifically wind – are considered. Factors such as the distribution of outage probability on lines and the potential correlation with wind power generation during storms are investigated; so too is sensitivity of security assessments involving extreme wind to the relationships used between failures and the natural hazard being studied, specifically wind speed. A large scale simulation ensemble is developed and demonstrated to investigate what are deemed the most significant features of power system simulation during extreme weather events. The challenges associated with modelling high impact low probability (HILP) events are studied and demonstrate that the results of security assessments are significantly affected by the granularity of incident weather data being used and the corrections or interpolation being applied to the source data. A generalizable simulation framework is formulated and deployed to investigate the significance of the relationship between incident natural hazards, in this case wind, and its corresponding impact on system resilience. Based on this, a large-scale simulation model is developed and demonstrated to take consideration of a wide variety of factors which can affect power systems during extreme weather events including, but not limited to, under frequency load shedding, line overloads, and high wind speed shutdown and its impact on wind generation. A methodology for quantifying and visualising distributed overhead line failure risk is also demonstrated in tandem with straightforward methods for making wind power projections over transmission systems for security studies. The potential correlation between overhead line risk and wind power generation risk is illustrated visually on representations of GB power networks based on real world data.Open Acces

Coordination and Control of Distributed Energy Resources: Modeling and Analysis Techniques

Coordinated control of distributed energy resources (DERs), such as flexible loads, storage devices and solar photovoltaic inverters, can provide valuable services to the electricity grid by reducing peak demand, balancing renewables and avoiding voltage excursions. Aggregate control of thermostatically controlled loads (TCLs), such as air-conditioners, water-heaters and refrigerators, offers a promising way of accommodating significant DERs in power systems. This dissertation focuses primarily on modeling and analysis techniques for ensembles of TCLs. It also develops techniques for efficiently aggregating DER-based flexibility. A wide-variety of load ensemble control techniques have been developed in the literature – with strategies including probabilistic switching signals, TCL set-point variation, and price-based signals. However, synchronization of TCL temperatures, oscillations in aggregate demand and bifurcations have been observed, which can lead to detrimental power- and voltage-related issues in the electricity grid. A detailed investigation is undertaken of a market-based transactive energy coordination (TEC) scheme, where TCL users submit bids for their energy demand and an aggregator clears the market to allocate energy among users. This study confirms the presence of such issues. To avoid these unintended consequences of load control, a Markov-chain-based state-transition model has been developed to capture the aggregate TCL dynamics under TEC. Using the state-transition model, a model predictive control scheme has been formulated to attain near-optimal control policies that maximize social welfare while limiting the possibilities of TCL synchronization and power oscillations. To further investigate unintended behavior arising from the control of load ensembles, a generalized hybrid dynamical system representation is developed to accurately capture the interactions between the continuous dynamics of loads and discrete control actions. This representation can capture diverse control-update intervals, from fifteen-minute intervals for economic dispatch problems to 2-10 seconds for frequency regulation services. Using this hybrid representation and modal analysis, it is shown that synchronizing behavior in TCLs can be identified under a wide range of control schemes, such as probabilistic and priority-based switching, and TEC. A number of practical constraints, such as limited availability of TCLs for control and/or limited TCL parameter information, are considered to quantify performance bounds of load control schemes. To compute the aggregate flexibility available from spatially distributed DERs, special convex sets known as homothets and zonotopes are employed. First, aggregation algorithms are developed assuming DERs are located at a single node of the network. The setting is then extended to spatially distributed resources by incorporating the network and power flow constraints. It is shown that network parameters and voltage limits often limit the flexibility that can be transferred from one node to its upstream or downstream neighbors. This flexibility model lends itself to several applications, including optimal power flow in distribution networks and efficient coordination of transmission and distribution systems.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155079/1/mdsnazir_1.pd

Loss allocation in a distribution system with distributed generation units

In Denmark, a large part of the electricity is produced by wind turbines and combined heat and power plants (CHPs). Most of them are connected to the network through distribution systems. This paper presents a new algorithm for allocation of the losses in a distribution system with distributed generation. The algorithm is based on a reduced impedance matrix of the network and current injections from loads and production units. With the algorithm, the effect of the covariance between production and consumption can be evaluated. To verify the theoretical results, a model of the distribution system in Brønderslev in Northern Jutland, including measurement data, has been studied