Learning Dynamical Demand Response Model in Real-Time Pricing Program

Price responsiveness is a major feature of end use customers (EUCs) that participate in demand response (DR) programs, and has been conventionally modeled with static demand functions, which take the electricity price as the input and the aggregate energy consumption as the output. This, however, neglects the inherent temporal correlation of the EUC behaviors, and may result in large errors when predicting the actual responses of EUCs in real-time pricing (RTP) programs. In this paper, we propose a dynamical DR model so as to capture the temporal behavior of the EUCs. The states in the proposed dynamical DR model can be explicitly chosen, in which case the model can be represented by a linear function or a multi-layer feedforward neural network, or implicitly chosen, in which case the model can be represented by a recurrent neural network or a long short-term memory unit network. In both cases, the dynamical DR model can be learned from historical price and energy consumption data. Numerical simulation illustrated how the states are chosen and also showed the proposed dynamical DR model significantly outperforms the static ones.Comment: Accepted to IEEE ISGT NA 201

Distributed voltage-driven demand response: flexibility, stability and value assessment

The need for operating reserve from energy storage, demand reduction (DR) etc. is expected to increase signifcantly in future low-carbon Great Britain (GB) power system with high penetration of non-synchronous renewable generation. One way to provide the reserve is to use power electronic compensators (PECs) for point-of-load voltage control (PVC) to exploit the voltage dependence of loads. This thesis focuses on the quantifcation of DR capability from PVC in the domestic sector using high-resolution stochastic demand models and generic distribution networks in GB. The effectiveness of utilising PVC in contributing to frequency regulation is analysed and demonstrated through time domain simulations. The techno-economic feasibility of such technology is evaluated considering the investment cost of the PEC deployment as well as the economic and environmental benefts of using PVC. The payback period varies between 0.3 to 6.7 years for different future scenarios considering a range of converter price. It is demonstrated that PVC could effectively complement battery energy storage system towards enhanced frequency response provision in future GB power system. For practical application of PVC for flexible demand and voltage regulation in future distribution networks/microgrids, it is important to investigate the overall small signal stability of the system. In this thesis, the linearised state space model of a distribution network/isolated microgrid with converter-interfaced distributed generators (CDGs) working in grid following mode along with loads with PVC is developed. The stability performance is revealed through both modal analysis and time domain simulations. It is shown that multiple loads with PVC for voltage regulation in distribution networks are not likely to threaten the small signal stability of the system. In the case of a microgrid, the introduction of PVC is shown to have marginal impact on the low frequency modes associated with the droop control of the CDGs. However, there is a trade-off when choosing the droop gain of the loads with PVC. Lower droop gains could ensure better frequency regulation in face of intermittent renewables but at the expense of a lower stability margin for an oscillation mode at a frequency slightly higher than 20Hz.Open Acces

Electric spring and smart load: technology, system-level impact and opportunities

Increasing use of renewable energy sources to combat climate change comes with the challenge of power imbalance and instability issues in emerging power grids. To mitigate power fluctuation arising from the intermittent nature of renewables, electric spring has been proposed as a fast demand-side management technology. Since its original conceptualization in 2011, many versions and variants of electric springs have emerged and industrial evaluations have begun. This paper provides an update of existing electric spring topologies, their associated control methodologies, and studies from the device level to the power system level. Future trends of electric springs in large-scale infrastructures are also addressed

IMPACT OF PLUG-IN ELECTRIC VEHICLES AND WIND GENERATORS ON HARMONIC DISTORTION OF ELECTRIC DISTRIBUTION SYSTEMS

Harmonic distortion on voltages and currents increases with the increased penetration of Plug-in Electric Vehicle (PEV) loads in distribution systems. Wind Generators (WGs), which are source of harmonic currents, have some common harmonic profiles with PEVs. Thus, WGs can be utilized in careful ways to subside the effect of PEVs on harmonic distortion. This work studies the impact of PEVs on harmonic distortions and integration of WGs to reduce it. A decoupled harmonic three-phase unbalanced distribution system model is developed in OpenDSS, where PEVs and WGs are represented by harmonic current loads and sources respectively. The developed model is first used to solve harmonic power flow on IEEE 34-bus distribution system with low, moderate, and high penetration of PEVs, and its impact on current/voltage Total Harmonic Distortions (THDs) is studied. This study shows that the voltage and current THDs could be increased upto 9.5% and 50% respectively, in case of distribution systems with high PEV penetration and these THD values are significantly larger than the limits prescribed by the IEEE standards. Next, carefully sized WGs are selected at different locations in the 34-bus distribution system to demonstrate reduction in the current/voltage THDs. In this work, a framework is also developed to find optimal size of WGs to reduce THDs below prescribed operational limits in distribution circuits with PEV loads. The optimization framework is implemented in MATLAB using Genetic Algorithm, which is interfaced with the harmonic power flow model developed in OpenDSS. The developed framework is used to find optimal size of WGs on the 34-bus distribution system with low, moderate, and high penetration of PEVs, with an objective to reduce voltage/current THD deviations throughout the distribution circuits. With the optimal size of WGs in distribution systems with PEV loads, the current and voltage THDs are reduced below 5% and 7% respectively, which are within the limits prescribed by IEEE

On the Control of Active End-nodes in the Smart Grid

The electrical grid has substantially changed in recent years due to the integration of several disruptive load and generation technologies into low-voltage distribution networks, which are meant to smarten it and improve its efficiency. These technologies have subjected the grid to unprecedented amounts of variability and uncertainty that threaten its reliability and could reduce its efficiency. Even a low penetration of these disruptive technologies may cause equipment overloads, voltage deviations beyond permissible operating thresholds, and bidirectional power flows in distribution networks. The smart grid will comprise a vast number of active end-nodes, including electric vehicle chargers, solar inverters, storage systems, and other elastic loads, that can be quickly controlled to adjust their real and reactive power contributions. Given the availability of inexpensive measurement devices and a broadband communication network that connects measurement devices to controllers, it is possible to incorporate potentially disruptive technologies into distribution networks while maintaining service reliability, using some novel control mechanisms, which are the focus of this thesis. In this thesis, we propose a new paradigm for the control of active end-nodes at scale. This control paradigm relies on real-time measurements of the states of the distribution network and the end-nodes rather than long-term predictions. We use an optimal control framework to design mechanisms that balance a set of system-level and user-level objectives. We study control of active end-nodes in two different contexts: a radial distribution system and a grid-connected public electric vehicle charging station powered by on-site solar generation. We develop both a feedback controller and an open-loop controller, and propose centralized and distributed algorithms for solving optimal control problems. We implement and validate these control mechanisms using extensive numerical simulations and power flow analysis on a standard test system

Increasing the capacity of distributed generation in electricity networks by intelligent generator control

The rise of environmental awareness as well as the unstable global fossil fuel market has brought about government initiatives to increase electricity generation from renewable energy sources. These resources tend to be geographically and electrically remote from load centres. Consequently many Distributed Generators (DGs) are expected to be connected to the existing Distribution Networks (DNs), which have high impedance and low X/R ratios. Intermittence and unpredictability of the various types of renewable energy sources can be of time scales of days (hydro) down to seconds (wind, wave). As the time scale becomes smaller, the output of the DG becomes more difficult to accommodate in the DN. With the DGs operating in constant power factor mode, intermittence of the output of the generator combined with the high impedance and low X/R ratios of the DN will cause voltage variations above the statutory limits for quality of supply. This is traditionally mitigated by accepting increased operation of automated network control or network reinforcement. However, due to the distributed nature of RES, automating or reinforcing the DN can be expensive and difficult solutions to implement. The Thesis proposed was that new methods of controlling DG voltage could enable the connection of increased capacities of plant to existing DNs without the need for network management or reinforcement. The work reported here discusses the implications of the increasing capacity of DG in rural distribution networks on steady-state voltage profiles. Two methods of voltage compensation are proposed. The first is a deterministic system that uses a set of rules to intelligently switch between voltage and power factor control modes. This new control algorithm is shown to be able to respond well to slow voltage variations due to load or generation changes. The second method is a fuzzy inference system that adjusts the setpoint of the power factor controller in response to the local voltage. This system can be set to respond to any steady-state voltage variations that will be experienced. Further, control of real power is developed as a supplementary means for voltage regulation in weak rural networks. The algorithms developed in the study are shown to operate with any synchronous or asynchronous generation wherein real and reactive power can be separately controlled. Extensive simulations of typical and real rural systems using synchronous generators (small hydro) and doubly-fed induction generators (wind turbines) have verified that the proposed approaches improve the voltage profile of the distribution network. This demonstrated that the original Thesis was true and that the techniques proposed allow wider operation of greater capacities of DG within the statutory voltage limits

Report on international experiences with E1st

The new report constitutes a step towards achieving the objective of making the Efficiency First (E1st) principle operational in EU decision making. The report includes 16 examples of how E1st has been applied in different contexts, from promoting the fabric first approach in buildings, enabling demand response to compete on electricity markets, requiring demand-side resources to be better taken into account in energy planning, to demand flexibility in district heating and avoiding new power plants. Each example details the implementation bodies, how the E1st principle has been implemented and the related barriers, replicability and scalability potential. The report also provides an overview about why E1st has been implemented, how the approach to E1st can be categorized, and what lessons can be learned from these experiences. The examples show policymakers, regulators, and energy policy actors that the concept of E1st can be implemented and can provide various benefits to the energy transition