Market-based Control of Air-Conditioning Loads with Switching Constraints for Providing Ancillary Services

Air-conditioning loads (ACLs) are among the most promising demand side resources for their thermal storage capacity and fast response potential. This paper adopts the principle of market-based control (MBC) for the ACLs to participate in the ancillary services. The MBC method is suitable for the control of distributed ACLs because it can satisfy diversified requirements, reduce the communication bandwidth and protect users' privacy. The modified bidding and clearing strategies proposed in this paper makes it possible to adjust the switching frequency and strictly satisfy the lockout time constraint for mechanical wear reduction and device protection, without increasing the communication traffic and computational cost of the control center. The performance of the ACL cluster in two typical ancillary services is studied to demonstrate the effect of the proposed method. The case studies also investigate how the control parameters affect the response performance, comfort level and switching frequency.Comment: 5 pages, conferenc

Potential of a population of domestic heat pumps to provide balancing service

This paper investigates the model of aggregated heat pumps as a source of the flexible load in Great Britain. A thermal model of a domestic heat pump was presented. A decentralised temperature control algorithm was proposed to control the building temperature, and heat pump’s ON and OFF cycles. Seven case studies were used to identify the suitable number of individual heat pump models that can be aggregated to accurately represent the projected number of heat pumps connected to the 2030 GB’s power system. The simulation results revealed that an aggregated model of 5,000 individual heat pumps was accurately representing the entire number of heat pumps in the Great Britain power system. Also, the power consumption of a group of heat pumps was examined in response to the grid frequency. Simulation results showed that the power consumption of aggregated heat pumps was successfully controlled in response to a frequency change. The controlled heat pumps reduced the dependency on the frequency service obtained by expensive peaking generators

Distributed energy storage using residential hot water heaters

This paper proposes and analyses a new demand response technique for renewable energy regulation using smart hot water heaters that forecast water consumption at an individual dwelling level. Distributed thermal energy storage has many advantages, including high overall efficiency, use of existing infrastructure and a distributed nature. In addition, the use of a smart thermostatic controller enables the prediction of required water amounts and keeps temperatures at a level that minimises user discomfort while reacting to variations in the electricity network. Three cases are compared in this paper, normal operation, operation with demand response and operation following the proposed demand response mechanism that uses consumption forecasts. The results show that this technique can produce both up and down regulation, as well as increase water heater efficiency. When controlling water heaters without consumption forecast, the users experience discomfort in the form of hot water shortage, but after the full technique is applied, the shortage level drops to nearly the starting point. The amount of regulation power from a single dwelling is also discussed in this paper

Review of techniques to enable community-scale demand response strategy design

Incorporating demand side flexibility can aid in integrating intermittent renewable energy generation and reducing the electricity grid’s operational costs. Buildings have the potential to provide demand response (DR) with minimal disruption to activities by leveraging the inherent energy storage in their heating ventilation and air conditioning (HVAC) systems. Harnessing this flexibility whilst minimising energy consumption and maintaining thermal comfort requires control strategies capable of incorporating these objectives, making model-predictive control (MPC) a promising framework. To elucidate the control techniques available to harness the HVAC flexibility of collections of buildings to participate in electricity markets, this paper reviews the current state of literature describing MPC techniques for community-scale control. The reviewed studies were classified based the following characteristics: the general aim of the MPC approach, objective function, thermal response model, amount and type of buildings considered, DR type, control structure, solving tools and techniques, and the energy, cost savings or flexibility achieved. The review shows that MPC strategies can successfully provide many types of DR indicating the versatility of the control approach. Decentralised control approaches reduced the complexity of the large-scale control problem whilst providing more autonomy to individual users. However, compared to centralised approaches, decentralised control led to lower amounts of flexibility. Lastly, few studies validated the performance of their controller in either simulation or physical environments. Therefore, the review suggests further research is needed to study and validate the performance the of different MPC control structures considering various community types and concurrent participation in various DR schemes

Customer Engagement Plans for Peak Load Reduction in Residential Smart Grids

In this paper, we propose and study the effectiveness of customer engagement plans that clearly specify the amount of intervention in customer's load settings by the grid operator for peak load reduction. We suggest two different types of plans, including Constant Deviation Plans (CDPs) and Proportional Deviation Plans (PDPs). We define an adjustable reference temperature for both CDPs and PDPs to limit the output temperature of each thermostat load and to control the number of devices eligible to participate in Demand Response Program (DRP). We model thermostat loads as power throttling devices and design algorithms to evaluate the impact of power throttling states and plan parameters on peak load reduction. Based on the simulation results, we recommend PDPs to the customers of a residential community with variable thermostat set point preferences, while CDPs are suitable for customers with similar thermostat set point preferences. If thermostat loads have multiple power throttling states, customer engagement plans with less temperature deviations from thermostat set points are recommended. Contrary to classical ON/OFF control, higher temperature deviations are required to achieve similar amount of peak load reduction. Several other interesting tradeoffs and useful guidelines for designing mutually beneficial incentives for both the grid operator and customers can also be identified