Experimental validation of the demand response potential of residential heating systems

To effectively exploit the potential of demand response, knowledge regarding the availability of flexibility is crucial. In this paper, the flexibility of residential heating systems is assessed using the results of the Dutch smart grid pilot PowerMatching City. Within this pilot a multi-objective multi-agent system is used to exploit the flexibility of residential heat pumps and micro-CHPs. To validate the practical flexibility, a data-driven approach is proposed, in which the measured load is used to evaluate the effect of the smart-grid control signal on load changes. As this effect is subjected to other variables as well, the load is considered as a function of time, weather circumstances and the control signal. Two types of load forecasting techniques are applied to model the response of the load to these variables: multiple regression and Artificial Neural Networks (ANNs). Both forecasters obtain comparable results regarding the available flexibility of the devices. However, the results indicate that ANNs are slightly better at capturing the non-linearity of flexibility

Assessing the impact of distributed energy resources on LV grids using practical measurements

Due to the fundamental changes in the energy system, electricity load profiles in residential areas are expected to change profoundly in the coming decades. Until now, the effects of the energy transition for the power system are mainly studied using synthetic load profiles. In this paper, load measurements from three different newly built residential areas were used to study the (local) impact of an increasing penetration of PV panels and heat pumps. Using these measurements, the bottlenecks and opportunities due to these technologies are identified. The results can be used to reflect and possibly optimize the residential load models used by distribution system operators for network planning, allocation and reconciliation processes

Classification of reserve capacity in future power systems

In electrical power systems must always be a balance between supply and demand. Any imbalance will result in a frequency deviation. To reduce the imbalance to zero, ancillary services for balancing are in use. Ancillary services are characterised by their deployment time and their capacity. By using Discrete Fourier Transform, the kind of ancillary services as well as the requirements for balance management can be characterised in the frequency domain. Agents, that are responsible for maintaining balance in a network, can use the characterisation in the frequency domain to define their needs for reserve capacity. This paper describes a method for spectral analysis of the required reserve capacity. Based on examples and a model, changes in a future power system are discussed using the frequency domain

Decentralised allocation of generation in autonomous power networks

Due to much larger numbers of small generators it will be more complex to control the balance between supply and demand in future power systems. To deal with this complexity, autonomous power networks could be effective. Autonomous power networks are aggregations of producers and consumers on both physical and economical level and have the capability to control complex systems with simple rules. To demonstrate economic dispatch within an autonomous power network, this paper describes the setup of a model for matching supply and demand within control zones. Next, a method for distributed economic dispatch is incorporated in the model to show how allocation of generators can be executed in a decentralised way

Load shifting potential of the washing machine and tumble dryer

Various smart grid pilots are being initiated worldwide to explore the flexibility in electricity demand of households. The potential flexibility of appliances can be unlocked using either manual or (semi-)automated demand response. In the Dutch smart grid pilot Your Energy Moment the effect of demand response is studied. The participating households are equipped with a smart washing machine or smart tumble dryer. These appliances can be used to manually respond to the dynamic tariff applied in the pilot, or cycles can be programmed to automatically respond to price fluctuations. Based on the pilot results, the total load shift of the washing machine and tumble dryer is quantified. Subsequently, the effect of the program function is studied, focusing on the use of this function and on the flexible hours provided for the schedule horizon. The results show that the load of the smart appliances is shifted in time. This load shift is a consequence of both manual and semi-automated load shift. The latter, semi-automated load shift related to the use of the program function, is however limited. Both the measured manual and semi-automated load shift did not change over time, indicating a structural change in behavior

Participation of distributed generation in balance management

Distributed generation is not yet considered to participate in balance management in power systems. Low marginal costs and poor predictability make them less attractive for this application. However, further integration of distributed generation will make participation in balance management a necessity both for down regulation as well as up regulation. The potential of different distributed generators to participate in balance management is analysed. Economic and regulatory boundaries are discussed, as well as improvements to create incentives for distributed generators to participat

A methodology to assess demand response benefits from a system perspective: A Dutch case study

\u3cp\u3eTo support decision-making about the implementation of demand response, insight into the prospects and value creation is essential. As the potential benefits are diverse and distributed amongst various power system stakeholders, a system perspective is necessary for their assessment. This paper describes a methodology to model the long-term demand response benefits from a system perspective. To quantify the benefits both the energy market value and the grid value are assessed. In a liberalized power system these benefits can generally be assigned to the two main electric utilities, i.e., the energy supplier and the grid operator. The applicability of the developed approach is demonstrated using the Netherlands as a case study and a model developed from actual data from the Dutch power system. Within this model, different demand-response strategies are implemented to shape the flexible future load available for residential areas. The potential benefits of the following demand-response strategies are quantified: grid based, energy market based and energy market based with capacity constraints. The results show that from a system perspective, a demand-response strategy that is energy market based with capacity constraints is most effective in terms of realizing system benefits from residential flexibility.\u3c/p\u3

Assessing the economic benefits of flexible residential load participation in the Dutch day-ahead spot and balancing markets

In this paper the authors present the potential cost-savings that may arise due to demand response from residential customers participating in the Amsterdam Power eXchange (APX) day-ahead auction and the Dutch balancing energy market which is organised by TenneT, the Dutch Transmission System Operator (TSO). For this purpose, a model for residential demand response is developed that utilises as input historical market data. Furthermore, the model synthesises a daily load profile based on load profiles of Dutch residential customers and simulated data to represent aggregate demands of domestic appliances and electric vehicles. The model is built around the concept of the aggregator, an envisioned legal entity, that contracts large amounts of residential customers and then coordinates them in real-time under different objectives (i.e. economic optimisation based on predicted day-ahead prices and the provision of balancing energy). Simulation results show that the potential economic benefits of residential demand response, on the Dutch electricity markets, is relatively low on a per household basis, but not negligible for the business case of the aggregator