Martin de Groot

Pool-Based Demand Response Exchange—Concept and Modeling

In restructured power systems, there are many independent players who benefit from demand response (DR). These include the transmission system operator (TSO), distributors, retailers, and aggregators. This paper proposes a new concept-demand response eXchange (DRX)-in which DR is treated as a public good to be exchanged between DR buyers and sellers. Buyers need DR to improve the reliability of their own electricity-dependent businesses and systems. Sellers have the capacity to significantly modify electricity demand on request. Microeconomic theory is applied to model the DRX in the form of a pool-based market. In this market, a DRX operator (DRXO) collects DR bids and offers from the buyers and sellers, respectively. It then clears the market by maximizing the total market benefit subject to certain constraints including: demand-supply balance, and assurance contracts related to individual buyer contributions for DR. The DRX model is also tested on a small power system, and its efficiency is reported.

Market-Based Demand Response Scheduling in a Deregulated Environment

In this paper we investigate efficient schemes for scheduling demand response (DR) in a deregulated environment. We begin with an analysis of partial schemes which are being implemented in many established markets. These schemes can be considered inefficient due to externalities that occur amongst DR beneficiaries including the transmission network company (Transco), distribution network companies (Discos), and retail electricity companies (Recos). This limitation of existing schemes motivates the development of a new concept-demand response exchange (DRX)-a separated market for trading DR fairly and flexibly across all beneficiaries. The DRX concept is realized by introducing a pool-based market clearing scheme. Extensive simulations are provided to illustrate the effectiveness of our DRX proposal.

Modeling Load Recovery Impact for Demand Response Applications

In this paper we develop a novel mathematical model to describe the localized economic impact of load recovery by electricity consumers following demand response (DR) event participation. In this model-termed “securitization”-cost and benefit associated with an amount of load recovery change exponentially with time-varying stochastic discount rates. These volatile rates, which can be estimated using the principle of Brownian motion, are further examined via case studies on the Roy Billinton test system. A formal application of the proposed recovery model to the crucial task of global DR scheduling is then studied. The study indicates that it is possible to optimize a DR schedule to cater for uncertainty in the subsequent load recovery.

Pool-based Demand Response Exchange: Concept and modeling

In restructured power systems, there are many independent players who benefit from demand response (DR). These include the transmission system operator (TSO), distributors, retailers, and aggregators. This paper proposes a new concept-demand response eXchange (DRX)-in which DR is treated as a public good to be exchanged between DR buyers and sellers. Buyers need DR to improve the reliability of their own electricity-dependent businesses and systems. Sellers have the capacity to significantly modify electricity demand on request. Microeconomic theory is applied to model the DRX in the form of a pool-based market. In this market, a DRX operator (DRXO) collects DR bids and offers from the buyers and sellers, respectively. It then clears the market by maximizing the total market benefit subject to certain constraints including: demand-supply balance, and assurance contracts related to individual buyer contributions for DR. The DRX model is also tested on a small power system, and its efficiency is reported.

Effect of the diesel engine delay on stability of isolated power systems with high levels of renewable energy penetration

Isolated power systems (IPSs) up to 20MW capacity are traditionally based on diesel generators. Due to the high cost of diesel fuel supply, as well as environmental concerns, IPSs are increasingly integrating renewable generation. Since traditional diesel generation was built for slow changing, diesel-only systems some IPSs might experience problems in the future, while trying to support fast-changing, intermittent renewable generation. This paper argues that engine delay, together with the governor and inertia, has to be considered when designing a high renewable penetration IPS based on diesel generators for reserve capacity. Our simulation results show that some diesel generators have advantage over others in governing the system and preserving power system stability.

Demand response in Isolated Power Systems

Isolated Power Systems (IPS) are stand-alone MW-scale (or even KW-scale) grids. They generally have higher supply costs and are less stable than GW-scale interconnected grids. Demand response (DR) could give a greater cost benefit per unit of delivered power in IPS applications than in larger grids. However, it is also likely to have higher installation and operation costs per unit of DR capacity. We review the most significant issues for DR in IPS, and illustrate the benefits with a current project to install a fine-grained demand management system on King Island in Australia.

Demand Response aware cluster resource provisioning for parallel applications

Data center energy consumption is significant and accounts for about 2% of total energy use in the U.S. recently. A range of approaches, from cooling techniques to workload consolidation have been taken to improve data center energy efficiency. In contrast to most methods published so far, this paper treats a data centre as a consumer in an electricity market. Our intention is to make data centres more responsive to electricity market conditions with minimal impact on their performance. In electricity markets, Demand Response(DR) is a method for improving grid efficiency by encouraging consumers to adjust their demand during price peaks or network stress. Significant consumption and cost savings can potentially be made via implementing DR programs involving a large set of consumers. Traditionally, DR has been a largely manual process, however, automated DR is becoming increasingly prevalent due to the deployment of smart grid technologies. In this paper, we treat the server cluster in a data centre as an energy consumer that participates DR activities. We give two algorithms to enable the cluster to automatically adjust the number of active servers to respond to DR requests while maintaining acceptable system performance. We evaluate our algorithms using real traces.

Enabling Demand Response in a computer cluster

Demand Response(DR) is a method for stimulating end-users to adjust consumption to support the change in the electricity market. DR can be used to improve the stability of power supply including the power generation, transmission and distribution. It can also be used to improve electricity market operation. Furthermore, significant cost savings can be made on the consumer side via the financial incentives in a range of DR programs. As the cloud computing paradigm gains popularity, there is an associated rapid growth of public and private data centers. Data center energy consumption increases significantly. Putting data center energy consumption in the context of power grid becomes important. In this paper, we propose an architecture to integrate data centre computer clusters with a DR service. The resource manager of a cluster can therefore take DR events into account when allocating resources. We particularly focus on resource provisioning for parallel workloads in such a cluster, and propose a DR strategy that is capable of balancing energy savings and user satisfaction.

Hardware Security Device Facilitated Trusted Energy Services

We report on our experiences in developing a hardware based security solution for a novel, smart-grid enabled energy services system. In this paper, we first give a background to a new energy services model and then describe how we incorporated a CSIRO developed portable trusted computing platform into a practical, prototype system which assures that all transactions between the energy service company and the consumer are trustworthy, secure and private.

Integrating formal methods with system management

Monitoring and fault diagnosis are core management tasks for deployed industrial systems. Diagnostic reasoning is closely related to reasoning about implementation correctness. A framework to support the integration of both reasoning tasks is introduced. Many well known formal methods for stepwise program refinement are shown to be compatible with the framework. Compatibility is achieved by treating a formal development as a hierarchical model of the implemented system and then adapting model-based reasoning techniques.