Duy Thanh Nguyen

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.

Walrasian Market Clearing for Demand Response Exchange

This paper presents the design and evaluation of an effective market-clearing scheme for trading demand response (DR) in a deregulated power system. The proposed scheme is called demand response exchange (DRX), in which DR is treated as a public good to be exchanged between two groups of participating agents, namely DR buyers and DR sellers. While buyers require DR and are willing to pay for it, sellers have the capacity to curtail customer loads to supply DR on request. The DRX market clearing scheme uses Walrasian auctions, where agents update their DR quantity bids in response to prices adjusted by the market operator. This auction is repeated iteratively until market equilibrium is obtained at the point where the market outcome is proven to be Pareto optimal. The proposed scheme is tested on a small power system and its effectiveness substantiated.

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.

Demand response for domestic and small business consumers: A new challenge

There is a need to integrate Demand Response (DR) into the management of the electricity market and power system within both planning and operational timescales. This paper reviews some issues of DR for domestic and small business consumers, in both the United States and Australian contexts. The advantages and limitations of two types of DR, namely reliability-based DR and price-based DR are discussed through examining related studies. The paper claims that neither price-based DR nor reliability-based DR can maximize the DR benefit if applied alone in a deregulated environment. In particular, a reliability-based program unfortunately achieves the lowest level of benefits since it only addresses short-term market conditions rather than the long-term impacts. A price-based program considering long-term benefits may sometimes incur short-term financial losses due to price spikes caused by unplanned network outages or shortfalls of intermittent power supply. The paper finally suggests a new hybrid framework, in which both price-based and reliability-based programs are able to cooperate with each other through an information management system within both planning and operational timescales.

Energy Exchange Between Electric Vehicle Load and Wind Generating Utilities

This paper proposes a novel approach to energy exchange between electric vehicle (EV) load and wind generation utilities participating in the day-ahead energy, balancing, and regulation markets. An optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. A new strategy model is based on optimizing decision making of a wind generating company (WGenCO) in selecting the best option among the use of the balancing or regulation services, the use of the energy storage system (ESS) and the use of all of them to compensate wind power deviation. Energy imbalance is discussed using conventional systems, ESS, and EV-Wind coordination; results are compared and analyzed. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MILP). Uncertainties associated with wind forecasting, energy price, and behavior of EV owners based on their driving patterns, are considered in the proposed stochastic method and validated through several case studies.

A new and separated market for demand response in restructured power systems

This paper introduces a new and separated market for the trading of Demand Response (DR) in a restructured power system. This market is called Demand Response eXchange or shortly DRX, in which DR is treated as a virtual resource to be exchanged between DR buyers and sellers. Buyers — including the Transmission System Operator (TSO), distributors, and retailers — need DR to improve the efficiency and reliability of their own businesses and systems. Sellers — including consumers though an aggregator — negotiate DR with those buyers. The DRX is modeled in the form of a pool-based market using microeconomic theory. In this market, a DRX Operator (DRXO) collects bids and offers from DR buyers and sellers respectively. It then clears the market by maximizing the total market benefit subject to certain operational constraints. The DRX model is also tested on a small power system in comparison to conventional DR approaches, and its advantages are reported.

Modeling Load Uncertainty in Distribution Network Monitoring

In this paper we describe an analytical method for estimating uncertainty in distribution loads, with applications to network monitoring and optimal meter placement. Our model works by assessing the impact of consumption aggregation from customers of different types, in order to determine the mean and variance of loading profile in each distribution transformer in the network. Such parameters are then adjusted by correlating with real-time information taken from the supervisory control and data acquisition system. Studies have been conducted on actual data to verify the proposed model and show its application for the optimal meter placement in distribution networks.

Short-term valuation of demand response

This paper proposes a novel assessment framework for estimating short-term financial benefits of demand response (DR) to be delivered to a deregulated power system. First, the framework analyzes DR costs and benefits for participants in a DR market, and for generators and retailers in the electricity trading market. Based on these local analyses, a global evaluation is performed to determine whether the optimized DR can produce a positive social surplus. If so, the DR will be dispatched during the time period under consideration. Case study is given on the Roy Billinton test system (RBTS) to show the usefulness of the proposed assessment framework and to examine its scalability.

Correlation properties of wavelet transform and applications in image coding

In the paper the correlation properties of wavelet transform coefficients are studied. By employing a high correlation property of the wavelet transform coefficients along the same prediction channels, a hybrid image coding system is proposed and designed. The simulation results show that the developed coding scheme is superior to its counterparts.

Integrating demand response market into energy/reserve market: A bilevel approach

The concept of demand response (DR) market, which recently introduced, is a comprehensive approach to schedule DR. DR market is a separate market in which DR is treated as a virtual resource to be exchanged between DR buyers and sellers. The major advantage of the DR market in comparison to other DR proposals is that it allocates benefits and payments across all participants, fairly. However, there are still obstacles to its integration into the existing power markets. This paper tries to address technical and economical issues towards integrating DR market into energy/reserve markets. For this purpose, a bilevel approach is proposed for clearing joint energy/reserve and DR markets whose upper-level problem determines system requirements for reserve using N-1 contingency criteria, and whose lower-level problem clears the DR market. The resulting nonlinear bilevel programming problem is translated into an equivalent single-level mixed-integer linear programming problem by replacing the lower-level problem by its Karush- Kuhn-Tucker optimality conditions and converting a number of nonlinearities to linear equivalents using some well-known techniques. Finally, a simple case study is used to verify the efficiency of the proposed approach.