Kit Po Wong

A Statistical Approach for Interval Forecasting of the Electricity Price

Electricity price forecasting is a difficult yet essential task for market participants in a deregulated electricity market. Rather than forecasting the value, market participants are sometimes more interested in forecasting the prediction interval of the electricity price. Forecasting the prediction interval is essential for estimating the uncertainty involved in the price and thus is highly useful for making generation bidding strategies and investment decisions. In this paper, a novel data mining-based approach is proposed to achieve two major objectives: 1) to accurately forecast the value of the electricity price series, which is widely accepted as a nonlinear time series; 2) to accurately estimate the prediction interval of the electricity price series. In the proposed approach, support vector machine (SVM) is employed to forecast the value of the price. To forecast the prediction interval, we construct a statistical model by introducing a heteroscedastic variance equation for the SVM. Maximum likelihood estimation (MLE) is used to estimate model parameters. Results from the case studies on real-world price data prove that the proposed method is highly effective compared with existing methods such as GARCH models.

Quantum-Inspired Evolutionary Algorithm Approach for Unit Commitment

This paper presents a novel method for solving the unit commitment (UC) problem based on quantum-inspired evolutionary algorithm (QEA). The proposed method applies QEA to handle the unit-scheduling problem and the Lambda-iteration technique to solve the economic dispatch problem. The QEA method is based on the concept and principles of quantum computing, such as quantum bits, quantum gates and superposition of states. QEA employs quantum bit representation, which has better population diversity compared with other representations used in evolutionary algorithms, and uses quantum gate to drive the population towards the best solution. The mechanism of QEA can inherently treat the balance between exploration and exploitation and also achieve better quality of solutions, even with a small population. The proposed method is applied to systems with the number of generating units in the range of 10 to 100 in a 24-hour scheduling horizon and is compared to conventional methods in the literature. Moreover, the proposed method is extended to solve a large-scale UC problem in which 100 units are scheduled over a seven-day horizon with unit ramp-rate limits considered. The application studies have demonstrated the superior performance and feasibility of the proposed algorithm.

A Modified Differential Evolution Algorithm With Fitness Sharing for Power System Planning

The application of evolutionary computation methods in search and optimization has been growing over the past few decades. As a promising approach in metaheuristic optimization algorithms, differential evolution (DE) has been attracting increasing attention for wide engineering applications including power engineering. Different from conventional evolutionary algorithms using predefined probability distribution function for mutation process, differential evolution exploits the differences of randomly sampled pairs of objective vectors for its mutation process. Consequently the variation between vectors will outfit the objective functions topographical information toward the optimization process, and therefore provides efficient global optimization capability. However, although DE is shown to be precise, fast as well as robust, its search efficiency will be impaired during solution process with fast descending diversity of population. In this paper, detailed numerical studies are carried out to propose the characterization of the performance of several DE mutation methods with and without fitness sharing scheme. All the approaches using the proposed modified DE are presented on an example in power system planning.

Wind power impact on system operations and planning

With the emission reduction scheme introduced, increasing number of wind farms have been planned and/or installed in many countries. In this paper, issues with wind power connection to the existing power grid are discussed, with particular emphasize on system operations and planning aspects. In addition to power system analysis, implications of wind power impacts on the electricity market operations are also discussed. From power system operations, wind power introduces stability and control challenges which are reflected in frequency control and voltage control ancillary services in a market environment. From system planning point of view, the increasing number of wind generation connection requests from generators requires a more systematic approach toward system studies on the connection impact on transmission system planning. The research presented in this paper focus on the wind power practice in Hong Kong and Australia. Case studies based on data from Australia and Hong Kong are given in this paper to highlight some of the issues and methodologies relevant to wind power impact studies. Issues on wind power impact on system operations and planning (general discussion paper, key words: wind power optimal dispatch with other generating resources, wind forecast utilization, network frequency control ancillary services, voltage control ancillary services, TAS example, HK example; key techniques: operational schemes, optimization methods, security constraints, impact on market - constraint impact; network connection options analysis;)

Wide-Area Protection and its Applications - A Bibliographical Survey

Modern power systems are continuously developing to large and interconnected ones. The power industry restructuring and the reduced investment in transmission system expansion make power systems operate closer and closer to their limits, and hence lead to larger possibility of fault outages than before. Therefore, the protection and control in power systems become more and more important as well as complicated. On the other hand, the continuous technological development in communication and measurement accelerates the occurrence and applications of wide-area protection, a kind of advanced protections based on wide-area measurements. The blackouts happened in North America as well as other countries in the past few years also provide more and more incentive for scientists and engineers in the power system circle to devote to the study on wide-area protection and control systems. In this paper, a comprehensive bibliographical survey is made on recent development in this field, and the survey is done from seven relevant aspects

Transient stability assessment on China Southern Power Grid system with an improved pattern discovery-based method

Intelligent systems (IS) have been widely adopted to facilitate very fast transient stability assessment (TSA) to prevent blackouts. More recently, a TSA model based on pattern discovery (PD) method has been proposed and demonstrated on several IEEE standard test systems. It has exhibited many attractive features, including high accuracy, ability to provide classification rules and system weak-points information, etc. In this paper, the PD-based TSA method is further improved by use an alternative feature selection method which is very computational efficient and tend to result in better performance. The improved model is examined on China Southern Power Grid dynamic equivalent system and compared with state-of-art IS methods. The simulation results show that the improved model has been significantly improved in modelling efficiency and its accuracy is competitive with state-of-the-art IS techniques.

Genetic algorithm-based spinning reserve dispatching in a competitive electricity market

Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISOs total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market.

Optimal dispatch of spinning reserve in a competitive electricity market using genetic algorithm

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.

Differential evolution algorithm for multi-objective economic load dispatch considering minimum emission costs

This paper describes a multi-objective economic load dispatch (ELD) model to minimize the emission cost due to CO2 and N2O. The power system operation costs are minimized under transmission network constraints in ELD. This model will be transformed from single objective economic problem to multi-objective problem to combine both economic and emission dispatch. The model is implemented by Differential Evolution (DE) and a set of numerical experiments for a standard test system is reported.

New issues on reliable and efficient operation of the National Electricity Market of Australia

The Australian national electricity market (NEM) has been in operation for almost 10 years. It is so far one of the successful electricity market models in the world without major energy crisis so far. However, with the global trend in renewable initiative and concerns of sustainable development, NEM, like many other electricity markets worldwide is also facing a number of new challenges in this respect. In this paper, a general review will be given on some of the key new issues on the reliable and efficient operation of the Australian NEM. These include greenhouse issues, emission trading issues, market efficiency issues, market planning issues in the NEM and emergency control issues of the NEM power grid.