Hoay Beng Gooi

Sizing of Energy Storage for Microgrids

This paper presents a new method based on the cost-benefit analysis for optimal sizing of an energy storage system in a microgrid (MG). The unit commitment problem with spinning reserve for MG is considered in this method. Time series and feed-forward neural network techniques are used for forecasting the wind speed and solar radiations respectively and the forecasting errors are also considered in this paper. Two mathematical models have been built for both the islanded and grid-connected modes of MGs. The main problem is formulated as a mixed linear integer problem (MLIP), which is solved in AMPL (A Modeling Language for Mathematical Programming). The effectiveness of the approach is validated by case studies where the optimal system energy storage ratings for the islanded and grid-connected MGs are determined. Quantitative results show that the optimal size of BESS exists and differs for both the grid-connected and islanded MGs in this paper.

Optimal scheduling of spinning reserve

Effective control of spinning reserve can provide substantial cost reductions in large power systems. This paper suggests that this goal can he achieved by tightly integrating a probabilistic reserve assessment with the unit commitment (UC) function. This enables the reliability of individual units and the uncertainty of the load forecast to be considered for short-term scheduling. The generation can then be scheduled to meet a given risk index. It is further argued that the optimal value of this risk index should be selected on the basis of a tradeoff between the total schedule cost obtained from the UC solution and the expected cost of energy not served which can be derived from the probabilistic reserve assessment. Finally, the problem of over-commitment of reserve in Lagrangian relaxation based UC is reduced by means of a new unit decommitment technique incorporating a look-ahead feature.

Extended-Boost

The Z-source inverter has gained popularity as a single-stage buck-boost inverter topology among many researchers. However, its boosting capability could be limited, and therefore, it may not be suitable for some applications requiring very high boost demand of cascading other dc-dc boost converters. This could lose the efficiency and demand more sensing for controlling the added new stages. This paper is proposing a new family of extended-boost quasi Z -source inverter (ZSI) to fill the research gap left in the development of ZSI. These new topologies can be operated with same modulation methods that were developed for original ZSI. Also, they have the same number of active switches as original ZSI preserving the single-stage nature of ZSI. Proposed topologies are analyzed in the steady state and their performances are validated using simulated results obtained in MATLAB/Simulink. Furthermore, they are experimentally validated with results obtained from a prototype developed in the laboratory.

Z

The World Wide Web (WWW) has become a convenient may to access information on the net because the WWW browser integrates different network services into a common easily accessible user interface. These features coupled with low investment cost are especially suited for accessing information of the SCADA (supervisory control and data acquisition) system. This paper describes a unique Web-based application which is implemented based on the client/server architecture. The user can view the real-time data superimposed on one-line diagrams generated automatically using the VLSIs placement and routing techniques. In addition, the user can also control the operation of the substation at the server site. The choice of the Java language offers unique and powerful features such as zero client installation, on-demand access and platform independence to the design of the SCADA display system.

-Source Inverters

In this paper, a probabilistic methodology for estimating spinning reserve requirement in microgrids is proposed. The spinning reserve amount is determined by a tradeoff between reliability and economics. The unreliability of units and uncertainties caused by load and nondispatchable units are both considered. In order to reduce computation burden, various uncertainties are aggregated. A multistep method is proposed to efficiently consider the combinatorial characteristic of unit outage events. The computation efficiency of spinning reserve calculations can be greatly improved. The optimization is solved by mixed integer linear programming (MILP). Two case studies are carried out to illustrate the proposed method. Their results and discussions are also presented.

Web-based SCADA display systems (WSDS) for access via Internet

In market operations, distributed generators (DGs) and price-sensitive loads participate in a microgrid energy market implemented in JADE. Each DG and each price-sensitive load is represented by the respective agents which perform various functions such as scheduling, coordination and market clearing subject to system, DG and load constraints. Each agent is assigned to one of the several agent objectives which maximizes either DG or load surpluses or both. In simulated operation of a microgrid, hourly power reference signals and load control signals from JADE are passed to DG and load models developed in MATLAB/Simulink using MACSimJX. Simulated operation of DGs and loads are studied by performing simulations under different agent objectives. Results from simulation studies demonstrate the effectiveness of implementing multi-agent system (MAS) in the distributed management of microgrids.

Spinning Reserve Estimation in Microgrids

Day-ahead unit commitment (UC) solution methods seek to determine the status and output of all available generators. In a world with an increasing integration of renewable energy sources such as wind electric generators (WEG), the UC solution process must model and include WEGs too in the decision-making process. Power output of WEGs in a day-ahead decision-making process are usually modeled using a short-term probabilistic forecast. Inclusion of WEGs introduces uncertainty in the solution that may be quantified through an imbalance risk function. Thus a UC solution method should seek a solution to minimize cost and risk in schedule. Two strategies are proposed in this paper to minimize costs and handle risks introduced due to WEGs. These formulations are posed as fuzzy optimization models and are solved using the mixed integer linear programming (MILP) technique. The proposed strategies are tested on a 26- and a 100-generator systems with associated transmission networks that have three and six wind generators each. The results with two strategies of handling WEGs are discussed.

Multi agent system for distributed management of microgrids

A probabilistic method for a pool-based combined energy and reserve market, which considers both generators and interruptible loads (ILs), is proposed in this paper. We minimize generation production cost together with the cost associated with expected energy not supplied (EENS) due to outages of generating units and failures of ILs to supply the reserve when required. The proposed settlement scheme allocates equitably cost of reserve among generators and ILs. Given that the method takes into account reliability of individual generators and ILs, the proposed scheme provides incentives for all market participants to improve their performance. A number of case studies are carried out to illustrate the impact of participants characteristics on the reserve cost allocation

Fuzzy MILP Unit Commitment Incorporating Wind Generators

In the deregulated environment, information is the key to secure operation, profitability, customer retention, market advantage, and growth for the power industry. The rapid development of the Internet and distributed computing have opened the door for feasible and cost-effective solutions. This article describes and demonstrates a unique Internet-based application in a substation automation system that is implemented based on the existing system control and data acquisition (SCADA) system and very large-scale integration (VLSI) information technologies (IT). The user can view the real-time data superimposed on one-line diagrams generated automatically using VLSI placement and routing techniques. In addition, the user can also control the operation of the substation at the server site. The choice of Java technologies, such as Java Native Interface (JNI), Java Remote Method Invocation (RMI), and Enterprise Java Bean (EJB), offers unique and powerful features, such as zero client installation, on-demand access, platform independence, and transaction management for the design of the online SCADA display system.

A probabilistic reserve market incorporating interruptible load

Due to the inherent uncertainty involved in renewable energy forecasting, uncertainty quantification is a key input to maintain acceptable levels of reliability and profitability in power system operation. A proposal is formulated and evaluated here for the case of solar power generation, when only power and meteorological measurements are available, without sky-imaging and information about cloud passages. Our empirical investigation reveals that the distribution of forecast errors do not follow any of the common parametric densities. This therefore motivates the proposal of a nonparametric approach to generate very short-term predictive densities, i.e., for lead times between a few minutes to one hour ahead, with fast frequency updates. We rely on an Extreme Learning Machine (ELM) as a fast regression model, trained in varied ways to obtain both point and quantile forecasts of solar power generation. Four probabilistic methods are implemented as benchmarks. Rival approaches are evaluated based on a number of test cases for two solar power generation sites in different climatic regions, allowing us to show that our approach results in generation of skilful and reliable probabilistic forecasts in a computationally efficient manner.