Reliability modeling and analysis for a novel design of modular converter system of wind turbines

Converters play a vital role in wind turbines. The concept of modularity is gaining in popularity in converter design for modern wind turbines in order to achieve high reliability as well as cost-effectiveness. In this study, we are concerned with a novel topology of modular converter invented by Hjort, Modular converter system with interchangeable converter modules. World Intellectual Property Organization, Pub. No. WO29027520 A2; 5 March 2009, in this architecture, the converter comprises a number of identical and interchangeable basic modules. Each module can operate in either AC/DC or DC/AC mode, depending on whether it functions on the generator or the grid side. Moreover, each module can be reconfigured from one side to the other, depending on the system\u27s operational requirements. This is a shining example of full-modular design. This paper aims to model and analyze the reliability of such a modular converter. A Markov modeling approach is applied to the system reliability analysis. In particular, six feasible converter system models based on Hjort\u27s architecture are investigated. Through numerical analyses and comparison, we provide insights and guidance for converter designers in their decision-making

Spare Parts Inventory Control Considering Stochastic Growth of an Installed Base

Installed base is a measure describing the number of units of a particular system actually in use. To maintain the performance of the installed units, spare parts inventory control is extremely important and becomes very challenging when the installed base changes over time. This problem is often encountered when a manufacturer starts to deliver a new product to customers and agrees to provide spare parts to replace failed units in the future. To cope with the resulting non-stationary stochastic maintenance demand, a spare parts control strategy needs to be carefully developed. The goal is to ensure that timely replacements can be provided to customers while minimizing the overall cost for spare parts inventory control. This paper provides a model for the aggregate maintenance demand generated by a product whose installed base grows according to a homogeneous Poisson process. Under a special case where the product’s failure time follows the exponential distribution, the closed form solutions for the mean and variance of the aggregate maintenance demand are obtained. Based on the model, a dynamic (Q, r) restocking policy is formulated and solved using a multi-resolution approach. Two numerical examples are provided to demonstrate the application of the proposed method in controlling spare parts inventory under a service level constraint. Simulation is utilized to explore the effectiveness of the multi-resolution approach

Reliability Growth Modeling for Inservice Electronic Systems Considering Latent Failure Modes

A latent failure mode is a type of failure that may not occur until the system has operated in the field for a certain period of time. Predicting latent failures is often difficult, but it has a great importance for reliability management in terms of system maintenance and warranty services. This paper proposes a stochastic model to predict the reliability growth for field or in-service electronic systems considering latent failures. The proposed model can be applied to electronics industries where extended in-house reliability testing cannot be implemented due to the tight design schedule. Based on the new method, the product management can proactively implement corrective actions against key failure modes using relevant engineering resources. A discussion between the effectiveness of corrective actions and the associated cost is also provided. Finally, field failure data collected from a fleet of automatic test equipment are used to demonstrate the applicability and performance of the model

Risk-averse Reliability Optimization in Electronic Product Design Considering Component and Non-component Failures

Reliability prediction assists manufacturers to eliminate product failures in the development stage and also allocate engineering resources to implement corrective actions after product shipment. This paper proposes a practical reliability prediction model for estimating failure rates of printed-circuit-boards during the development stage. Unlike traditional reliability prediction models focusing only on component failures, the new method further considers non-component failures due to design, software, manufacturing and process. Component failure rates are estimated based on either historical data or baseline failure rates adjusted by operating conditions. Triangular distributions are used to model non-component failure rates. Finally, an optimisation problem is formulated in order to minimise the upper bound of the failure rate under cost constraints. A genetic algorithm is used to search the optimal solution. The optimisation method is demonstrated by the design of a DC/analogue instrument board used in the automatic test equipment in semiconductor industry

Designing an Incentive Contract Menu for Sustaining the Electricity Market

This paper designs an incentive contract menu to achieve long-term stability for electricity prices in a day-ahead electricity market. A bi-level Stackelberg game model is proposed to search for the optimal incentive mechanism under a one-leader and multi-followers gaming framework. A multi-agent simulation platform was developed to investigate the effectiveness of the incentive mechanism using an independent system operator (ISO) and multiple power generating companies (GenCos). Further, a Q-learning approach was implemented to analyze and assess the response of GenCos to the incentive menu. Numerical examples are provided to demonstrate the effectiveness of the incentive contract

The quest for carbon-neutral industrial operations: renewable power purchase versus distributed generation

Integrating renewable energy into the manufacturing facility is the ultimate key to realising carbon-neutral operations. Although many firms have taken various initiatives to reduce the carbon footprint of their facilities, there are few quantitative studies focused on cost analysis and supply reliability of integrating intermittent wind and solar power. This paper aims to fill this gap by addressing the following question: shall we adopt power purchase agreement (PPA) or onsite renewable generation to realise the eco-economic benefits? We tackle this complex decision-making problem by considering two regulatory options: government carbon incentives and utility pricing policy. A stochastic programming model is formulated to search for the optimal mix of onsite and offsite renewable power supply. The model is tested extensively in different regions under various climatic conditions. Three findings are obtained. First, in a long term onsite generation and PPA can avoid the price volatility in the spot or wholesale electricity market. Second, at locations where the wind speed is below 6 m/s, PPA at $70/MWh is preferred over onsite wind generation. Third, compared to PPA and wind generation, solar generation is not economically competitive unless the capacity cost is down below$1.5 M/MW