Reliability-cost trade-offs for electricity industry planning with high variable renewable energy penetrations in emerging economies: A case study of Indonesia�s Java-Bali grid

Electricity industries in emerging economies face particular challenges in delivering affordable, environmentally sustainable, and secure power given growing demand and limited financial resources. While supply reliability is often poor and emission reductions given lower priority, solar and wind are now amongst our cheapest supply options but highly variable. Our study seeks to demonstrate the potential value of trading-off reliability standards against higher renewables and lower industry costs in future generation planning. We use an open-source, evolutionary programming-based, capacity expansion planning tool, NEMO, to solve least cost generation mixes for Indonesia�s Java-Bali grid in 2030. We explicitly test the cost and emission impacts of reliability targets of 0.005%�5% unserved energy (USE), modelled as both a hard optimization constraint and a penalty price on USE in the cost function. Our results highlight that lower reliability targets can increase solar and wind penetrations, reducing CO2 emissions while reducing industry costs. Both methods of incorporating reliability delivered similar outcomes but pricing USE had some advantages for optimization over hard constraint setting. While the impacts of lower reliability on consumers requires careful consideration, our study highlights the potential cost and emission implications of arguably unrealistic reliability targets in generation planning for emerging economies

Constructing a reproducible testing environment for distributed Java applications.

The emergence of the global Internet, wireless data communications, and the availability of powerful computers is enabling a new generation of distributed and concurrent systems. However, the inherent complexity of such systems introduces many new challenges in system testing and maintenance. One of the major problems in testing such systems is that executions with internal non-deterministic choices make the testing procedure non-repeatable. A natural solution is to artificially force the execution of a program to take desired paths so that a test can be reproduced. However, with geographically distributed processes and heterogeneous platform architectures, distributed systems have imposed new challenges in developing effective techniques for reproducible testing. The goal of this research is to build an environment to automate testing for distributed and concurrent Java applications. We will focus on controlling the order of occurrences of input and remote call events according to a user-specified test scenario, which is composed of input data, a constraint expressed as a partial order over the input and remote call events, and expected output. The testing environment is by itself distributed and does not require source code intrusion into the application under test. With minor changes, the testing components can also be reused in CORBA-based applications implemented in Java.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .W35. Source: Masters Abstracts International, Volume: 42-05, page: 1769. Adviser: Jessica Chen. Thesis (M.Sc.)--University of Windsor (Canada), 2003

SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry

In this paper, we aim at the automated unit coverage-based testing for embedded software. To achieve the goal, by analyzing the industrial requirements and our previous work on automated unit testing tool CAUT, we rebuild a new tool, SmartUnit, to solve the engineering requirements that take place in our partner companies. SmartUnit is a dynamic symbolic execution implementation, which supports statement, branch, boundary value and MC/DC coverage. SmartUnit has been used to test more than one million lines of code in real projects. For confidentiality motives, we select three in-house real projects for the empirical evaluations. We also carry out our evaluations on two open source database projects, SQLite and PostgreSQL, to test the scalability of our tool since the scale of the embedded software project is mostly not large, 5K-50K lines of code on average. From our experimental results, in general, more than 90% of functions in commercial embedded software achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in SQLite achieve 100% MC/DC coverage, and more than 60% of functions in PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the runtime exceptions at the unit testing level. We also have reported exceptions like array index out of bounds and divided-by-zero in SQLite. Furthermore, we analyze the reasons of low coverage in automated unit testing in our setting and give a survey on the situation of manual unit testing with respect to automated unit testing in industry.Comment: In Proceedings of 40th International Conference on Software Engineering: Software Engineering in Practice Track, Gothenburg, Sweden, May 27-June 3, 2018 (ICSE-SEIP '18), 10 page

Synthetic Modeling of Power Grids Based on Statistical Analysis

The development of new concepts and methods for improving the efficiency of power networks needs performance evaluation with realistic grid topology. However, much of the realistic grid data needed by researchers cannot be shared publicly due to the security and privacy challenges. With this in mind, power researchers studied statistical properties of power grids and introduced synthetic power grid topology as appropriate methodology to provide enough realistic power grid case studies. If the synthetic networks are truly representative and if the concepts or methods test well in this environment they would test well on any instance of such a network as the IEEE model systems or other existing grid models. In the past, power researchers proposed a synthetic grid model, called RT-nested-smallworld, based on the findings from a comprehensive study of the topology properties of a number of realistic grids. This model can be used to produce a sufficiently large number of power grid test cases with scalable network size featuring the same kind of small-world topology and electrical characteristics found in realistic grids. However, in the proposed RT-nested-smallworld model the approaches to address some electrical and topological settings such as (1) bus types assignment, (2) generation and load settings, and (3) transmission line capacity assignments, are not sufficient enough to apply to realistic simulations. In fact, such drawbacks may possibly cause deviation in the grid settings therefore give misleading results in the following evaluation and analysis. To address this challenges, the first part of this thesis proposes a statistical methodology to solve the bus type assignment problem. This method includes a novel measure, called the Bus Type Entropy, the derivation of scaling property, and the optimized search algorithm. The second part of this work includes a comprehensive study on generation/Load settings based on both topology metrics and electrical characteristics. In this section a set of approaches has been developed to generate a statistically correct random set of generation capacities and assign them to the generation buses in a grid. Then we determine the generation dispatch of each generation unit according to its capacity and the dispatch ratio statistics, which we collected and derived from a number of realistic grid test cases. The proposed approaches is readily applied to determining the load settings in a synthetic grid model and to studying the statistics of the flow distribution and to estimating the transmission constraint settings. Considering the results from the first two sections, the third part of this thesis will expand earlier works on the RT-nested-smallworld model and develop a new methodology to appropriately characterize the line capacity assignment and improve the synthetic power grid modeling

An empirical investigation into branch coverage for C programs using CUTE and AUSTIN

Automated test data generation has remained a topic of considerable interest for several decades because it lies at the heart of attempts to automate the process of Software Testing. This paper reports the results of an empirical study using the dynamic symbolic-execution tool. CUTE, and a search based tool, AUSTIN on five non-trivial open source applications. The aim is to provide practitioners with an assessment of what can be achieved by existing techniques with little or no specialist knowledge and to provide researchers with baseline data against which to measure subsequent work. To achieve this, each tool is applied 'as is', with neither additional tuning nor supporting harnesses and with no adjustments applied to the subject programs under test. The mere fact that these tools can be applied 'out of the box' in this manner reflects the growing maturity of Automated test data generation. However, as might be expected, the study reveals opportunities for improvement and suggests ways to hybridize these two approaches that have hitherto been developed entirely independently. (C) 2010 Elsevier Inc. All rights reserved