The design of optimal control architectures and the optimal selection of controlled variables represents a critical task for maximizing the economic profitability of operating plants. Traditionally, controlled variables are selected based on heuristics or past experiences. For cyber-physical systems (CPS), where physical and virtual components can be integrated in the same unit to evaluate the dynamic response of innovative power cycles past experiences may not be available. Trial-and-error methods can be time-consuming and costly. Besides, the selected controlled variables may not be optimal from the economic perspective. A systematic approach to the selection of controlled variable for cyber physical systems is presented here. The method is applied to a solid oxide fuel cell (SOFC)-gas turbine (GT) CPS at the National Energy Technology Laboratory (NETL) in Morgantown, WV. The main result of this work is the synthesis of optimal controlled variable sets for a cyber physical system exhibiting trade offs between economics as well as controllolability of variables.

In this paper, an economic model is presented for the evaluation of gas turbine total productive life cost and profitability. The model utilizes input from gas turbine engine performance, emissions and lifing models to provide quantitative information on the economic implications of an investigated system or investment option. In this study, the proposed model is used to conduct economic analysis on a turbojet engine, repurposed for alternative profitable use in electrical power generation. Results from the analysis are compared against competitor units to determine the models economic feasibility, benefits and limitations over competitors. Results obtained from the investigation reveal that the repurposed unit is economically feasible and favours profitability at minimal investment costs, with least burden on consumers. At a discount rate of 2.5%, investing in the repurposed engine model offers an investment base 13% lower, NPV 6% higher and an LCOE 24% higher in simple cycle than in combined cycle operation.

Cement industry consumes high energy levels with 4GJ per ton produced in average, 30% of it being electric and 70% thermal [1]. Cogeneration in this type of processes is not widespread; for only a few efforts have been made worldwide to implement methods that take advantage of waste heat stream, given that these contain 36% of the thermal input energy required to produce electricity [2]. Furthermore the implementation of a power generation alternative to feed limestone’s calcinations process is suggested. This paper is focused on the evaluation of thermal energy recovery strategies through the implementation of cogeneration systems, enabling an increase in efficiency and profitability producing electricity in before and after-processes of the cement production process. This will be achieved using methods of computer analysis implementing the ASPEN HYSIS™ software to simulate the behavior of the systems taking the rotary kiln operating conditions as main input or output variables. For the implementation of the system two important steps furnace operation will be taken. First one, related to combustion, is performed to produce the energy required in limestone’s processing entering this system, at this point the commercial gas turbine is used, coupled to a generator subsequently taking the power of oxygen-rich flow at the exhaust which is at a high temperature allowing a post-combustion using an afterburner. Finally, a second stage is evaluated at the downstream of the kiln, where a flow of charged waste gases counts with enough energy to perform an additional phase of power generation using an organic Rakine cycle (ORC).

The aim of this paper is to introduce readers to the UK’s Combined Heat and Power (CHP) industry, whilst identifying the key influences to the industry’s steady decline and the future diversification from an asset owner to a credible CHP or Utilities Operations and Maintenance (O&M) Service provider. There is a lack of research specific to the CHP and Utility O&M sectors that identify how to focus on attaining service excellence that adds real value to customers and stakeholders. The Service–Profit Chain (SPC) model developed by J. Heskett et al [1] is a recognised theory and business model that established the connection between profitability, customer loyalty, employee satisfaction and productivity. The application of the SPC model to the CHP and Utilities market sectors has identified a possible shortfall with the SPC model framework; in that it requires additional links to the resource support infrastructure and customer service cycle, whilst including the organization’s strategic service vision. Going beyond the application of the SPC model, this study will identify the additional management tools required to enhance and support the diversification process. An O&M SPC implementation model and a site specific Key Performance Indicator (KPI) model have been designed to complement the organization’s diversification. In addition to this, 10 golden rules have been developed in conjunction with a six tier approach to attain a meaningful O&M Service culture, which should ensure a sustainable future for an O&M Service provider.

Utilities need technology that is able to accurately estimate the performance and health of the power plant, and assess and optimize the plant’s current generation position for the purposes of generating accurate market pricing and operating cash-flows forecasts. The technology must be able to provide the utility with the required information to support robust power trading and risk management strategies, and ultimately increase the profitability of the business. This paper will address the utilization of integrated performance monitoring technologies to improve asset optimization at power generating facilities and report on the health of the power plant. Additionally, this paper will provide insight to some specific advanced monitoring technologies, how integration of the technologies can provide increased value for plant operations, and address the impact on key performance indicators that almost all utilities track, formally or informally. Case studies related to the technical information presented will also be presented.

The changes in the energy market dispatching and pricing, have increased the need to start fossil steam turbines faster to meet demand and save fuel. Exelon worked with a consultant to optimize the start up times of their steam turbines resulting in greatly reduced start up times, increased dispatching frequency, and reduced thermal stresses on the turbines. This optimized start up process was achieved by utilization of the Valve Open Start (VOS) and Accelerated Hot Start (AHS) process. VOS utilizes condenser vacuum aligned to the steam generator to produce superheated steam at much lower temperatures and pressures than usual. This steam is drawn through the turbine to warm the unit while the boiler increases in temperature and pressure. The AHS changes the startup sequence of operations by setting up the turbine in a manner that allows the turbine to roll at precisely the time that a perfect temperature match is obtained between the main steam temperature and first stage metal temperature. The use of these processes significantly increases profitability of the units and meets all OEM criteria for unit protection and results in a reduction in rotor thermal gradient, temperature mismatch, and thermally induced vibration.

The objective of this project was to perform an analysis of all of the major aspects of implementing electrical power generation using wind energy in a specific location. The project consisted of three main sections: location selection, turbine modeling and selection, and an economic analysis of the potential project as a whole. A limiting factor for a location was the availability of adequate wind speed data for analysis of the area’s potential. With these criteria, several locations were considered, and the Dominican Republic was selected because of high wind energy potential as well as high demand for electricity. There were several regions of the country with class 4 winds [1], and the average cost of electricity was very high at $0.15/kWh [2]. For the modeling and design of a wind turbine, a program named PROPID was used, which is a tool that takes design and wind parameters and returns simulated data such as power curves. The software was first validated for known configurations, to show the accuracy of the program, and it was then used to iteratively design new turbine configurations. The design of a popular 1300 kW commercial turbine, the Nordex N60, was scaled down to produce 1000 kW, and then gradually redesigned to increase the ratio of the power output to the surface area of the turbine, which was termed the design-factor, which would help to increase profitability of the turbine. The design-factor was increased from 320.9 for the original design to 466.2 for the final design. The final portion of the project was an economic analysis of a proposed wind farm. A software tool called HOMER was used, as well as Microsoft Excel’s internal rate of return function to calculate the long-term return of the project. Initial and annual costs were estimated based on available data for existing projects, and a 10 MW, 20 year life-span project was simulated using the newly designed turbine. Total levelized cost of energy was found to be between $0.042 and $0.057/kWh, depending on actual costs, and the overall annual return on investment in the project was calculated to be between a very conservatively determined value of 9.1% and a more general value of 12.9%. These values are limited in accuracy, and a more detailed study would be required prior to further project consideration, however they do indicate that this area is highly likely to have profitable wind energy resources.

Virtually, all industrial machinery requires periodic maintenance for dependable long-term operation. In fact, the very term “maintenance” is defined as keeping machines in the as-designed or as-purchased and manufactured condition. At issue is whether the equipment owner’s profitability objectives are best served by “maintaining only”, or by judiciously combining maintenance and upgrading tasks. Assuming the answer favors combining maintenance and upgrading, the question arises whether an intelligent and well thought-out combination of maintenance and upgrading should be entrusted only to the original equipment manufacturer (OEM), or if qualified non-OEMs should be considered also. The co-authors would like to offer their answer to the question. Experience shows that a highly qualified independent rebuild shop with demonstrated capabilities and experienced personnel can offer high-quality upgrades that improve both uptime and efficiency. Such a shop can do so consistent with current system performance requirements. With the considerable consolidations in the pump industry, the distinct possibility exists that the OEM is not able to offer the same engineering competence he previously had and that independent shops should be considered. This presentation deals with a case study and details where such upgrading was being planned, implemented, and verified to have had the desired results. It further explains the role played by competent pump rebuild shops (we chose to call them “CPRS”) in these important endeavors. Our work supports the premise that rebuilding a vintage process pump to original OEM specifications makes no sense, given current pump rebuilding technology and changes to the system performance that occur over time. We find compelling reasons to systematically upgrade the efficiency and potential run length of large centrifugal pumps. Of course, this upgrading must be pre-planned and then carried out during a future maintenance outage.

The desire to maintain power plant profitability, combined with current market fuel gas pricing is forcing power generation companies to constantly look for ways to keep their industrial gas turbine units operating at the highest possible efficiency. Gas Turbines Operation requires the compression of very large quantities of air that is mixed with fuel, ignited and directed into a turbine to produce torque for purposes ranging from power generation to mechanical drive of pumping systems to thrust for air craft propulsion. The compression of the air for this process typically uses 60% of the required base energy. Therefore management of the compression process efficiency is very important to maintain overall cycle efficiency. Since fouling of turbine compressors is almost unavoidable, even with modern air filter treatment, and over time results in lower efficiency and output, compressor cleaning is required to maintain gas turbine efficiency.

The global energy market continues to face significant change, evolving over time in several dimensions. One of them is a structural change, where it went into de-regulation and that has become a viable opportunity and reality; another is clean technology as new generating alternatives with greater efficiency and “environmental friendliness” has become available. Today, there is a keen interest in power plants using the latest gas turbine technology, which has higher firing temperatures, greater output, and improved efficiencies and remains environmental friendly. With evolving markets and variations in prices, the importance of reliability has increased greatly. As these technologies evolve and improve, it is important to recognize that the operational performance and profitability is expected to be consistently on the rise. Consequently, market conditions and expectations continue to place a significant emphasis on the achievable level of reliability and availability, which in turn provides the importance on having feedback from the plants within the framework of quality data resulting in building up benchmarking statistics. ORAP® (Operational Reliability Analysis Program) which is owned by Strategic Power System Inc.® (SPS) tracks reliability and availability performance on gas turbines from various MW size ranges, manufacturers, applications, and duty cycles. NERC is another data source with several years of data from varied fuels and power plant types. This paper presents the importance of having benchmarking data from an independent third party and the results of quality analysis by OEM experts. This focused approach develops the methodology of setting targets for MTBF, MTTR, FOR and failure rate not only at system level but also even down to component level for any operating power plant. The reliability growth potential is identified and reliability techniques are applied.

Engineers design plants with overall income and operating cost objectives in mind. Defining system requirements, component functions, and failure modes, they discern risks that drive design. Maintenance costs get considered as an afterthought. Misunderstanding significant equipment failure modes greatly changes profitability. Improving certainty of plant economic success requires reducing the risk of unknown failures. Unanticipated operating restrictions can hobble commercial production. Avoiding unanticipated problems sustains predictable costs and operations. Relational software can reduce economic operating risk during plant design to project and control operating risks and maintenance costs.