Control aspects of the Schuchuli Village stand-alone photovoltaic power system

A photovoltaic power system in an Arizona Indian village was installed. The control subsystem of this photovoltaic power system was analyzed. The four major functions of the control subsystem are: (1) voltage regulation; (2) load management; (3) water pump control; and (4) system protection. The control subsystem functions flowcharts for the control subsystem operation, and a computer program that models the control subsystem are presented

The subjective effect of multiple co-channel frequency modulated television interference

As the geostationary orbit/spectrum becomes saturated, there is a need for the ability to reuse frequency assignments. Protection ratios (the ratio of wanted signal power to interfering signal power at the receiver) play a key role in determining efficient frequency reuse plans. A knowledge of the manner in which multiple sources of co-channel interference combine is vital in determining protection ratio requirements such that suitable margin may be allocated for multiple interfering signals. Results of tests examining the subjective assessment of multiple co-channel frequency modulated television signals interfering with another frequency modulated TV system are presented

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets

Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Methods: Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Results: Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). Conclusion: The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller

Modelling business and management systems using Fuzzy cognitive maps: A critical overview

A critical overview of modelling Business and Management (B&M) Systems using Fuzzy Cognitive Maps is presented. A limited but illustrative number of specific applications of Fuzzy Cognitive Maps in diverse B&M systems, such as e business, performance assessment, decision making, human resources management, planning and investment decision making processes is provided and briefly analyzed. The limited survey is given in a table with statics of using FCMs in B&M systems during the last 15 years. The limited survey shows that the applications of Fuzzy Cognitive Maps to today’s Business and Management studies has been steadily increased especially during the last 5-6 years. Interesting conclusions and future research directions are highlighted

Why Modeling Complex Dynamic Systems using Fuzzy Cognitive Maps?

The difficult problem of modeling Complex Dynamic Systems (CDS) is carefully reviewed. Main characteristics of CDS are considered and analyzed. Today’s mathematical models and approaches cannot provide satisfactory answers to the challenging problems of the society. The key problem of complex dynamic systems and control theory consists in the development of methods of qualitative analysis of the dynamics and behavior of such systems and in the construction of efficient control algorithms for their efficient operation. The purpose of control to bring the system to a point of its phase space which corresponds to maximal or minimal value of the chosen efficiency criterion is reviewed and analyzed. The reasons for using Fuzzy Cognitive Maps (FCMs) in modeling Complex dynamic Systems are provided. The basics of FCMs are briefly presented. An illustrative example is considered and interesting results are presented and discusse

Why Modeling Complex Dynamic Systems using Fuzzy Cognitive Maps?

The difficult problem of modeling Complex Dynamic Systems (CDS) is carefully reviewed. Main characteristics of CDS are considered and analyzed. Today’s mathematical models and approaches cannot provide satisfactory answers to the challenging problems of the society. The key problem of complex dynamic systems and control theory consists in the development of methods of qualitative analysis of the dynamics and behavior of such systems and in the construction of efficient control algorithms for their efficient operation. The purpose of control to bring the system to a point of its phase space which corresponds to maximal or minimal value of the chosen efficiency criterion is reviewed and analyzed. The reasons for using Fuzzy Cognitive Maps (FCMs) in modeling Complex dynamic Systems are provided. The basics of FCMs are briefly presented. An illustrative example is considered and interesting results are presented and discussed

Modelling business and management systems using Fuzzy cognitive maps: A critical overview

A critical overview of modelling Business and Management (B&M) Systems using Fuzzy Cognitive Maps is presented. A limited but illustrative number of specific applications of Fuzzy Cognitive Maps in diverse B&M systems, such as e business, performance assessment, decision making, human resources management, planning and investment decision making processes is provided and briefly analyzed. The limited survey is given in a table with statics of using FCMs in B&M systems during the last 15 years. The limited survey shows that the applications of Fuzzy Cognitive Maps to today’s Business and Management studies has been steadily increased especially during the last 5-6 years. Interesting conclusions and future research directions are highlighted

A Critical Overview of Data Mining for Business Applications

Everybody looks to a world that does not remain the same. Furthermore no one can deny that the world is changing, and changing very fast. Technology, education, science, environment, health, communicating habits, entertainment, eating habits, dress - there is hardly anything in life that is not changing. Some changes we like, while others create fear and anxiety around us. Everywhere there is a feeling of insecurity. What will happen to us tomorrow, or what will happen to our children, are questions we keep frequently asking. One thing, however, is clear. It is no more possible to live in the way we have been living so far. It seems that now the entire fabric of life will have to be changed. Life will have to be redesigned. The life of the individual, the social structure, the working conditions and governance all will have to be re-planned. Furthermore over the past 2-3 decades there has been a huge increase in the amount of data being stored in databases as well as the number of database applications in business and the scientific domain. This explosion in the amount of electronically stored data was accelerated by the success of the relational model for storing data and the development and maturing of data retrieval and manipulation technologies. While technology for storing the data developed fast to keep up with the demand, little stress was paid to developing software for analysing the data until recently when companies realized that hidden within these masses of data was a resource that was being ignored. The huge amounts of stored data contains knowledge on a good number of aspects of their business waiting to be harnessed and used for more effective business decision support. Database Management Systems (DMS) used to manage these data sets at present only allow the user to access information explicitly present in the databases i.e. the data. The data stored in the database is only a small part of the \u27iceberg of information\u27 available from it. Contained implicitly within this data is knowledge about a number of aspects of their business waiting to be harnessed and used for more effective business decision support. This extraction of knowledge from large data sets is called Data Mining or Knowledge Discovery in Databases and is defined as the non-trivial extraction of implicit, previously unknown and potentially useful information from data. Almost in parallel with the developments in the database field, machine learning research was maturing with the development of a number of sophisticated techniques based on different models of human learning. Learning by example, cased-based reasoning, learning by observation and neural networks are some of the most popular learning techniques that were being used to create the ultimate thinking machine

An Overview of Zero Energy Buildings with an Emphasis on Energy Savings

The indiscriminate exploitation of the planet\u27s energy sources has nowadays led to an uncontrolled form of climate change, with negative consequences for both humankind and the environment. In an effort to curb this situation, energy savings in both the building sector and other sectors of activity (industry, transport, etc.) is a primary objective and an indispensable component of any energy policy been planned today all around the world. As the building sector consumes 40% of the energy required at European level, the European Union (EU) has made considerable efforts to significantly reduce these consumption levels. In recent years, the European Union’s efforts have been made to improve the situation in energy policy and planning issues, focusing on energy saving as well as the use of renewable energy sources that have proven to have significant benefits for the environment, society and the economy. The European Council adopted a package and the European Parliament voted it and the 27 Heads of State and governments finally agreed to implement the 20-20-20 EU Energy targets: by 2020, reduce by 20% the emissions of greenhouse gases, increase by 20% the energy efficiency in the EU and to reach 20% of renewable energy sources (RES) in total energy consumption in the EU.It is characteristic that in the context of saving efforts in the building sector, provisions have been incorporated into the requirements of net Zero Energy Buildings (nZEB)both in the corresponding Community Directives. These provisions provide for the construction of all new buildings by 2021 at the latest with net zero consumption standards. In particular for public new buildings, the time horizon is even shorter. These targets difficult will be met.In this paper a review of definitions and methodologies of nZEB will be presented. It also examines the possibility of integrating two different systems of solar energy utilization into a residential building in the Patras area in order to achieve its energy self-sufficiency and hence its classification in the category of Zero Energy Consumption Buildings. More specifically, the integration of both photovoltaic and hybrid photovoltaic - thermal collectors was examined. The mathematical model for this proposed hybrid energy system is presented and analyzed. Examining these systems against other RES technologies was preferred because of their easier integration in building infrastructure but also the greater familiarity that users of the buildings usually have with both photovoltaic and solar thermal systems. The modeling of the operation of the two systems was done using the Matlab programming environment, taking into account the relevant literature and data available from manufacturers of related equipment. Different formats were developed to model the two technologies due to the different mathematical equations governing the operation of each of the proposed systems. Modeling took place for four representative months of the year (January, April, July and October) in the Western part of Greece. Obtained simulation results which have been very promising will be presented at the conference