Optimizing district heating operations: Network modeling and its implications on system efficiency and operation

Automated guided vehicles (AGVs) have long been identified as a potential driver to improve system efficiency and lower labour costs in material handling systems. Accordingly, the reliability and availability of AGV systems is crucial to assure the stability and efficiency of these systems. However, the reliability issues and maintenance strategies of AGVs have not previously been studied sufficiently. This is even more marked in the case of multi-AGV systems that consist of fleets of AGVs. To fill this knowledge gap, research is conducted considering a multi-AGV system, consisting of three AGVs, in order to develop a scientific methodology for optimising the layout design, operation and maintenance of a multi-AGV system. Once an AGV is failed, it will be towed to the maintenance site for repair by a recycle vehicle to prevent deadlock and conflict. The efficiency of the recycling process of failed AGVs in a multi-AGV system, with respect to the change of location of the maintenance site, is analysed by the approach of coloured Petri nets (CPNs). A CPN model simulating the corrective and periodic preventive maintenance processes of failed AGVs is also developed in order to investigate the impact of different AGV maintenance strategies on the operation efficiency of the multi-AGV system. The simulation results obtained clearly show that the location of maintenance sites and maintenance strategies do have significant influence on the performance of a multi-AGV system, where corrective maintenance is an effective measure to maintain the long-term reliability and stability of the system.

One of the factors of internal disturbances and obstacles in the operation of the system of synchronization of coherent demodulators of telecommunication control systems and remote learning, which directly affect the efficiency of the entire system, are transient processes caused by the system's reaction to the transition from one stationary state to another stationary state. At the current stage of research devoted to the issue of minimizing the influence of the transient process on the operation of the phase synchronization system, increasing the speed and reducing the transient component of the phase error, which is generated by transient processes, was solved by the synthesis of an open connection under the condition of minimizing the phase error in the stable and transient modes of operation of the synchronization system. The solution of the specified task was solved by the method of synthesis of an open connection, the link of which had a permanent structure. As an improvement of the methodology for building a system of phase synchronization of coherent demodulators for telecommunication control and distance learning systems, a mathematical model and a method based on it are proposed in the work, which allows for the synthesis of the open link of the combined synchronization system with a variable structure. Thanks to this, further minimization of the influence of transient processes on the efficiency of the synchronization system of the coherent demodulator is ensured. The scheme of open communication with a variable structure proposed in the paper allows to minimize the influence of the transient process on the efficiency of the synchronization system by influencing the time of the transient process. The assessment carried out in the work of the possibility of an open connection link with a variable structure in terms of the influence on the time of the transient process in the system showed that by logically switching to an open connection branch with the appropriate values of the time operator, it is possible to achieve up to 6 or more times the reduction of the time of the transient process in compared to the transient process in a system with a stable scheme of an open communication link. This ensures an increase in the efficiency of receiving the input signal by the coherent demodulator and affects the quality of data transmission in telecommunication control and distance learning systems.

In recent years, with the development of battery energy storage technology and the support of policy, the construction scale of user-side battery energy storage system is increasing rapidly, and its operation performance has become more and more valued. In-depth quantitative analysis and evaluation is of great significance to provide reliable guarantee for high efficiency, safety and reliability operation of energy storage system. Based on the principles of scientificity, comprehensiveness and operability, the operation evaluation indexes are proposed including charge-discharge performance, energy efficiency, safety, reliability and economic performance. The operation performance of an example battery energy storage system for peak-load shifting is quantitatively analyzed and evaluated, based on the operation data and field test data. And the optimization suggestions are given for the problems existing in the operation of the system. The results show that the proposed operation evaluation indexes and methods can realize the quantitative evaluation of user-side battery energy storage systems on the charge-discharge performance, energy efficiency, safety, reliability and economic performance, which are helpful for the operation and maintenance of user-side battery energy storage systems.

Accurate short-term wind power forecasting has a significant impact to economic dispatch, which ensures the efficiency and smooth operation of power system. In this paper, a hybrid wind power forecasting method based on a typical algorithm of feedforward neural network, convolutional neural network (CNN) and a time circulation neural network, and long short-term memory network (LSTM) models is proposed. It aims to improve the accuracy of ultra-short-term wind power forecasting.

SCADA system has come a long way over the past three decades and now the same are not an isolated system serving only the system operators for operational safety. Presently, the SCADA system needs to support a wide variety of user requirements starting from system operators to different market participants, regulators, data analysts, and requirement for interconnection between SCADA and IT system is felt. Further, working with legacy systems can present a number of problems that ranges from higher maintenance cost, sluggish performance, non-availability of support service, availability of modern facilities in State of the art SCADA systems, interconnection facility with heterogeneous systems and operational efficiency of the new technology. With rapid expansion of the power system in India and evolution of markets through establishment of power exchanges, system operation has become more and more complex with interaction with huge number of market participants. Advanced visualization is of utmost importance to the system operators to ensure reliability of the system. Further, the requirement of interconnection of IT system with SCADA was felt to support the various MIS and data analysis requirement. With a view to use the present technology for better system efficiency and to support the present day need of the system operators and the customers, it was decided that the legacy SCADA is upgraded at all the State, Regional and National Control Centre in India.

Many legacy systems are still essential. They run efficiently and accurately in legacy hardware and software environments. Therefore, it is necessary to migrate legacy hardware and software to modern platforms. One of the directions of migration is to service-oriented architectures. In this case, side effects are possible. Therefore, it is necessary to use the software system model. This model is used to assess the migration process of legacy software systems. An approach for building network models from the ground up is proposed in this research. Time-dependent Petri nets are used to explain the traces of events in the simulated network. A user may create a network workload model that can be utilized for network planning purposes using this technique. A method must be established to determine whether or not the created model is suitable. An example is used to determine the suitability of the Markov model for the behavior of a system with discrete states in terms of precision. An example is used to build a model for the operation of a basic software system. Providing the executable network model of the migrating system to the service identification approach input is preferred.

One of the most frequent issues in multiple robot implementation is task allocation with the lowest path cost. Our study addresses the multi‐robot task allocation challenge with path costs, the lowest computing time, and task distribution. Furthermore, it is usual for a robot's processing capabilities to be restricted to operate in various target environments. As a consequence, adequate processing power consumption would demonstrate the system's efficiency. Task allocation and path planning issues must be addressed regularly to ensure multi‐robot system operation. Task allocation and path planning issues must be addressed regularly to ensure multi‐robot system operation. The above‐mentioned serious challenge gets more complicated when system factors such as robots and tasks multiply. As previously stated, this article solves the issue using a fuzzy‐based optimum path and reverse auction‐based methods. The detailed simulation results indicate that the suggested methods can solve task allocation with the lowest path cost. A comparative study is conducted between the suggested algorithm and two existing commonly used techniques, the auction‐based and the Hungarian algorithms. Finally, the suggested method was run in real‐time on a TurtleBot2 robot. The findings show the suggested algorithm's efficiency and simplicity of implementation.

The article describes the Data Envelopment Analysis (DEA) method and the main features of its application. The main problems of heat and power systems are described, which are addressed by the DEA method of efficiency assessment presented in the article. The approbation of this method is presented at the objects of the centralized municipal heat supply system of the fuel and energy complex: boiler houses and heat and power plants. 9 objects were analyzed according to four input indicators: available heat capacity, installed heat capacity, heat consumption for own needs, fuel consumption. Also, the efficiency of the system was evaluated according to two output indicators: the release of thermal energy to the grid and the mass of the emission. As a result of the analysis and calculations made, it was revealed that 5 objects have the maximum possible efficiency indicator equal to 1, that is, they function as efficiently as possible. 4 objects of the centralized municipal heat supply system have an efficiency indicator less than 1. Accordingly, improvements are required for the operation of the above Decision-Making Units (DMU)s. These objects have deviations in terms of the inputs and outputs of the actual data and those obtained using the DEA method. Based on the calculations obtained for these 4 objects, the article provides recommendations for changing the quantitative values of their input and output indicators. For example, for object number 2, it is recommended to reduce the installed heat capacity in the grid by 72.57%, without changing the available heat capacity and fuel consumption. Reduce the heat consumption for your own needs by 69.383%. In addition, it is recommended to increase the supply of thermal energy to the grid by 6,034%, and reduce the mass of emission by 11.5%. Specific measures have also been developed to modernize the studied objects in order to achieve the recommended indicators of inputs and outputs. The research results presented in the article are of scientific and practical interest and can be used to improve the efficiency of heat and power systems facilities

Modelling pathogen log10 reduction values achieved by activated sludge treatment using naïve and semi naïve Bayes network models

Side-by-side comparison of horizontal subsurface flow and free water surface flow constructed wetlands and artificial neural network (ANN) modelling approach

North China Grid (NCG) has been expanding rapidly in the recent years, along with which new issues emerge in system operations. There is an urgent need for NCG to construct and maintain the entire NCG transmission network model according to time points precisely and reliably to deal with those issues. However it becomes difficult to achieve this goal with the conventional centralized modeling method. Fortunately CIM standard has grown mature enough to afford a chance for developing a distributed method of modeling. NCG collaborates with technology vendors to design a solution based on the CIM standard. The goal is achieved by developing and deploying a cooperative and extensible model management system. With this new system modeling activities are performed cooperatively between the regional and local modeling authorities and as a result the precise and the quality of the NCG regional model is enhanced.

The successful application of the unified power flow controller (UPFC) provides a new control method for the secure and economic operation of power system. In order to make the full use of UPFC and improve the economic efficiency and static security of a power system, a preventive security-constrained power flow optimization method considering UPFC control modes is proposed in this paper. Firstly, an iterative method considering UPFC control modes is deduced for power flow calculation. Taking into account the influence of different UPFC control modes on the distribution of power flow after N-1 contingency, the optimization model is then constructed by setting a minimal system operation cost and a maximum static security margin as the objective. Based on this model, the particle swarm optimization (PSO) algorithm is utilized to optimize power system operating parameters and UPFC control modes simultaneously. Finally, a standard IEEE 30-bus system is utilized to demonstrate that the proposed method fully exploits the potential of static control of UPFC and significantly increases the economic efficiency and static security of the power system.

The work is dedicated to the investigation and analysis of the operation of the electromechanical system of an autonomous photovoltaic pumping station. Photovoltaic pumping stations are essential components of sustainable development, enabling efficient utilization of solar energy for independent water pumping. The study provides a detailed analysis of the structure and operation principles of the photovoltaic pumping station. Key components of the system, such as solar panels, electronic controllers, electromechanical pumps, and energy storage, were studied. Various methods for maximizing energy output from solar panels and optimizing the efficiency of pumping systems were examined. The research results revealed that the effective functioning of the photovoltaic pumping station depends on the precise balance of electromechanical components, optimal utilization of solar energy, and efficient management of electronic systems. Recommendations were put forth for improving the system's efficiency and reliability. Within the study, it was established that a crucial factor in the successful function of the photovoltaic pumping station is the selection of the optimal type of solar panels and their positioning to ensure maximum solar energy collection. The issue of storing excess energy to maintain system stability during periods of limited solar irradiation was also addressed. Moreover, the study included modeling and experimental research of various operational modes of the pumping station, including load variation and solar activity fluctuations. This provided crucial data regarding the dynamics and compliance of system operation with planned parameters. An important aspect of the research was evaluating the efficiency and economic viability of the photovoltaic pumping station in comparison with traditional energy sources for water supply. It was found that in some cases, the use of photovoltaic energy could be a more economically advantageous and environmentally cleaner solution. Overall, the results of this scientific work hold significant practical value for sustainable energy development and the utilization of renewable energy sources. The investigation of the operation of the electromechanical system of an autonomous photovoltaic pumping station contributes to a deeper understanding of the technological, economic, and environmental aspects of such systems. In conclusion, this research provides a deeper insight into the functioning principles of autonomous photovoltaic pumping stations and can serve as a foundation for further studies in the field of renewable energy utilization.

A thorough performance analysis of a heat pump air conditioning system for both heating and cooling applications is presented in this research. The purpose of the study is to assess the system's overall performance, energy usage, and efficiency under various operating circumstances. The study makes use of a variety of experimental measurements. An outline of the heat pump air conditioning system's parts and operation is given at the start of the analysis. Important factors including compressor power usage, ambient temperature, refrigerant flow rate, and indoor/outdoor temperature differentials are all monitored during the experimental setting. These measurements, which take into account both heating and cooling modes, are gathered under varied working conditions. For HVAC engineers, researchers, and policymakers, the performance analysis of the heat pump air conditioning system provided in this paper is an invaluable resource. The insights gained from this study contribute to the on-going efforts to improve the design and operation of heat pump systems for heating and cooling applications, fostering sustainability and energy conservation in the built environment.

Security and economy are long standing underpinnings for power system operation. The evolution from regulated utility operation to competitive markets operation led to more formalized treatment of economy and security concerns through the deployment of market clearing applications that are based mathematical programming methods. Among the most common market clearing applications are security-constrained unit commitment (SCUC) for day-ahead scheduling, and security-constrained economic dispatch (SCED) for real-time dispatch. Compared with previous generations of experience and/or heuristic based approaches, the use of formal optimization technology allows for greater transparency and consistency in the scheduling and dispatch processes. By extension, the market clearing application engines can be adapted to after-the-fact studies for assessing past performance. Such an approach is used by PJM in its successful implementation of the Perfect Dispatch (PD) functions. With appropriate configuration of the optimization model and assembly of historical data that collectively simulate perfect 20-20 hindsight, the PD application calculates an idealize reference dispatch. By comparing actual dispatch against the idealized reference, one can develop efficiency metrics for market system operation. The development of Perfect Dispatch has been an important milestone, by an RTO as market operator, to assess market efficiency.