Artificial Intelligence in Power Systems
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The document discusses applications of artificial intelligence techniques in power systems. It describes expert systems, artificial neural networks, fuzzy logic, and genetic algorithms as common AI techniques. These techniques can be used for fault detection and diagnosis, optimization of power delivery, planning and operation of generation, transmission, and distribution systems. As an example, the document outlines how expert systems, artificial neural networks, and fuzzy logic can be applied to monitor a transmission line and optimize its performance based on environmental conditions.
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Artificial Intelligence in Power Systems
- 1. BY K.MANOGNA 17251D5405 UNDER THE GUIDANCE OF: G.UJWALA ASSISTANT PROFESSOR
- 2. An electric power system is a network of electrical components used to supply, transmit and use electric power. Power systems engineering is a subdivision of electrical engineering that deals with the generation, transmission, distribution and utilization of electric power and the electrical devices connected to such systems like generators, motors and transformers . POWER SYSTEMS
- 3. • Commonly, artificial intelligence is known to be the intelligence exhibited by machines and software, for example, robots and computer programs. • The term is generally used to the project of developing systems equipped with the intellectual processes features and characteristics of humans, like the ability to think, reason, find the meaning, generalize, distinguish, learn from past experience or rectify their mistakes. •Artificial general intelligence (AGI) is the intelligence of a hypothetical machine or computer which can accomplish any intellectual assignment successfully which a human being can accomplish. ARTIFICIAL INTELLIGENCE
- 4. Power system analysis is more difficult using conventional methods they include: 1) Complex versatile and large amount of information which is used in calculation ,diagnosis and learning. 2) Increase in computational time period and accuracy due to extensive and vast system data handling. 3) Optimization of power delivered to the load according to the demand. 4) Probability of fault occurrence in a particular transmission bus calculation requires more environmental sensing data. NEED FOR AI IN POWER SYSTEMS
- 5. The artificial intelligence is the combination of the following four techniques. 1) Expert systems 2) Artificial neural networks 3) Fuzzy logics and 4) Genetic algorithm. ARTIFICIAL INTELLIGENCE TECHNIQUES
- 7. • The expert systems is the main technique used in the artificial intelligence in power systems. •Expert system is placed in series to the transmission line component . •It consists of environment sensors which senses the environment conditions . •They work under the computer program. •Their main operation is to act as a comparator which continuously senses the transmission line data with the standard ratings of the transmission line which is given as instructions to the software used in the expert systems. EXPERT SYSTEMS
- 8. HOW EXPERT SYSTEM USED IN POWER SYSTEMS •Since expert systems are basically computer programs, the process of writing codes for these programs is simpler than actually calculating and estimating the value of parameters used in generation, transmission and distribution. •Any modifications even after design can be easily done because they are computer programs. • Virtually, estimation of these values can be done and further research for increasing the efficiency of the process can be also performed
- 10. ARTIFICIAL NEURAL NETWORK •Artificial Neural Networks are biologically inspired systems which convert a set of inputs into a set of outputs by a network of neurons, where each neuron produces one output as a function of inputs. • A fundamental neuron can be considered as a processor which makes a simple non linear operation of its inputs producing a single output. •The understanding of the working of neurons and the pattern of their interconnection can be used to construct computers for solving real world problems of classification of patterns and pattern recognition. •They are classified by their architecture: number of layers and topology, connectivity pattern, feed forward or recurrent.
- 11. HOW ANN USED IN POWER SYSTEMS • As ANNs operate on biological instincts and perform biological evaluation of real world problems, the problems in generation, transmission and distribution of electricity can be fed to the ANNs so that a suitable solution can be obtained. •Given the constraints of a practical transmission and distribution system, the exact values of parameters can be determined. • For example, the value of inductance, capacitance and resistance in a transmission line can be numerically calculated by ANNs taking in various factors like environmental factors, unbalancing conditions, and other possible problems. • Also the values of resistance, capacitance and inductance of a transmission line can be given as inputs and a combined, normalized value of the parameters can be obtained. In this way skin effect and proximity effect can be reduced to a certain extent.
- 12. FUZZY LOGICS
- 13. FUZZY LOGICS • Fuzzy logic or Fuzzy systems are logical systems for standardization and formalization of approximate reasoning. • It is similar to human decision making with an ability to produce exact and accurate solutions from certain or even approximate information and data. • Fuzzy logic is the way like which human brain works, and we can use this technology in machines so that they can perform somewhat like humans. •Fuzzification provides superior expressive power, higher generality and an improved capability to model complex problems at low or moderate solution cost. •Fuzzy logic allows a particular level of ambiguity throughout an analysis. •Fuzzy logic provide the conversions from numerical to symbolic inputs, and back again for the outputs.
- 15. HOW FUZZY LOGICS USED IN POWER SYSTEMS • Fuzzy logic can be used for designing the physical components of power systems. •They can be used in anything from small circuits to large mainframes. •They can be used to increase the efficiency of the components used in power systems. • As most of the data used in power system analysis are approximate values and assumptions, fuzzy logic can be of great use to derive a stable, exact and ambiguity-free output.
- 16. GENETIC ALGORITM •Genetic algorithm is an optimization technique based on the study of natural selection and natural genetics. •Its basic principle is that the fittest individual of a population has the highest probability and possibility for survival. • Genetic algorithm gives a global technique based on biological metaphors. •The Genetic algorithm can be differentiated from other optimization methods by: (i) Genetic algorithm works on the coding of the variables set instead of the actual variables. (ii) Genetic algorithm looks for optimal points through a population of possible solution points, and not a single point.
- 17. HOW GENETIC ALGORITHM USED IN POWER SYSTEMS (i) Planning – Wind turbine positioning, reactive power optimisation, network feeder routing, and capacitor placement. (ii) Operation – Hydro-thermal plant coordination, maintenance scheduling, loss minimisation, load management, control of FACTS. (iii) Analysis – Harmonic distortion reduction, filter design, load frequency control, load flow.
- 18. APPLICATIONS OF AI Several problems in power systems cannot be solved by conventional techniques are based on several requirements which may not feasible all the time. In these situations, artificial intelligence techniques are the obvious and the only option. Areas of application of AI in power systems are: (i) Operation of power system like unit commitment, hydro- thermal coordination, economic dispatch, congestion management, maintenance scheduling, state estimation, load and power flow. (ii) Planning of power system like generation expansion planning, power system reliability, transmission expansion planning, reactive power planning. (iii) Control of power system like voltage control, stability control, power flow control, load frequency control. (iv) Control of power plants like fuel cell power plant control, thermal power plant control.
- 19. APPLICATIONS OF AI (Contd..) (v) Control of network like location, sizing and control of FACTS devices. (vi) Electricity markets like strategies for bidding, analysis of electricity markets. (vii) Automation of power system like restoration, management, fault diagnosis, network security. (viii) Applications of distribution system like planning and operation of distribution system, demand side response and demand side management, operation and control of smart grids, network reconfiguration. (ix) Applications of distributed generation like distributed generation planning, solar photovoltaic power plant control, wind turbine plant control and renewable energy resources. (x) Forecasting application like short term and long term load forecasting, electricity market forecasting, solar power forecasting, wind power forecasting.
- 20. EXAMPLE FOR AI APPLICATION IN POWER SYSTEM (TRANSMISSION LINE)
- 21. EXAMPLE FOR AI APPLICATION IN POWER SYSTEM (TRANSMISSION LINE) • Consider a practical transmission line. If any fault occurs in the transmission line, the fault detector detects the fault and feeds it to the fuzzy system. • Only three line currents are sufficient to implement this technique and the angular difference between fault and pre-fault current phasors are used as inputs to the fuzzy system. •The fuzzy system is used to obtain the crisp output of the fault type. Fuzzy systems can be generally used for fault diagnosis. •Artificial Neural Networks and Expert systems can be used to improve the performance of the line. • The environmental sensors sense the environmental and atmospheric conditions and give them as input to the expert systems. •The expert systems are computer programs written by knowledge engineers which provide the value of line parameters to be deployed as the output.
- 22. EXAMPLE FOR AI APPLICATION IN POWER SYSTEM (TRANSMISSION LINE) (Contd…) •The ANNs are trained to change the values of line parameters over the given ranges based on the environmental conditions •Training algorithm has to be given to ANN. •After training is over, neural network is tested and the performance of updated trained neural network is evaluated. • If performance is not upto the desired level, some variations can be done like varying number of hidden layers, varying number of neurons in each layer. •The processing speed is directly proportional to the number of neurons. •These networks take different neurons for different layers and different activation functions between input and hidden layer and hidden and output layer to obtain the desired output. • In this way the performance of the transmission line can be improved.
- 23. CONCLUSION The main feature of power system design and planning is reliability, which was conventionally evaluated using deterministic methods. Moreover, conventional techniques don’t fulfill the probabilistic essence of power systems. This leads to increase in operating and maintenance costs. Plenty of research is performed to utilize the current interest AI for power system applications. A lot of research is yet to be performed to perceive full advantages of this upcoming technology for improving the efficiency of electricity market investment, distributed control and monitoring, efficient system analysis, particularly power systems which use renewable energy resources for operation.