Modern Optimization Algorithms and Applications in Solar Photovoltaic Engineering

This chapter is devoted to main tendencies of optimization in photovoltaic (PV) engineering showing the main trends in modern energy transition - the changes in the composition (structure) of primary energy supply, the gradual shift from a traditional (mainly based on fossil fuels) energy to a new stage based on renewable energy systems from history to current stage and to future. The concrete examples (case studies) of optimization PV systems in different concepts of using from power electronics (particularly maximum power point tracking optimization) to implementing geographic information system (GIS) are considered. The chapter shows the gradual shifting optimization from specific quite narrow areas to the new stages of optimization of the very complex energy systems (actually smart grids) based on photovoltaics and also other renewable energy sources and GIS.

Optimal Reactive Power Dispatch Incorporating TCSC-TCPS Devices Using Different Evolutionary Optimization Techniques

The chapter presents two effective evolutionary methods, namely, artificial bee colony optimization (ABC) and biogeography based optimization (BBO) for solving optimal reactive power dispatch (ORPD) problem using flexible AC transmission systems (FACTS) devices. The idea is to allocate two types of FACTS devices such as thyristor-controlled series capacitor (TCSC) and thyristor-controlled phase shifter (TCPS) in such a manner that the cost of operation is minimized. In this paper, IEEE 30-bus test system with multiple TCSC and TCPS devices is considered for investigations and the results clearly show that the proposed ABC and BBO methods are very competent in solving ORPD problem in comparison with other existing methods.

Improved Pseudo-Gradient Search Particle Swarm Optimization for Optimal Power Flow Problem

This paper proposes an improved pseudo-gradient search particle swarm optimization (IPG-PSO) for solving optimal power flow (OPF) with non-convex generator fuel cost functions. The objective of OPF problem is to minimize generator fuel cost considering valve point loading, voltage deviation and voltage stability index subject to power balance constraints and generator operating constraints, transformer tap setting constraints, shunt VAR compensator constraints, load bus voltage and line flow constraints. The proposed IPG-PSO method is an improved PSO by chaotic weight factor and guided by pseudo-gradient search for particle's movement in an appropriate direction. Test results on the IEEE 30-bus and 118-bus systems indicate that IPG-PSO method is superior to other methods in terms of lower generator fuel cost, smaller voltage deviation, and lower voltage stability index.

A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow

Optimal power flow with transient stability constraints (TSCOPF) becomes an effective tool of many problems in power systems since it simultaneously considers economy and dynamic stability of power system. TSC-OPF is a non-linear optimization problem which is not easy to deal directly because of its huge dimension. This paper presents a novel and efficient optimisation approach named the teaching learning based optimisation (TLBO) for solving the TSCOPF problem. The quality and usefulness of the proposed algorithm is demonstrated through its application to four standard test systems namely, IEEE 30-bus system, IEEE 118-bus system, WSCC 3-generator 9-bus system and New England 10-generator 39-bus system. To demonstrate the applicability and validity of the proposed method, the results obtained from the proposed algorithm are compared with those obtained from other algorithms available in the literature. The experimental results show that the proposed TLBO approach is comparatively capable of obtaining higher quality solution and faster computational time.

Application of Adaptive Tabu Search Algorithm in Hybrid Power Filter and Shunt Active Power Filters

A novel hybrid series active power filter to eliminate harmonics and compensate reactive power is presented and analyzed. The proposed active compensation technique is based on a hybrid series active filter using ATS algorithm in the conventional Sinusoidal Fryze voltage (SFV) control technique. This chapter discusses the comparative performances of conventional Sinusoidal Fryze voltage control strategy and ATS-optimized controllers. ATS algorithm has been used to obtain the optimum value of Kp and Ki. Analysis of the hybrid series active power filter system under non-linear load condition and its impact on the performance of the controllers is evaluated. MATLAB/Simulink results and Total harmonic distortion (THD) shows the practical viability of the controller for hybrid series active power filter to provide harmonic isolation of non-linear loads and to comply with IEEE 519 recommended harmonic standards. The ATS-optimized controller has been attempted for shunt active power filter too, and its performance has also been discussed in brief.

Engineering QoS and Energy Saving in the Delivery of ICT Services

ICT service-providers are to daily face the problem of delivering ICT services (data processing (Dp) and/or telecommunication (Tlc) services) assuring the best compromise between Quality of Service (QoS) and Energy Optimization. Indeed, any operation of saving energy involves waste in the QoS. This holds both for Dp and for Tlc services. This paper introduces models the providers may use to support their decisions in the delivery of ICT services. Dp systems totalize millions of servers all over the world that need to be electrically powered. Dp systems are also used in the government of Tlc systems, which also require Tlc-specific power, both for mobile networks and for wired networks. Research is thus expected to investigate into methods to reduce ICT power consumption. This paper investigates ICT power management strategies that look at compromises between energy saving and QoS. Various optimizing ICT power management policies are studied that optimize the ICT power consumption (minimum absorbed Watts), the ICT performance (minimum response-time), and the ICT performance-per-Watt.

Problems of Modeling and Optimization of Heat Supply Systems

This chapter presents new methods and software system SOSNA intended for the parameter optimization of heat supply systems. They make it possible to calculate large-scale systems which have a complex structure with any set of nodes, sections, and circuits. A new methodological approach to solving the problem of the parameter optimization of the heat supply systems is developed. The approach is based on the multi-level decomposition of the network model, which allows us to proceed from the initial problem to less complex sub-problems of a smaller dimension. New algorithms are developed to numerically solve the parameter optimization problems of heat supply systems: an effective algorithm based on the multi-loop optimization method, which allows us to consider hierarchical creation of the network model in the course of problem solving; a parallel high-speed algorithm based on the dynamic programming method. The new methods and algorithms were used in the software system SOSNA.

Assessment and Enhancement of the Energy Supply System Efficiency with Emphasis on the Cogeneration and Renewable as Main Directions for Fuel Saving

The paper presents methods for assessing economic, resource and environmental efficiency of energy supply systems and ways of its improvement, the main of which are the development of cogeneration and renewable energy sources (RES). The problem of allocating fuel and financial costs in the case of the combined production is solved. The methods allow determining specific indicators of supplied products which makes it possible to compare the efficiency of energy supply systems of different companies and countries, and to define their future target indicators. The technology of introducing RES-based power plants to the energy supply systems by means of using unstabilized RES-based power for direct fuel substitution at thermal power plants. The paper can be interesting to power engineering specialists, businessmen and economists, and also participants of the upcoming UN Climate Change Conference aimed at achieving a universal agreement on climate, which will be held in 2015 in Paris.

Fuzzy Random Regression-Based Modeling in Uncertain Environment

The parameter value determination is important to avoid the developed mathematical model is troublesome and may yield inappropriate results. However, estimating the weights of the parameter or objective functions in the mathematical model is sometimes not easy in real situations, especially when the values are unavailable or difficult to decide. Additionally, various uncertainties include in the statistical data makes common mathematical analysis is not competent to deal with. Hence, this paper presents the Fuzzy Random Regression approach to determine the coefficient whereby statistical data used contain uncertainties namely, fuzziness and randomness. The proposed methods are able to provide coefficient information in the model setting and consideration of uncertainties in the evaluation process. The assessment of coefficient value is given by Weight Absolute Percentage Error of Fuzzy Decision. It clarifies the results between fuzzy decision and non-fuzzy decision that shows the distance of different between both approaches. Finally, a real-life application of production planning models is provided to illustrate the applicability of the proposed algorithms to a practical case study.

Scope of Biogeography-Based Optimization for Economic Load Dispatch and Multi-Objective Unit Commitment Problem

Biogeography Based Optimization (BBO) algorithm is a population-based algorithm based on biogeography concept, which uses the idea of the migration strategy of animals or other spices for solving optimization problems. Biogeography Based Optimization algorithm has a simple procedure to find the optimal solution for the non-smooth and non-convex problems through the steps of migration and mutation. This research chapter presents the solution to Economic Load Dispatch Problem for IEEE 3, 4, 6 and 10-unit generating model using Biogeography Based Optimization algorithm. It also presents the mathematical formulation of scalar and multi-objective unit commitment problem, which is a further extension of economic load dispatch problem.