Дисертації з теми "RESTRUCTURED POWER SYSTEMS"

The theme of this thesis is the supply of capacity during peak demand in restructured power systems. There are a number of reasons why there is uncertainty about whether an enegyonly electricity market (where generators are only paid for the energy produced) is able to ensure uninterrupted supply during peak load conditions.

Much of the public debate in Europe has been about the present surplus generation capacity. However, in a truly competitive environment, it is hard to believe that seldom used capacity will be kept operational. This is illustrated by developments in Sweden. For this reason, the large surplus of generation capacity in the European Union may vanish much faster than generally assumed. In the USA, much of the debate has been about California. During the last three summers, California has occasionally experienced involuntary load shedding and prices have been very high during these periods. To some extent, the Californian situation illustrates the relevance of the subject of this thesis: in a deregulated system generators may not be willing to invest in peaking capacity that is only needed occasionally, even though prices are very high during these periods.

A good solution to the problem of providing peaking power is pivotal to the success of power market restructuring. Solutions that fail to create the right incentives will result in unacceptable load shedding and can endanger the whole restructuring process. On the other hand, solutions that pay too much for investments in peaking power will lead to generation capacity surpluses and thus represent a societal loss.

Why is peaking capacity a problematic issue in energy-only markets?

Traditionally, probabilistic methods are applied to calculate the required generation capacity to obtain a desired level of reliability. In a centrally planned system, this level of generation capacity is developed in a least-cost manner. A single utility or central authorities can thus control the level of reliability directly. This is not possible in a market-based system, if suppliers are only paid for the energy produced.

Under the assumption of certainty and continually varying prices, generators fully recover their variable and investment costs under ideal market conditions. When uncertainty is taken into account, generators will cover their expected costs. However, revenues will be extremely volatile, especially for peaking generators. Combined with a risk-averse attitude, it is unlikely that investments will be sufficient to maintain the traditional level of reliability in an energyonly market. Consequently, one would expect reserve margins to decline in such markets. This effect is very clear in Sweden that deregulated in 1996, and less explicit in a number of other cases like Norway, California and Alberta.

Pricing and Consumer Preferences

The theory of electricity pricing was originally developed for vertically integrated utilities, but elements from this theory are also valuable in a restructured context. Many authors have agreed on the presence of a capacity element in the optimal price during peak-load conditions, while price should equal marginal cost during low-load conditions. An important assumption is that prices have to be stable. More recently, spot pricing of electricity has been advocated. A number of papers have been written about how to efficiently include security considerations in the spot price.

Because the availability of capacity cannot be directly controlled in an energy-only spot market, the probability of occasional capacity shortages increases. It is important to be prepared for this situation. The core of the problem is that demand is de facto inelastic in the short-term because of traditional tariff systems. It is shown that considerable economic gains are obtained when demand elasticity can be utilized, even if only minor shares of demand are elastic in the short-term. Better utilization of demand elasticity was also profitable in traditional systems, but after restructuring the gain is much larger: the alternative is not expensive generation but random rationing, which is unacceptable in modern society.

It is possible to go one step further. Consumers have different preferences for the use of energy and reliability. Some consumers have a low tolerance about being disconnected, while others are more willing to accept this. This will be reflected by their willingness to pay for reliability. A better solution would emerge if consumers could buy electricity and reliability more or less as separate commodities, based on their preferences.

In the context of pricing it should be pointed out that ”profile-based settlement” that allows small consumers to freely choose their supplier without hourly metering is detrimental with respect to the correct pricing of capacity. It should only be used in the initial phases of opening a market.

Improved utilization of system resources

Even in the short-term, demand and the availability of generation and transmission resources are uncertain. Therefore, it is necessary to have reserves available in a power system. When capacity becomes scarce, it is difficult to satisfy the reserve requirements. If these requirements are strict, the only possibility is to resort to what can be called ”preventive loadshedding” to satisfy the reserve requirements. This is obviously an expensive solution, but there are no obvious ways of balancing the (societal) cost of preventive load shedding against reduced system security. In this thesis, a model is developed for unit commitment and dispatch with a one-hour time horizon, with the objective of minimizing the sum of the operation and disruption costs, including the expected cost of system collapse. The model is run for the IEEE Reliability Test System. It is shown that under conditions where there is not enough capacity available to satisfy the reserve requirements, large cost savings can be obtained by optimizing the sum of the operation and disruption costs instead of using preventive load-shedding. In the model, it is also possible to directly target reliability indexes like the Loss of Load Probability or Expected Energy not Served. It is shown that increased reliability (in terms of the values of the indexes) can be obtained at a lower cost by targeting the indexes directly instead of resorting to reserve requirements. This is especially the case if flexible load-shedding routines are developed, making it possible to disconnect and reconnect the optimal amounts of load efficiently.

The use of alternatives to fixed reserve requirements as a means to maintain system security does not solve the problem about how to ensure the availability of peaking capacity. However, in a situation with occasional capacity shortages, it gives the System Operator a tool to find the optimal balance between preventive load shedding and system security, which can result in significantly lower disruption costs in such cases. More research and development in this area is necessary to develop methods and tools that are suitable for large power systems.

Ancillary Services

Investment in peaking capacity is insufficient in restructured systems because expected revenues are too low or too uncertain. If generator revenues are increased, the situation improves. One way to obtain this is to create markets for ancillary services. In the thesis, a model is developed for a central-dispatch type of pool. In this model, markets for energy and three types of ancillary services are cleared simultaneously for 24 hours ahead. Market prices are such that volumes and prices are consistent with the market participants. self-dispatch decisions . i.e. given these prices, market participants would have chosen the same production of energy and ancillary services as the outcome of the optimization program. With this model, it is shown that markets for ancillary services increase generator revenues, but this effect is partly offset by lower energy prices. This shows that markets for ancillary services can contribute to improving the situation, but given the remaining uncertainty, this is hardly enough to solve the problem.

Capacity Subscription

Because consumers have preferences for two goods: electricity and reliability, they should ideally have the choice of purchasing the preferred amount of each of these. Traditionally this is not possible . reliability is a public good, produced or obtained by a central authority on behalf of all consumers. Technological progress is presently changing this. Capacity subscription is a method that allows consumers to choose their individual level of reliability, at the same time creating a true market for capacity. It is based on the concept of selfrationing. Consumers anticipate (for example on a seasonal basis) their need for capacity at the instant of system-wide peak demand. Based on this anticipation, they procure their desired level of capacity in a market, where generators offer their available capacity. Demand is limited to subscribed capacity by a fuse-like device that is activated when total demand exceeds total available generation. In this way, the capacity payment only influences the market when demand is close to installed capacity, and does not distort the energy price in other periods. Demand is not limited when there is ample capacity. Demand will never exceed supply, because it can be limited in an acceptable way when this situation occurs. Moreover, both consumers and suppliers can adapt to situations with scarce or ample capacity, and the price of capacity will reflect this situation. There is one problem with the method: as consumers do not reach their subscribed capacity simultaneously, there will be a capacity surplus at the instant the fuse-devices are activated. Two methods to solve this problem are analysed, and it is shown that the problem can be solved optimally by giving consumers who prefer this the opportunity to buy power in excess of their subscription on the spot market.

Policy evaluation

Six alternative policies to assess the peaking power problem are analysed based on the following criteria:

- Static efficiency: the welfare-optimal match of consumption and supply

- Dynamic efficiency: the ability to create incentives for innovation

- Invisibility: with invisible strategies, each market actor pursues his or her own objectives without worrying about anyone else.s

- Robustness: a robust policy is less sensitive to deviations from assumptions

- Timeliness: the ability of a policy to be employed at the right time

- Stakeholder equity: the degree to which all the involved parties are treated equitable

- Corrigibility: the extent to which a policy can be corrected once it is employed

- Acceptability: the degree to which the policy is acceptable to all parties

- Simplicity: ceteris paribus simple strategies are preferable over more complicated strategies

- Cost: the cost of implementing the policy

- System security: the policy.s ability to obtain an acceptable level of system security

The policies are, in short (an example is given in parentheses):

- Capacity obligation: suppliers are obliged to keep sufficient capacity (PJM)

- Fixed capacity payment: a fixed payment is offered for available capacity (Spain)

- Dynamic capacity payment: capacity payment is based on the Loss of Load Probability (England and Wales)

- Energy-only: no explicit payments or obligation (Scandinavia, California)

- Proxy prices: very high administrative prices are used as a proxy to the Value of Lost Load when load shedding is necessary (Australia)

- Capacity subscription: cf. the description above (not implemented)

As could be expected, no single policy performs best on all criteria. The obligation and fixed payment methods do not perform well on market efficiency criteria, as essentially they are not market-based policies. The proxy prices policy is a reasonable policy on most criteria. It is easy, cheap and quick to implement. Because there is little experience with the method so far, there is some uncertainty with respect to if it is effective. One can anticipate that the threat of having to buy power at rationing prices will motivate market participants to avoid coming in a buying position in such cases, and that this will stimulate the adaptation of innovative solutions, especially on the demand side.

The capacity subscription policy looks very promising on the issues of efficiency, robustness and system security. This is especially true for dynamic efficiency: consumers will weigh the cost of capacity against the cost of innovative load control devices, and if the price of capacity is high, a market for such technology will emerge. However, there is a considerable threshold prior to the introduction of capacity subscription, caused by the implementation costs and complexity.

The conclusion on policies is thus that in an early stage after restructuring it may be appropriate to resort to the capacity obligation or payment method if the capacity balance is tight at the time of transition. For the medium-term, or if there is ample capacity initially, it is sensible to introduce proxy market prices to transfer the risk of a capacity deficit to market participants, with due attention being paid to the appropriate price level. Capacity subscription can be a long-term objective.

This thesis analyzes generator reactive power dispatch under restructured power systems from two different perspectives.
The first follows the two-step approach adopted by some electricity markets where first, the generators' real powers are dispatched in the energy market, followed by the dispatching of the generator reactive power support services in the ancillary services market.
Once the generators' real power has been dispatched in the energy market, the generators' reactive power is dispatched according to the minimization of a combination of multiple objectives: network MW loss cost, generator opportunity cost, and generator MW shift cost. The MW loss cost is represented as a function of bus voltage magnitudes and angles as well as the nodal prices in $/MWh found in the first step. Opportunity cost is represented as a function of the generator reactive powers, whose cost parameters are derived in terms of the MW dispatch, the MW nodal prices and the generators' capabilities. The generator shift cost is represented as a function of the generator real powers and the MW shift weighting factor. As these three objectives may conflict, compromises are needed to arrive at an optimum solution.
The second reactive power dispatch approach unifies real and reactive power dispatch by minimizing both MW and MVAr generation costs while enforcing the MW and MVAr/voltage constraints simultaneously. This unified dispatch avoids a disadvantage of the two-step MVAr dispatch, that is, that the MW price signal determined in the energy market may be distorted by the subsequent MVAr dispatch in the ancillary services market.
Several numerical examples under different conditions are presented to examine and compare the effectiveness of these two methods.

This dissertation is mainly focused on technical issues associated with load-frequency control (LFC) in restructured power systems. Operating the power system in the deregulated environment will certainly be more complex than in the past, due to the considerable degree of interconnection, and to the presence of technical constraints to be considered together with the traditional requirements of system reliability. However at present, the power system utilities participate in LFC task with simple, heuristically tuned controllers. In response to the new technical control demands, the main goal of this dissertation is to develop the robust decentralized LFC synthesis methodologies for multi-area power systems based on the fundamental LFC concepts and generalized well-tested traditional LFC scheme to meet the specified LFC objectives. The dissertation is organized as follows: Chapter 1 gives a general introduction on load-frequency control problem and its conventional control scheme. The past achievements in the LFC literature are briefly reviewed, and the main objectives of the present dissertation are summarized. Chapter 2 introduces modified models to adapt well-tested classical LFC scheme to the changing environment of power system operation under deregulation. The main advantage of the given strategies is the use of basic concepts in the traditional framework, and avoiding the use of impractical or untested LFC models. The introduced structures provide the base models for robust LFC synthesis in the subsequent chapters. Chapter 3 presents two robust decentralized control design methodologies for LFC synthesis using structured singular value theory (µ). The first one describes a new systematic approach to design sequential decentralized load-frequency controllers in multi-area power systems. System uncertainties, practical constraint on control action and desired performance are included in the synthesis procedure. The robust performance in terms of the structured singular value is used as a measure of control performance. The second control methodology addresses a control approach to design of robust load frequency controller in a deregulated environment. In this approach the power system is considered under the pluralistic-based LFC scheme, as a collection of separate control areas. Each control area can buy electric power from some generation companies to supply the area-load. Multi-area power system examples are presented demonstrating the controllers’ synthesis procedures and advantages of proposed strategies. In chapter 4, the decentralized LFC synthesis is formulated as an H∞-based static output feedback (SOF) control problem and is solved using an iterative linear matrix inequalities (ILMI) algorithm to design of robust PI controllers in multi-area power systems. Two multi-area power system examples using both traditional and bilateral based LFC schemes with a wide range of load changes are given to illustrate the proposed approach. Chapter 5 is organized in two main sections. In the first one, the LFC problem is formulated as a multi-objective control problem and the mixed H2/H∞ control technique is used to synthesis the desired robust controllers for LFC system in a multi-area power system. In the second section, with regard to model uncertainties, the multi-objective LFC problem is reformulated via a mixed H2/H∞ control technique and then in order to design a robust PI controller, the control problem is reduced to a static output feedback control synthesis. Finally, the problem is easily solved using a developed ILMI algorithm. The proposed methods are applied to multi-area area power system examples under different LFC schemes. The results are compared with pure control design. Chapter 6 summarizes the research outcomes of this dissertation.

This thesis describes the development of three decision support models for long-term investment planning in restructured power systems. The model concepts address the changing conditions for the electric power industry, with the introduction of more competitive markets, higher uncertainty and less centralised planning. Under these circumstances there is an emerging need for new planning models, also for analyses of the power system in a long-term perspective. The thesis focuses particularly on how dynamic and stochastic modelling can contribute to the improvement of decision making in a restructured power industry. We argue that the use of such modelling approaches has become more important after the introduction of competitive power markets, due to the participants’ increased exposure to price fluctuations and economic risk. Our models can be applied by individual participants in the power system to evaluate investment projects for new power generation capacity. The models can also serve as a decision support tool on a regulatory level, providing analyses of the long-term performance of the power system under different regulations and market designs.

In Chapter 1, we give a brief introduction to the ongoing development towards restructuring and liberalisation of the electrical power system. A discussion of the operation and organisation of restructured power systems is also provided. In Chapter 2, we look more specifically at different modelling approaches for expansion planning in electrical power systems. We also discuss how the contributions in this thesis compare to previous work in the field of decision support models for long-term planning in both regulated and competitive power systems. In Chapter 3, we develop a power market simulation model based on system dynamics. The advantages and limitations of using descriptive system dynamics models for long-term planning purposes in this context are also discussed. Chapter 4 is devoted to a novel optimisation model which calculates the optimal investment strategy for a profit maximising investor considering investments in new power generation capacity. The model is based on real options theory, which is an alternative to static discounted cash flow evaluations of investments projects under uncertainty. In the model we represent load growth as a stochastic variable. A stochastic dynamic programming algorithm is applied in order to solve the investment problem. Prices and profits are calculated in a separate model, whose parameters can be estimated based on historical data for load, prices and installed capacity in the power system. In Chapter 5, we extend the stochastic dynamic optimisation model from Chapter 4, so that the investor now can choose between two different power generation technologies to invest in. An alternative representation of the power market is also implemented, which makes it possible to use either a profit or a social welfare objective in the optimisation. With this model we can compare the optimal investment decisions, and the dynamics of investments, prices and reliability, which follow from centralised and decentralised decision making.

The main scientific contributions in the thesis lie in the combined use of economic theory for restructured power systems and theory for optimal investments under uncertainty. With an explicit representation of the power market, the dynamic investment models can identify profit maximising investment strategies under different regulations and market designs. The use of physical state variables in the models also facilitates analyses of the long-term consequences for the power system, which result from the optimal decentralised investment decisions. Decision support models for expansion planning in the regulated power industry do not address the aspect of competition and decentralised decision making. At the same time, long-term uncertainties and their impact on optimal investment decisions are rarely represented in planning models for the competitive industry. The stochastic dynamic models in this thesis therefore provide a new framework for long-term analysis of investments and prices in restructured power systems.

Potential applications of the investment models are demonstrated in a number of illustrative examples in the thesis. Through the analyses in these examples we have gained increased insight into the complex dynamics of prices, investments and security of supply in competitive power systems.

As open access market principles are applied to power systems, significant changes are happening in their planning, operation and control. In the emerging marketplace, systems are operating under higher loading conditions as markets focus greater attention to operating costs than stability and security margins. Since operating stability is a basic requirement for any power system, there is need for newer tools to ensure stability and security margins being strictly enforced in the competitive marketplace. This dissertation investigates issues associated with incorporating voltage security into the unbundled operating environment of electricity markets. It includes addressing voltage security in the monitoring, operational and planning horizons of restructured power system. This dissertation presents a new decomposition procedure to estimate voltage security usage by transactions. The procedure follows physical law and uses an index that can be monitored knowing the state of the system. The expression derived is based on composite market coordination models that have both PoolCo and OpCo transactions, in a shared stressed transmission grid. Our procedure is able to equitably distinguish the impacts of individual transactions on voltage stability, at load buses, in a simple and fast manner. This dissertation formulates a new voltage stability constrained optimal power flow (VSCOPF) using a simple voltage security index. In modern planning, composite power system reliability analysis that encompasses both adequacy and security issues is being developed. We have illustrated the applicability of our VSCOPF into composite reliability analysis. This dissertation also delves into the various applications of voltage security index. Increasingly, FACT devices are being used in restructured markets to mitigate a variety of operational problems. Their control effects on voltage security would be demonstrated using our VSCOPF procedure. Further, this dissertation investigates the application of steady state voltage stability index to detect potential dynamic voltage collapse. Finally, this dissertation examines developments in representation, standardization, communication and exchange of power system data. Power system data is the key input to all analytical engines for system operation, monitoring and control. Data exchange and dissemination could impact voltage security evaluation and therefore needs to be critically examined.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Technology, Management, and Policy Program, 2001.
Includes bibliographical references (p. 193-209).
Modem society requires reliable and safe operation of its infrastructure. Policymakers believe that, in many industries, competitive markets and regulatory incentives will result in system performance superior to that under command-and-control regulation. Analytical techniques to evaluate the reliability and safety of complex engineering systems, however, do not explicitly account for responses to market and regulatory incentives. In addition, determining which combination of market and regulatory incentives to use is difficult because policy analysts' understanding of complex systems often depends on uncertain data and limited models that reflect incomplete knowledge. This thesis confronts the problem of evaluating the reliability of a complex engineering system that responds to the behavior of decentralized economic agents. Using the example of restructured and partially deregulated electric power systems, it argues that existing engineering-based reliability tools are insufficient to evaluate the reliability of restructured power systems. This research finds that electricity spot markets are not perfectly reliable, that is, they do not always result in sufficient supply to meet demand. General conclusions regarding the reliability of restructured power systems that some economic analysts suggest should be the basis of reliability policies are either verified or demonstrated to be true only when applied to extremely simple and unrealistic models. New generation unit and transmission component availability models are proposed that incorporate dependent failure modes and capture the behavior of economic agents, neither of which is considered with current adequacy techniques.
(cont.) This thesis proposes the use of a probabilistic risk analysis framework as the foundation for bulk power-system-reliability policy to replace existing policy, which is an ad hoc mixture of deterministic criteria and risk-based requirements. This thesis recommends distinguishing between controlled, involuntary load curtailments and uncontrolled, involuntary load curtailments in power system reliability modeling. The Institute of Electrical and Electronics Engineers (IEEE) Reliability Test System is used to illustrate the possible impact that dependent failure modes and the behavior of economic agents have on the reliability of bulk power systems.
by Frank A. Felder.
Ph.D.

As the power industry across the world is experiencing a radical change by separation of transmission from generation activities, creation of competition by bidding or through provision of bilateral transactions in spot markets, there is need for the unit commitment in power industry with generation biddings, load biddings and bilateral transaction biddings. In general Unit Commitment can be formulated as non-linear, large scale, mixed integer combinatorial optimization problem. For Better optimized result with quick response, piece-wise linearization of cost function and slack terms with high penalty factor are incorporated in unit commitment along with all generator, system, operator and line constraints. In order to get convergence solution with UC, OPF is performed with fixed unit status from unit commitment solution by taking account of generator ramp rates. Unit Commitment with 3-part generator bidding, load bidding and bilateral transaction with both elastic and inelastic parts is performed which is suitable for the recent power industry.

The prime objective of automatic generation control (AGC) is to adjust the active power generation in response to variable power demands and hence to maintain scheduled system frequency and scheduled tie-line power flows with neighboring control areas at desired tolerance values. A sizeable fall in frequency might badly affect the timing of electric clocks, magnetizing currents in transformers/induction motors, constant speed of AC motors, continuous operation of processes and synchronous operation of various units in power system. Additionally, power system may face a serious instability problem at substantial drop in the frequency. In steady state, automatically these variations must be zero. Enhanced power system stability is achieved with the proper design of supplementary controller adopted in an AGC system. However, continuous growth in size and complexity, stochastically changing power demands, system modeling errors, alterations in electric power system structures and variations in the system parameters over the time has turned AGC task into a challenging one. Consequently, conventional control strategies may be incompetent to handle such unpredictable variations in an AGC system. Hence, the researchers over the world are trying to propose several novel control strategies that fuse knowledge, techniques and methodologies from varied sources to tackle AGC problem of power system effectively. The literature survey indicates that several researchers, to tackle AGC issue in restructured system, have presented various types of controllers optimized using various conventional and intelligent soft computing techniques. The literature survey also unveils that the performance of AGC system depends chiefly on the sort of intelligent technique exploited and structure of the controller. Hence, the goal of the present study is to propose different types of new vi supplementary controller structures for various types of restructured as well as traditional power systems. The presented work is divided into ten chapters. Chapter 1 deals with the introduction of AGC topic in deregulated environment. Chapter 2 presents a critical review of AGC schemes in restructured power system. Chapter 3 stresses on the modeling of traditional and restructured power systems under the study. The main simulation work starts from Chapter 4. In Chapter 4, the study is firstly conducted on a proposed restructured two-area multi-source hydrothermal and hydrothermal gas power systems interconnected via AC and AC/DC parallel tie-lines. Modern optimal control theory based optimal PI structured controllers are designed with full state vector feedback control strategy employing performance index minimization criterion. From the results obtained in the study, it is substantiated that the use of AC/DC parallel links as an area interconnection shows enrichment in the dynamic performance of the system in terms of less oscillations, settling time and peak overshoots/undershoots in the deviation in frequency and tie-line power responses. Eigenvalue study confirmed the positive effect of AC/DC parallel links on the system dynamic performance and stability. It is also observed that the multi-source hydrothermal system shows inferior performance in comparison to the single-source thermal system due the presence of hydro source in each area of the multi-source hydrothermal system due to the non-minimum phase characteristics of hydro turbines. The full state feedback optimal PI controllers work well and are very much robust but in realistic environments, the measurement of all states is not feasible all the time. Hence, next, in Chapter 5, some modern methods are adopted to conduct the study. In first attempt, a modified fuzzy PI (FPI) controller optimized using genetic algorithm vii (GA) is proposed for different electric power system models such as traditional two area non-reheat thermal, reheat thermal, multi-source hydrothermal and restructured two-area reheat thermal systems. In traditional two-area multi-source hydrothermal system, each control area owns two generating units, one non-reheat thermal and one mechanical governor based hydro power plant. However, in restructured two-area single-source system, each control area owns two single reheat thermal generating units. Firstly, a FPI-1 controller is designed with nominal range of membership functions (mfs) and GA tuned output scaling factors. Secondly, to test the impact of alteration in horizontal range of mfs of FPI-1, it is further optimized to get FPI-2 controller. The results of FPI-1 and 2 controllers are compared and the results due to later controller are found to be superior. Yet, FPI controllers are designed only for a traditional two-area non-reheat thermal system; they are successfully applied on other system under studies. The performance of FPI controllers is found significantly superior in terms of lesser numerical values of settling times (STs), peak undershoots (PUs) and various performance indices (PIs) compared to conventional controllers based on optimal, GA, gravitational search algorithm (GSA), bacterial foraging optimization algorithm (BFOA), hybrid BFOA-particle swarm optimization (hBFOA PSO) and hybrid firefly algorithm-pattern search (hFA-PS) techniques. Next, in Chapter 6, BFOA optimized fuzzy PI (FPI) and fuzzy PID (FPID) controllers are proposed for traditional two-area non-reheat thermal, reheat thermal, multi-source hydrothermal and restructured multi-source hydrothermal power systems. BFOA is used to simultaneously tune the input and output scaling factors of FPI/FPID controller keeping mfs and fuzzy rules invariant. It is observed that FPI controller shows superior results in terms of lesser values of STs/PUs/PIs compared to PI controller based on recently reported techniques like GA/PSO/BFOA/hBFOA viii PSO/hFA-PS/FA/artificial bee colony (ABC) and FPI controller tuned using PS/PSO algorithms for the same system design. Further, a fractional order PID (FOPID) structured controller is suggested for AGC problem solution of power systems in Chapter 7. The parameters of FOPID controller are optimized exploiting BFOA. At first, a traditional two-area multi-source hydrothermal system is considered and the advantage of FOPID is established over PI/PID controller optimized using hFA-PS and PID controller optimized using grey wolf optimization (GWO) techniques. To show the effectiveness of the method, the approach is further extended to restructured two-area multi-source hydrothermal and thermal gas systems. The analysis of the simulation results discloses the efficacy of FOPID controller over BFOA/differential evolution (DE)/GA optimized PID controller. Then, the study is extended to a restructured three-area multi-source hydrothermal power system. In the next step of the study, a maiden attempt is made to propose a fractional order fuzzy PID (FOFPID) controller for traditional two-area multi-source hydrothermal, restructured two-area multi-source hydrothermal, restructured two-area multi-source thermal gas and restructured three-area multi-source hydrothermal AGC systems in Chapter 8. The parameters of FOFPID controller are also tuned utilizing BFOA. The critical analysis of the obtained results revealed the worth of FOFPID controller over FOPID controller in terms of less numerical value of STs, PUs and PIs. It is also experienced that FOFPID controller satisfies the AGC requirements in different power transactions taking place under deregulated environment more fruitfully than FOPID controller. In Chapter 9, FOFPID controller is implemented in AGC of restructured three area multi-source hydrothermal system considering appropriate generation rate ix constraint (GRC), deadzone (DZ), boiler dynamics (BD) and time delay (TD). However, controller is optimized for linear system it works robustly in the presence of GRC/DZ/BD/TD physical constraints; though in the presence of GRC/DZ/BD/TD the system performance degraded drastically in comparison to the linear or the system with GRC only. Further, investigations clearly reveal that the controller is found to perform well when the system is subjected to higher degree of uncontracted load demands and simultaneous occurrence of uncontracted load demands. Thus, controller parameters obtained for the linear system are robust enough and need not be retuned for the system having appropriate GRC or GRC/DZ/BD/TD or wide changes in the size and location of contract violations. Thus, BFOA tuned FOFPID controller and other controllers proposed in the previous chapters may be options to supply reliable power with quality to the consumers. Finally, Chapter 10 presents an overview of the contributions made in the current thesis. Few suggestions are also given to extend the research in the future.