This paper presents an enhanced genetic algorithm (EGA) for the solution of the optimal power flow (OPF) with both continuous and discrete control variables. The continuous control variables modeled are unit active power outputs and generator-bus voltage magnitudes, while the discrete ones are transformer-tap settings and switchable shunt devices. A number of functional operating constraints, such as branch flow limits, load bus voltage magnitude limits, and generator reactive capabilities, are included as penalties in the GA fitness function (FF). Advanced and problem-specific operators are introduced in order to enhance the algorithm's efficiency and accuracy. Numerical results on two test systems are presented and compared with results of other approaches.

Optimal power flow by enhanced genetic algorithm

In this paper, the traditional automatic generation control (AGC) two-area system is modified to take into account the effect of bilateral contracts on the dynamics. The concept of distribution companies (DISCO) participation matrix to simulate these bilateral contracts is introduced and reflected in the two-area block diagram. Trajectory sensitivities are used to obtain optimal parameters of the system using a gradient Newton algorithm.

/pdf/simulation-and-optimization-in-an-agc-system-after-3sbh1k98e2.pdf

Simulation and Optimization in an AGC System after Deregulation

Participants in a competitive electricity market develop bidding strategies in order to maximize their own profits. On the other hand, it is necessary for regulators to investigate strategic bidding behavior in order to identify possible market power abuse and to limit such abuse by introducing appropriate market management rules. An interesting body of work has been done on this subject, and this paper presents a literature survey based on more than 30 research publications.

Strategic bidding in competitive electricity markets: a literature survey

Preface. Notation. 1. Background. 2. Introduction to SIME. 3. Sensitivity Analysis. 4. Preventive Analysis and Control. 5. Integrated TSA&C Software. 6. Closed-Loop Emergency Control. 7. Retrospect and Prospect. Appendices. References. Index.

Transient Stability of Power Systems: A Unified Approach to Assessment and Control

This paper presents an integrated distribution locational marginal pricing (DLMP) method designed to alleviate congestion induced by electric vehicle (EV) loads in future power systems. In the proposed approach, the distribution system operator (DSO) determines distribution locational marginal prices (DLMPs) by solving the social welfare optimization of the electric distribution system which considers EV aggregators as price takers in the local DSO market and demand price elasticity. Nonlinear optimization has been used to solve the social welfare optimization problem in order to obtain the DLMPs. The efficacy of the proposed approach was demonstrated by using the bus 4 distribution system of the Roy Billinton Test System (RBTS) and Danish driving data. The case study results show that the integrated DLMP methodology can successfully alleviate the congestion caused by EV loads. It is also shown that the socially optimal charging schedule can be implemented through a decentralized mechanism where loads respond autonomously to the posted DLMPs by maximizing their individual net surplus.

https://orbit.dtu.dk/files/57803323/s1-ln15464456276540516-1939656818Hwf35008047IdV121601649415464456PDF_HI0001.pdf

Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging Management

Three very different methods of accomplishing the same task-managing the operation of the transmission system in the deregulated power system operating environment-have been implemented as deregulated market structures have been created around the world. They are first, the optimal power flow (OPF) model found in various implementations in the United Kingdom, parts of the United States, and in Australia and New Zealand. Second, the point tariff, price area congestion control model used in the Nordpool market area in Norway and Sweden. Third, the US transaction-based model. All are pragmatic solutions implemented in advance of complete theoretical understanding. Each has strengths and flaws, and there are some surprising inter-relationships. Each maintains power system security but differs in its impact on the economics of the energy market. No clearly superior method has so far emerged. In the future, methods of combining decentralized market solutions with operational use of optimal power flow may provide better solutions to existing and emerging problems.

Transmission management in the deregulated environment

Three very different methods of accomplishing the same task-managing the operation of the transmission system in the deregulated power system operating environment-have been implemented as deregulated market structures have been created around the world. They are first, the optimal power flow (OPF) model found in various implementations in the United Kingdom, parts of the United States, and in Australia and New Zealand. Second, the point tariff, price area congestion control model used in the Nordpool market area in Norway and Sweden. Third, the U.S. transaction-based model. All are pragmatic solutions implemented in advance of complete theoretical understanding. Each has strengths and flaws, and there are some surprising inter-relationships. Each maintains power system security but differs in its impact on the economics of the energy market. No clearly superior method has so far emerged. In the future, methods of combining decentralized market solutions with operational use of optimal power flow may provide better solutions to existing and emerging problems.

R. D. Christie

Papers

Transmission management in the deregulated environment

Transmission management in the deregulated environment : The technology of power system competition