Electricity markets are open after the deregulation of power systems due to competition. An optimization problem based on dynamic economic dispatch has recently come up in the new context of deregulated power systems known as bid-based dynamic economic dispatch (BBDED). It is one of the major operations and control functions in the electricity markets used to determine the optimal operations of market participants with scheduled load demands during a specified period. BBDED involves power generation companies (GENCOs) and customers to submit energy and price bids to the independent system operator (ISO) in a day-ahead market. The ISO clears the market with the objective of social profit maximization. In this paper, a BBDED problem is solved using an improved simulated annealing algorithm (ISA), including system constraints with different periods under bidding strategies. The proposed ISA technique is implemented in MATLAB and applied on a 3-unit system, a 6-unit system, and a 40-unit large-scale system. The proposed ISA is evaluated by comparison with relevant methods available in the literature, to demonstrate and confirm its potential in terms of convergence, robustness, and effectiveness for solving the BBDED problem.

This paper presents an application of quadratic programming (QP) for solving dynamic economic load dispatch (DELD) problem with minimum gas emission. This problem determines optimum power generation schedule while minimizing gas emission. The proposed QP method takes care of different unit and system constraints to find optimal solution. To validate the effectiveness and the feasibility of the approach, it has been examined on different standard test cases, (i) a -unit, (ii) and 10-unit test system. Simulation results obtained are also compared with other reported methodology. The comparison confirms the superiority, fast convergence and proficiency of the algorithm. KeywordsEconomic load dispatch; quadratic programming; gas emission.I.

No abstract

The voltage control problem is generally difficult because of the large scale and non-linear characteristics in power systems. Based on the power system status, the reactive power and voltage control is required to make the correct decision in order to get the system back to an acceptable operating state. For this purpose we have developed in this paper an algorithm based on Fuzzy Logic in order to control the VAR resources, transformer tap changer and PV pus voltage in a power system under abnormal and/or contingency operation to maintain the voltage at all buses within acceptable limits, when minimizing the number of control actions. The algorithm is iterative and designed to take advantage decoupling the load flow Jacobean matrix to decrease the computation time. The effectiveness of the developed algorithm is identified through its application to the IEEE 14 test system. The calculation results show excellent performance of the proposed method, in regard to computation time and quality of results.