2. 4 Economic Load Dispatch With Transmission Losses : Analysis

(3 marks) c) Determine the optimal number of bus and train travelers. (2 marks) d) Say a train strike significantly reduced the number of trains available. By how much would the train capacity constraint have to fall for the optimal solution to be altered? (2 marks)

After finishing high school I will be attending St. Clair for their fast track power engineering program learning things like the operation of steam boilers and more depending on how far i go with the tickets, and if I decide to move away or stay close to home. First off in the power engineering field I have to know things from the operation of steam boilers, to refrigeration systems and more. Second there are different classes of power engineering ranging from the fourth class to the first class ticket with different salaries and places to work with each ticket. Lastly if I end up not being able to get a job in power engineering there are other options I could branch into with this course. After finishing high school and attending St. Clair for power engineering all these things need to be taken into account when figuring out where I will finally end up with my career.

Table 12: Factor and their level for maximizing throughput and system utilization through genetic algorithm

Dispatched generator real power output should not exceed the maximum real power capability of the unit (Pgen = Pmin). Note: Although small violations of this Pmin rule appear trivial, the result is same for all violations – the case will not initialize in dynamics.

Find the optimal solution using the graphical method (use graph paper). Identify the feasible region and the optimal solution on the graph. How much is the maximum profit? Consider the following linear programming problem: Minimize Z = 3 x + 5 y (cost, $) subject to 10 x + 2 y ≥ 20 6 x + 6 y ≥ 36 y ≥ 2 x, y ≥ 0 Find the optimal solution using the graphical method (use graph paper). Identify the feasible region and the optimal solution on the graph. How much is the minimum cost? 2. The Turner-Laberge Brokerage firm has just been instructed by one of its clients

The energy output from all three Projects is fully contracted. About 72% of the output is sold at a fixed price+ a revenue escalator to the investment grade off-takers and the remaining output sold to Commonwealth Edison (“ComEd”) for the 28% of the total capacity (147.5 MWs) has a minimum output requirement that are based on 115% of the P50 exceedance level output. In addition, the regulatory curtailments are non-reimbursable and there is a basis risk in terms of the point of interconnect and the nod for the financial settlement of the derivatives. Inability to deliver the minimum contracted quantity adds to the price volatility since the LD Project must reimburse ComEd the difference between the spot energy price and the contract price. The Analyst notes that the sport electricity prices have been significantly below the contract price that is annually adjusted by an inflation rate of 2%. Under the SFS EF AM sensitivity case, increase in the sport price by 500% will lower cash flows by about $10 million annually. The Analyst notes that the contract price is about 90% higher than the historical and the expected spot energy prices in the ComEd service area.

The Darby Company is re-evaluating its current production and distribution system in order to determine whether it is cost-effective or if a different approach should be considered. The company produces meters that measure the consumption of electrical power. Currently, they produce these meters are two locations – El Paso, Texas and San Bernardino, California. The San Bernardino plant is newer, and therefore the technology is more effective, meaning that their cost per unit is $10.00, while the El Paso plant produces at $10.50. However, the El Paso plant has a higher capacity at 30,000 to San Bernardino’s 20,000. Once manufactured, the meters are sent to one of three distribution centers – Ft. Worth, Texas, Santa

D. Card et al.(2007)[33] This paper presents a review on distributed generation planning in the distribution power system networks from different power system performances such as minimization of real and reactive power loss

The major benefit of using a GA is that it does not require gradient information which is generally computationally expensive. Several authors worked on developing genetic algorithms and improving the genetic operators as well as fine tuning parameters [29,30,31]. However, they can be computationally expensive for more complex design problems and suffer from local optima and convergence issues especially when coupled with finite element analysis [32,33].

An accurate cost function for the transmission system is formulated where both fixed and variable costs for all planned facilities are includes, in addition to the cost energy losses. The cost function is then minimized, using (BBO) algorithms. We can be used to derive algorithms for optimization. We apply the BBO on the model of IEEE of 6-bus test system.

This paper presents a Dynamic Programming (DP) method based an algorithm to solve the Unit Commitment (UC) scheduling of the thermal generation units in Yangon. Electricity demands are in its peak in Yangon, it has become very difficult for operators to fulfill the demand in the present. The main objective of Unit Commitment is to determine a minimum cost turn-on and turn-off schedule of a set of electrical power generating units to meet a load demand while satisfying a set of operational constraints. The total production costs include fuel, startup, shutdown, and no-load costs. There are many conventional and evolutionary programming methods used for solving the unit commitment problem. Dynamic programming method is one of the successful approaches to unit commitment problem. Dynamic Programming has many advantages over the enumeration scheme, the chief advantage being a reduction in the dimensionality of the problem. It is one of the refined algorithm design standards and is powerful tool which yields definitive algorithm for various types of optimization problems. To implement the unit commitment problem into an optimization program, the MATLAB® software is used.

In addition, the transmission capacity limits should be considered to optimize the total market cost. In this paper, a new approach based on constrained particle swarm optimization (CPSO) is developed to deal with the multi-product (energy and reserve) and multi-area electricity market dispatch problem. Constrained handling is based on particle ranking and uniform distribution. CPSO method offers a new solution for optimizing the total market cost in a multi-area competitive

Abstract-Due to the liberalization of the electricity market and the introduction of distributed generation (DG), the importance of distribution loss allocation (LA) has incremented. This paper presents developing method for distribution power LA in radial systems. The proposed method, which based on the results of power flow and considers active and reactive power flows of lines for Loss Allocation (LA) is composed of three steps. In the first step, starting from the source nodes, the puissance loss allocated to all nodes is calculated and then the power loss allocated to the loads connected to each node is obtain. In the next step, the total power loss is allocated to the nodes in order to calculate the power loss allocated to the DGs predicated on the results of this step. In contrast to the precursor step, in this step, allocating

The most popular technique in evolutionary computation research has been the genetic algorithm. In the traditional genetic algorithm, the representation used is a fixed-length bit string. Each position in the string is assumed to represent a particular feature of an individual, and the value stored in that position represents how that feature is expressed in the solution. Usually, the string is “evaluated as a collection of structural features of a solution that have little or no interactions”. The analogy may be drawn directly to genes in biological organisms. Each gene represents an entity that is structurally independent of other genes. The main reproduction operator used is bit-string crossover, in which two strings are used as parents and new individuals are formed by swapping a

Keywords – Long-term load forecasting, generation planning, transmission planning, WASP-IV, Newton-Raphson based load flow calculation