Cost Of Conventional Generation Research Articles

Optimal flexible alternative current transmission system device allocation under system fluctuations due to demand and renewable generation

This study proposes two methods for the optimal placement of flexible alternative current transmission system (FACTS) devices considering variations in demand and renewable generation output. The basic optimisation technique utilised is the differential evolution algorithm and the objective is to minimise the cost of generation. The static performance of the FACTS device is considered here. Simulation shows that with renewable generation present in the network, the system state at peak demand is not always the most suitable state to use for the determination of the optimal FACTS allocation. From this, techniques based on the Monte Carlo simulation are proposed to determine the location for which the operation of FACTS device gives highest benefit in terms of saving cost of conventional generation. These techniques collectively are called renewable uncertainty-based optimal FACTS allocation techniques. This study shows the effectiveness of the techniques in the determination of the optimal FACTS placement for networks with a high penetration of renewable generation.

Optimizing the Geographic Distribution of Wind Plants in Iowa for Maximum Economic Benefit and Reliability

By the end of June 1999, 250 MW of wind generation had been dedicated in the State of Iowa. This represents the beginning of what is likely to be significant wind capacity development during the next 20 years in the State as a result of possible governmental mandates and consumers' desire for sustainable sources of energy. After accounting for predicted load growth over the next 15 years, we estimate Iowa's potential wind energy portfolio through to the year 2015. Winds in the Midwest are primarily generated by fronts moving through the region. The purpose of this study is to find the best way to distribute wind-generating capacity among several sites by using an electricity-production, cost and reliability model. We calculate this benefit in terms of reduction in the fuel cost of conventional generators. We also consider system reliability in terms of energy not served (ENS). Our findings indicate that it is beneficial to develop wind power plants at several sites, and that there are many possible combinations of wind locations that can be chosen to obtain diversity benefits. We also calculate capacity credit for the composite wind power plants using two different methods, and calculate a trade-off curve between the economically optimal and the most reliable solutions. The methods we use to find the best geographical locations and sizes of wind power plant are based on a dynamic fuzzy search algorithm and a genetic algorithm. Each procedure produces a solution set that can be analyzed further in other contexts, such as voltage and land use constraints. We illustrate the sensitivity of the fuzzy economic benefit solutions to small perturbations of the capacity selections at each wind site. We find that small changes in site capacity and/or location have small effects on the economic benefit provided by wind power plants.