G.B. Shrestha

Congestion-driven transmission expansion in competitive power markets

A framework for transmission planning in a deregulated power market environment is discussed. The level of congestion in the network is utilized as the driving signal for the need of network expansion. A compromise between the congestion cost and the investment cost is used to determine the optimal expansion scheme. The long-term network expansion problem is formed as the decoupled combination of: 1) the master problem (minimization of investment costs subject to investment constraints and the Benders cuts generated by the operational problem (power pool) and 2) the operational problem, whose solution provides congestion details and associated multipliers. A proper power-pool model is developed and solved for congestion cost, congestion revenue, and transmission shadow prices. Linear programming is utilized to solve the investment subproblem, while the quadratic programming technique has been used to solve the operational problem. The algorithm has been developed for the complete planning process, which provides the expansion schemes for the planning horizon. The technique has been applied to illustrate the network planning study for a modified IEEE 24-bus test system.

Medium term power planning with bilateral contracts

This paper addresses the optimal management of hydropower resources on medium term. The objective is to maximize the expected revenue of a producer, and the decision variables are generation and forward contracts in each period for each scenario. Stochastic linear and nonlinear programming has been used as a framework for modeling and solution. Results are exposited for a Norwegian power producer participating in Nord Pool, the Nordic power exchange.

Strategic self-dispatch considering ramping costs in deregulated power markets

Ramp rates of generators are generally specified within elastic range of the strength of the shaft to safeguard the rotor from fatigue. These limits can, however, be exceeded, albeit at the risk of reducing the rotor life. Such effects on the rotor life can be compensated by incorporating appropriate ramping costs. Power demand and power price in deregulated power markets have shown a tendency of sudden wide excursions over short intervals of time. The ability to respond to such fast change in demand and price can be quite rewarding. This provides the motivation to utilize the ramping rates beyond traditional elastic limits. This paper studies the strategic use of ramping rates beyond elastic limits in a power producers self-dispatch in a power market with price and demand volatility. A set of ramping processes has been developed from ramping-cost versus ramping time relationships to derive the total operation cost including ramping costs for various levels of ramping rates exceeding elastic limits. A thorough theoretical analysis has been conducted for the selection of the optimal ramping process under different conditions. A numerical example is presented to highlight the potential benefits from the optimal use of these ramping processes. It is seen that the benefit from the strategic use of ramp rates beyond elastic limits not only depends on the high price in the power market but also on the initial loading of the generator which limits the capacity available for dispatch.

Power system stability enhancement using static phase shifter

The role of static phase shifters in improving power system stability is investigated. A new technique, based on the nonlinear variable structure control principle, is used to formulate a control algorithm for the static phase shifter. Parameter uncertainty has been considered in the proposed scheme. Computer simulations show that a static phase shifter with the new control scheme has produced significant improvement in power system performance.

Price based unit commitment for Gencos in deregulated markets

Some power markets require the Gencos to bid for each individual generator rather than for a group of units. So, it may be desirable to develop unit commitment and generation schedule strategies for individual units. This paper presents a technique to optimize the unit commitment and generation schedules on the basis of the forecasted price. A methodology based on dynamic programming and enumeration has been proposed. The technique has further been extended to optimize the problem for a group of generators. The technique is explained with illustrative examples and then applied to several systems reported in the literature. The results obtained are very encouraging, comparable, if not better, than the results reported earlier in all cases. Finally, the proposed technique is quite simple and requires significantly less computational time.

Strategic Bidding for Minimum Power Output in the Competitive Power Market

As deregulation of the power industry is becoming a reality, there has been an intense interest in the strategic bidding for suppliers to optimize their benefits. The benefit gained by a supplier is related not only to its energy-price bid curve but also to its submitted operational parameters such as minimum output, etc. This is especially so when market size is limited because of a limited number of competitors in the market itself or due to the transmission capacity constraints. This paper addresses the study of strategic bidding for minimum output in a deregulated environment. The impact of minimum output bids on the market result is analyzed. A criterion with regard to minimum output bid to assess the outcome of competition among suppliers is derived. The method to optimize the benefit from a suppliers viewpoint by adjusting the bids for the minimum output and price is proposed. It is shown that an individual supplier can optimize its own benefit by fine-tuning its minimum output and price when there are only a few suppliers dominating the market. A fairly thorough theoretical analysis of the bidding for minimum output is illustrated with a numerical example.

Profit based unit commitment in competitive markets

The unit commitment of a thermal power producer is addressed which is based on the price behavior in the spot market. The classical unit commitment objective has been redefined to a profit-maximizing objective to match the competitive market. A new method using heuristic technique in coordination with dynamic programming and nonlinear programming has been proposed to solve the unit-scheduling problem. The proposed technique is first compared with the available techniques and is subsequently applied to the profit based unit commitment (PBUC) problem. The results are compared to evaluate the performance of the proposed technique and the implications of PBUC in the competitive market are discussed.

Enhancing power engineering education through the use of design modules

This paper describes the main features of four design modules that form part of the curriculum for the final year power engineering students at the Nanyang Technological University, Singapore. Through the use of these modules, the students gain an insight into the various aspects of power engineering-including power electronics and drives-and this will hopefully help them in a better understanding of the practical aspects of power engineering, and therefore make them better engineers in the power industry. The four modules described are Generating Capacity Expansion Planning, Rectifier and DC Motor Control, Power Systems Operations Planning, and Security Enhancement using Optimal Power Flow.

A Study on the Pricing of Network Services

This paper compares two marginal cost based transmission pricing methods, which can be directly incorporated into the energy dispatch models. In both the proposed methods direct transmission costs (embedded cost) as well as re-dispatch cost (out-of-merit generation cost) caused by network losses and network congestion, are accounted under a unified model. Method-1 employs Power Transfer Distribution Factors (PTDF) to model network related details. Method-2 utilizes modified DC power flow techniques to represent the network. The merits and de-merits of the two approaches are discussed using the results obtained for a simple 3-node network and the modified IEEE 24-bus reliability test system (RTS).

Maximizing Profit of a Wind Genco Considering Geographical Diversity of Wind Farms

Uncertainty and geographical diversity of wind speeds create risk for a wind power generation company (WGenco) to make the maximum profit from power market trading. A probabilistic approach is proposed to estimate the profit of a WGenco considering geographical diversity and uncertainty of wind speeds and market prices. The objective of the optimization problem is to assist a WGenco to do the optimal bidding in market trading in order to make the maximum profit under various market and wind speed uncertainties. The point estimate method (PEM) has been improved to facilitate stochastic modeling of the aggregated power output of wind turbine generators in different locations in the problem formulation. The principal component analysis (PCA) is used to manage correlated wind speeds.