Raymond B. Johnson

Short-term resource scheduling with ramp constraints [power generation scheduling]

This paper describes a Lagrangian relaxation-based method to solve the short-term resource scheduling (STRS) problem with ramp constraints. Instead of discretizing the generation levels, the ramp rate constraints are relaxed with the system demand constraints using Lagrange multipliers. Three kinds of ramp constraints, startup, operating and shutdown ramp constraints are considered. The proposed method has been applied to solve the hydro-thermal generation scheduling problem at PG&E. An example alone with numerical results is also presented.

Equity and efficiency of unit commitment in competitive electricity markets

Abstract We examine the effects of competition and decentralized ownership on resource scheduling. It is shown that centralized scheduling of multi-owned resources under imperfect information may face difficulties that do not arise when resources are centrally owned. A simulation case study is performed using a Lagrangian relaxation-based unit commitment algorithm modified to simulate proposed second-price pool auction procedures. We show that variations in near optimal unit commitments that have negligible effect on total costs could have significant impact on the profitability of individual resources. These results raise serious questions regarding the feasibility of proper mechanisms to oversee the efficiency and equity of a mandatory centrally dispatched pool.

A transmission-constrained unit commitment method in power system scheduling

This paper presents a transmission-constrained unit commitment method using a Lagrangian relaxation approach. Based on a DC power flow model, the transmission constraints are formulated as linear constraints. The transmission constraints, as well as the demand and spinning reserve constraints, are relaxed by attaching Lagrange multipliers. A three-phase algorithmic scheme is devised including dual optimization, a feasibility phase and unit decommitment. A large-scale test problem with more than 2200 buses and 2500 transmission lines is tested along with other test problems. q 1999 Elsevier Science B.V. All rights reserved.

Price-based adaptive spinning reserve requirements in power system scheduling

In a deregulated electricity market such as the California WEPEX, spinning reserves must be explicitly identified as an ancillary service and priced. Additionally, scheduling coordinators who match suppliers and demands may either self-provide spinning reserves, or rely on the Independent System Operator (ISO) to provide reserves at the spot price. The deregulated market structure makes explicit the implicit softness that has always been recognized in the reserve constraints: additional reserves may have value even when a minimum reserve requirement has been met. In this paper we formulate the spinning reserve requirement (SRR) as a function of the endogenously determined marginal values of reserves. The spinning reserve requirement depends, according to a non-increasing response function, on a price/value signal. We present three power system scheduling algorithms in which this price/value signal is updated at each iteration of a dual optimization. Game theory is used to interpret the proposed algorithms. Numerical test results are also presented.

A unit decommitment method in power system scheduling

This paper presents a unit decommitment method for power system scheduling. Given a feasible unit commitment, our algorithm determines an optimal strategy for decommitting overcommitted units based on dynamic programming. This method is being developed as a possible post-processing tool to improve the solution quality of the existing unit commitment algorithm used at PG&E. It can also be integrated into any other unit commitment method or used as a complete unit commitment algorithm in itself. The decommitment method can also be used as a tool to measure the solution quality of unit commitment algorithms. The proposed method maintains solution feasibility at all iterations. In this paper we prove that the number of iterations required by the method to terminate is bounded by the number of units. Numerical tests indicate that this decommitment method is computationally efficient and can improve scheduling significantly.

Volatility of unit commitment in competitive electricity markets

We examine the effects of competition and decentralized ownership on resource scheduling. We show that centralized scheduling of multi-owned resources under imperfect information may face difficulties that do not arise when resources are centrally owned. We perform a simulation case study using a Lagrangian relaxation-based unit commitment algorithm modified to simulate proposed second-price pool auction procedures. This algorithm is based on the Hydro-Thermal Optimization (HTO) program used in short-term resource scheduling at PG&E. We demonstrate both the volatility of simulation outcomes for resources not base loaded, and the especially negative consequences of volatility for marginal resources (i.e., resources that frequently determine system marginal costs). Specifically, we show that variations in near optimal unit commitments that have negligible effect on total costs could have significant impact on the profitability of individual resources. These results raise serious questions regarding the feasibility of proper mechanisms to oversee the efficiency and equity of a mandatory centrally dispatched pool.

Positioning for a Competitive Electric Industry with Pg&E'S Hydro-Thermal Optimization Model

The Hydro-Thermal Optimization (HTO) system optimizes the weekly electric production schedules of Pacific Gas and Electric Companys diverse resource mix. PG&E developed HTO to reduce operating costs, forecast marginal costs, and position itself for competition. PG&E implemented the system after extensive prototyping and validation and uses HTO daily for unit commitment, hydro scheduling, energy trading, fuel forecasting, resource evaluation, and marginal cost-based pricing. PG&E estimates annual benef its of HTO conservatively at

Comparative analysis of the convergence characteristics of second-order loadflow methods

15 million. On a broader scale, PG&E has used HTO to analyze auction protocols for a deregulated power market and demonstrated that use of HTO-like tools to administer a power auction, as is done in the UK, could result in profit distribution inequities among bidders. HTO thus enabled PG&E to support a profound change in Californias restructuring of the electric industry, from the proposed UK-type pool to a decentralized decision-making framework in which bidders optimize their own operations. As a result, Californias

A new unit commitment method

20 billion electric-power market will realize increased efficiencies and savings for both taxpayers and consumers.

Hydro unit commitment in hydro-thermal optimization

Abstract The second-order loadflow technique defined in rectangular coordinates has become attractive because of the large amount of computation required in the evaluation of polar trigonometric functions in conventional loadflow methods. Seven versions of the second-order loadflow technique are developed and their convergence characteristics and computing times determined with tests carried out on the IEEE 14 and 30 bus networks. It is suggested that the version based on the CRIC approach warrants further developments into optimal power flows and automatic contingency selection algorithms for real-time control.