Antonio J. Conejo

Day-ahead electricity price forecasting using the wavelet transform and ARIMA models

This paper proposes a novel technique to forecast day-ahead electricity prices based on the wavelet transform and ARIMA models. The historical and usually ill-behaved price series is decomposed using the wavelet transform in a set of better-behaved constitutive series. Then, the future values of these constitutive series are forecast using properly fitted ARIMA models. In turn, the ARIMA forecasts allow, through the inverse wavelet transform, reconstructing the future behavior of the price series and therefore to forecast prices. Results from the electricity market of mainland Spain in year 2002 are reported.

Real-Time Demand Response Model

This paper describes an optimization model to adjust the hourly load level of a given consumer in response to hourly electricity prices. The objective of the model is to maximize the utility of the consumer subject to a minimum daily energy-consumption level, maximum and minimum hourly load levels, and ramping limits on such load levels. Price uncertainty is modeled through robust optimization techniques. The model materializes into a simple linear programming algorithm that can be easily integrated in the Energy Management System of a household or a small business. A simple bidirectional communication device between the power supplier and the consumer enables the implementation of the proposed model. Numerical simulations illustrating the interest of the proposed model are provided.

Optimal response of a thermal unit to an electricity spot market

This paper addresses the optimal response of a thermal unit to an electricity spot market. The objective is to maximize the unit profit from selling both energy and spinning reserve in the spot market. The paper proposes a 0/1 mixed-integer linear programming approach that allows a rigorous modeling of (i) nonconvex and nondifferentiable operating costs, (ii) exponential start-up costs, (iii) available spinning reserve taking into account ramp rate restrictions, and (iv) minimum up and down time constraints. This approach overcomes the modeling limitations of dynamic programming approaches and is computationally efficient. Results from realistic case studies are reported.

Economic Valuation of Reserves in Power Systems With High Penetration of Wind Power

This paper proposes a methodology to determine the required level of spinning and nonspinning reserves in a power system with a high penetration of wind power. The computation of the required reserve levels and their costs is achieved through a stochastic programming market-clearing model spanning a daily time horizon. This model considers the network constraints and takes into account the cost of both the load shedding and the wind spillage. The methodology proposed is illustrated using an example and a realistic case study. Some conclusions are finally drawn.

Market-clearing with stochastic security-part I: formulation

The first of this two-paper series formulates a stochastic security-constrained multi-period electricity market-clearing problem with unit commitment. The stochastic security criterion accounts for a pre-selected set of random generator and line outages with known historical failure rates and involuntary load shedding as optimization variables. Unlike the classical deterministic reserve-constrained unit commitment, here the reserve services are determined by economically penalizing the operation of the market by the expected load not served. The proposed formulation is a stochastic programming problem that optimizes, concurrently with the pre-contingency social welfare, the expected operating costs associated with the deployment of the reserves following the contingencies. This stochastic programming formulation is solved in the second companion paper using mixed-integer linear programming methods. Two cases are presented: a small transmission-constrained three-bus network scheduled over a horizon of four hours and the IEEE Reliability Test System scheduled over 24 h. The impact on the resulting generation and reserve schedules of transmission constraints and generation ramp limits, of demand-side reserve, of the value of load not served, and of the constitution of the pre-selected set of contingencies are assessed.

Transmission expansion planning: a mixed-integer LP approach

This paper presents a mixed-integer LP approach to the solution of the long-term transmission expansion planning problem. In general, this problem is large-scale, mixed-integer, nonlinear, and nonconvex. We derive a mixed-integer linear formulation that considers losses and guarantees convergence to optimality using existing optimization software. The proposed model is applied to Garvers 6-bus system, the IEEE Reliability Test System, and a realistic Brazilian system. Simulation results show the accuracy as well as the efficiency of the proposed solution technique.

Transmission loss allocation: a comparison of different practical algorithms

A pool-operated electricity market based on hourly auctions usually neglects network constraints and network losses while applying its market-clearing mechanism. This mechanism determines the accepted and unaccepted energy bids as well as the hourly market-clearing prices. As a result, ex post procedures are needed to resolve network congestions and to allocate transmission losses to generators and demands. This paper focuses on transmission loss allocation procedures and provides a detailed comparison of four alternative algorithms: pro rata, marginal allocation, unsubsidized marginal allocation, and proportional sharing. A case-study based on the IEEE RTS is provided. Different load scenarios covering a whole year are analyzed. Conclusions and recommendations are stated.

Electric Energy Systems : Analysis and Operation

Electric Energy Systems-An Overview I.J. Perez Arriaga, H. Rudnick, and M. Rivier Steady-State Single-Phase Models of Power System Components E. Handschin, A. F. Otero, and J. Cidras Load Flow A. Gomez-Exposito and F. L. Alvarado State Estimation A. Gomez-Exposito and A. Abur Economics of Electricity Generation F. D. Galiana and A. J. Conejo Optimal and Secure Operation of Transmission Systems J. L. Martinez Ramos and V. H. Quintana Three-Phase Linear and Nonlinear Models of Power System Components E. Acha and J. Usaola Fault Analysis and Protection Systems J. Cidras, J. F. Minambres, and F. L. Alvarado Frequency and Voltage Control G. Andersson, C. Alvarez Bel, and C. Canizares Angle, Voltage, and Frequency Stability C. Canizares, L. Rouco, and G. Andersson Three-Phase Power Flow and Harmonic Analysis W. Xu and J. G. Mayordomo Electromagnetic Transients Analysis J. A. Martinez-Velasco and J. Marti Appendix A: Solution of Linear Equation Systems F. L. Alvarado and Antonio Gomez-Exposito Appendix B:Mathematical Programming A. J. Conejo Appendix C:Dynamic Models of Electric Machines L. Rouco Index

Self-scheduling of a hydro producer in a pool-based electricity market

This paper addresses the self-scheduling of a hydro generating company in a pool-based electricity market. This company comprises several cascaded plants along a river basin. The objective is to maximize the profit of the company from selling energy in the day-ahead market. This paper proposes a 0/1 mixed-integer linear programming (LP) model to account, in every plant, for the nonlinear and nonconcave three dimensional relationship between the power produced, the water discharged and the head of the associated reservoir. Additionally, startup costs due mainly to the wear and tear are considered. Finally, different realistic case studies are analyzed in detail.

Multi-area coordinated decentralized DC optimal power flow

This paper provides a framework to carry out a multi-area optimal power flow in a coordinated decentralized fashion. A DC nonlinear optimal power flow model is used. Losses are incorporated through additional loads based on cosine approximations. The model makes it possible the independent optimal dispatch of each area while the global economical optimum of the whole electric energy system is achieved. This is possible by means of the Lagrangian relaxation decomposition procedure. Optimal energy pricing rates for the energy traded through the interconnections are derived. The developed algorithm can be run in parallel either to carry out numerical simulations or in an actual multi-area electric energy system.