Customer choice of reliability in spinning reserve procurement and cost allocation using well-being analysis,” Elect

a b s t r a c t A novel pool-based market-clearing algorithm for spinning reserve (SR) procurement and the cost allocation associated with provision of spinning reserve among customers (DisCos) is developed in this paper. Rational buyer market model is used to clear energy and spinning reserve markets in the proposed algorithm. This market model gives DisCos the opportunity to declare their own energy requirement together with their desired reliability levels to the ISO and also they can participate in the SR market as a interruptible load. The DisCos' desired reliability levels are selected from a hybrid deterministic/probabilistic framework designated as the system well-being model. Using the demand of each DisCo and its associated desired reliability level, the overall desired system reliability level is determined. The market operator then purchases spinning reserve commodity from the associated market such that the overall desired system reliability level is satisfied. A methodology is developed in this paper to fairly allocate the cost associated with providing spinning reserve among DisCos based on their demands and desired reliability levels. An algorithm is also presented in this paper for implementing the proposed approach. The effectiveness of the proposed technique is examined using the IEEE-RTS

Day-ahead allocation of operation reserve in composite power systems with large-scale centralized wind farms

This paper focuses on the day-ahead allocation of operation reserve considering wind power prediction error and network transmission constraints in a composite power system. A two-level model that solves the allocation problem is presented. The upper model allocates operation reserve among subsystems from the economic point of view. In the upper model, transmission constraints of tielines are formulated to represent limited reserve support from the neighboring system due to wind power fluctuation. The lower model evaluates the system on the reserve schedule from the reliability point of view. In the lower model, the reliability evaluation of composite power system is performed by using Monte Carlo simulation in a multi-area system. Wind power prediction errors and tieline constraints are incorporated. The reserve requirements in the upper model are iteratively adjusted by the resulting reliability indices from the lower model. Thus, the reserve allocation is gradually optimized until the system achieves the balance between reliability and economy. A modified two-area reliability test system (RTS) is analyzed to demonstrate the validity of the method.This work was supported by National Natural Science Foundation of China (No. 51277141) and National High Technology Research and Development Program of China (863 Program) (No. 2011AA05A103)

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

A probabilistic spinning reserve market model considering DisCos different value of lost loads

In practice, some customers like industrial ones have higher value of involuntary lost load (VOLL) than other customers and thus, are willing to pay more for higher reliability levels than those with less VOLL, and consequently, they are more concerned with their individual load point reliability. Considering this fact, this paper proposes a new model, which makes distribution companies (DisCo)s able to select their reliability preferences by declaring their VOLLs. Based on the proposed model, firstly, a probabilistic security constraint unit commitment problem (SCUC) is used to clear energy and spinning reserve markets simultaneously in order to determine system spinning reserve requirement in this paper. Also, the expected load interruption costs of DisCos are incorporated in the SCUC objective function. Secondly, a new cost allocation method is proposed to evaluate each DisCo's reserve cost, and finally, in the case that an outage happens in the system, a relevant approach is proposed to assess each DisCo's share of that outage such that each DisCo's reliability preference is fulfilled. IEEE reliability test system (IEEE-RTS) is used to demonstrate the effectiveness of the presented model. (C) 2010 Elsevier B.V. All rights reserved

A probabilistic joint energy and spinning reserve market model

Both deterministic and probabilistic approaches can be used to establish spinning reserve requirements. It has been proved that determining reserve requirements based on probabilistic approaches results in more economical efficiency. So, a probabilistic security constraint unit commitment problem (SCUC) is used to clear energy and spinning reserve simultaneously and to determine system spinning reserve requirement in this paper. Also, the expected load interruption costs of DisCos are incorporated in the SCUC objective function. IEEE reliability test system (IEEE-RTS) is used to demonstrate the presented model

Reactive power reserve management ::Preventive countermeasure for improving voltage stability margin

Voltage stability imposes important limitations on the power systems operation. The system should be operated with an adequate voltage stability margin by the appropriate scheduling of reactive power resources and voltage profile. The main countermeasures against voltage instability are distinctly classified into preventive and corrective control actions. The management of the reactive power generation and its reserve are the main preventive actions against voltage instability. In this paper a Benders’ decomposition method is proposed to improve the voltage stability margin through management of reactive power and its reserve. The voltage and reactive power management is studied from the generator’s point of view which so far less attention is paid rather than the load’s perspective. The proposed optimization procedure is applied on 6 bus test system to illustrate the effectiveness of the method

Reactive power reserve management: Preventive countermeasure for improving voltage stability margin

Voltage stability imposes important limitations on the power systems operation. The system should be operated with an adequate voltage stability margin by the appropriate scheduling of reactive power resources and voltage profile. The main countermeasures against voltage instability are distinctly classified into preventive and corrective control actions. The management of the reactive power generation and its reserve are the main preventive actions against voltage instability. In this paper a Benders' decomposition method is proposed to improve the voltage stability margin through management of reactive power and its reserve. The voltage and reactive power management is studied from the generator's point of view which so far less attention is paid rather than the load's perspective. The proposed optimization procedure is applied on 6 bus test system to illustrate the effectiveness of the method