Multi-transactions ATC determination using PTDF based approach in deregulated markets

In recent years, an increased interest was devoted to the problem of flexible AC transmission system devices location. In literature, most of proposals consist in iterative analyses, exhaustively looking for the branch that maximizes or minimizes an objective, such as least transmission losses or best power transfer capability. In this paper, attention is particularly focused on the static synchronous series compensator and a method is proposed to determine the device best location that maximizes the power system available transfer capability measured as the maximum system load increase before any operating limit is reached. The proposed method always performs an exhaustive analysis although conducted by modelling the transmission network by means of the simplified DC load flow equations embedded within an opportune optimisation model. Tests carried on networks modelled also by means of the AC load flow representation have demonstrated the validity of the proposed DC load flow based method

The existing power market is contentiously promoting sustainability and competitiveness in the electricity industry. It has raised the transmission networks' transfer capacity as an emerging area for researchers. The electricity production units and consumers share the same transmission network. All stakeholders try to generate power from cheaper sources to make more significant profit margins. This situation creates transmission congestion, violation of voltage and thermal limits, and system security threats. The accurate measurement and optimal use of the available transfer capability (ATC) shall resolve this issue up to some extent. Thus, efficient evaluation of ATC is needed to ensure system security, and it provides an open and trending research topic. This article presents a review of the various techniques for ATC determination and provides the characteristics, practices, and features of the methods. This analysis demonstrates the issues of ATC evaluation techniques and provides the research areas to the researchers.

In a new competitive electricity market, accurate information should be shared to provide nondiscriminatory access to all participants. Key information to determine how much power can be shipped through the network is dubbed available transfer capability (ATC). This paper presents a methodology for the calculation of ATC, which is performed through a fuzzy logic approach to parallelizing contingency constrained optimal power flow (CCOPF). This algorithm may be used by utilities to optimize economy interchange for severe contingencies analyzed without disclosing details of their operating cost to competitors. In fact, the main objective of fuzzy multi-objective CCOPF is to determine the minimization of both the base-case (pre-contingency) operating cost and the post-contingency correction times as conflicting but fuzzy goals. Also, Benders decomposition is adopted to partition the fuzzy formulation with contingency constraints, which allows for post-contingency corrective rescheduling, motivated by the improvement of the computational efficiency using parallel processing. The IEEE-30 bus system is employed to test the proposed algorithm and the results are comprehensively demonstrated by a distinct comparison between the conventional optimal power flow and the CCOPF with respect to the same array of transactions, base-case, and generation/line outages.

The unified power flow controller (UPFC) integrates properties of both shunt and series compensations and can effectively alter power system parameters in a way that increases power transfer capability and stabilizes the system. This paper presents an approximate model for power flow studies that takes into consideration modeling of lossless UPFC-embedded transmission lines including the effect of line charging susceptance. The approximate model is then simplified to a dc load flow model that takes into account the modeling of the UPFC. The equations derived in this paper are applied to an optimal power flow of a small test system, where the results obtained by approximate load flow method are compared to those of dc load flow method. The results presented in the paper show valuable impacts of putting UPFC in service on out-of-merit costs and locational marginal prices (LMPs) in a restructured power system environment. The results show that the dc load flow relations can be modified to reflect the effects of the UPFC. In addition, results show that UPFC may reduce generation out-of-merit costs and let LMPs regain uniformity.

Integration of wind power into the competitive electricity market presents challenges to power system planners and operators. It is not possible for wind generators to bid into the competitive electricity market due to high cost and intermittent nature of available power. This paper analyses and proposes the pricing mechanism for wind power in the competitive electricity market. The both demand and supply side bidding scenarios with case studies are presented in the paper. The impact of wind power in market mechanism such as market collusion, ancillary series and market power are also discussed. This paper could be guide line for the policy makers and market operators to promote the wind power with system reliability and security.

An efficient contingency evaluation method for power system security analysis

Improvements on the line outage distribution factor for power system security analysis

In a competitive electricity market, the most important tasks of congestion management requires the Independent System Operator (ISO) to identify and relieve congestion as it threatens system security and may cause rise in electricity price resulting in market inefficiency. In corrective action of congestion management schemes, it is crucial for ISO to select the most sensitive generators to re-schedule their optimal real and reactive powers in congestion management. As the real and reactive power dispatches play a vital role to relieve the congestion at low congestion cost, in this paper, the reactive support of generators, in addition to the rescheduling of real power generation, has been considered to manage congestion. The re-dispatch of transactions for congestion management in a pool model is formulated as a Nonlinear Programming (NLP). This paper proposed Fitness Distance Ratio Particle Swarm Optimization based Optimal Power Flow (FDRPSO-OPF) to solve the NLP. The Conventional PSO (CPSO) oscillate in damped sinusoidal waves until they converge to points in between their previous pBest and gBest positions which prevent the particles from effective search for the global optimum. To overcome this problem the FDRPSO has been used in this paper. The proposed method has been tested on a practical 75-bus Indian System and 39-bus New England System for single line congestion case and the results are compared with Conventional PSO (CPSO), Binary Coded Genetic Algorithm (BCGA) and Real Coded Genetic Algorithm (RCGA) based OPF methods. (6 pages)

This paper presents several techniques for recovering cost function estimates for electricity generation from a model of optimal bidding behavior in a competitive electricity market. Two techniques are developed based on different models of the price-setting process in a competitive electricity market. The first assumes that the firm is able to choose the price that maximizes its realized profits given the bids of its competitors and the realization of market demand. This procedure is straightforward to apply, but does not impose all of the market rules on the assumed price-setting process. The second procedure uses the assumption that the firm bids to maximize its expected profits. This procedure is considerably more complex, but can yield more insights about the nature of the firm's variable costs, because it allows the researcher to recover generation unit-level variable cost functions. These techniques are applied to bid, market outcomes and financial hedge contract data obtained from the first three months of operation of the National Electricity Market (NEM1) in Australia. The empirical analysis illustrates the usefulness of these techniques in measuring actual market power and the ability to exercise market power possessed by generation unit owners in competitive electricity markets.

In deregulated electricity market, most of the power transferred through the wheeling transaction. Hence, it is very important and necessary to determine the transfer capability of the transmission system before the power dispatch. Series FACTS devices such as Thyristor controlled series compensators (TCSC), with its ability to directly control the power flow can be very effective to total transfer capability of transmission network. Proper location of TCSC plays key role in improving total transfer capability (TTC). From the viewpoint, this paper focuses on the evaluation of the impact of TCSC on TTC via optimal location. Evaluation total transfer capability using TCSC requires a two-step approach. First, the optimal location of the TCSC in the network must be ascertained by Min cut algorithm and then, the mathematical formulation of TTC using Repeated Power Flow (RPF) with fixed TCSC parameters is solved. The proposed method is tested and validated for locating TCSC in IEEE 14-, IEEE-30 bus test systems. Results show that the proposed method is capable of finding the best location for TCSC installation to improve total transfer capability.KeywordsDeregulated power systemFACTSTCSCRPFTTC

A problem of concern in the deregulated electricity market is to obtain a global power quality (PQ) index for the supply and load side to estimate the cost of PQ in order to include it in the contracts between customers and utility companies. Existing PQ indices are usually isolated and lack the cost impact of bad PQ. This study presents an intelligent method based on artificial neural network (ANN) and fuzzy logic to obtain a quantitative global index for PQ evaluation and pricing in competitive electricity market. Taking into account the cost of PQ phenomena with their relative weights in this index, it can be used as a PQ measure in electricity tariffs by utility companies. Although individual cost assignments used in this study are subject to approximation, once the assignments are made, the calculation is consistent and gives a useful and unique measure of quality of electricity for both supply side and customer side. The proposed algorithm has been implemented on real measured data of a distribution network. The results show the capability of this method to obtain an accurate measure for PQ evaluation and pricing.

India is on the path of rapid economic growth along with speedy overall development, simultaneously it has to face the global threat of climate change. India has unique renewable energy resources (RES) and development of country depends to a great extent on harnessing these sources. Being a developing infrastructure, increasing energy needs, eradicating poverty, and social development are the overriding priorities before India. These have to be achieved without compromising on the environment and maintaining ecological balance alongside. Maintaining a high growth rate is a necessity for India. This poses a formidable challenge but is perceived to be a great opportunity for the country to increase the share of renewable in the overall energy mix. For India to meet its power demand in a responsible, sustainable and eco-friendly manner there is urgent need to promote renewable. Hence current status, various issues, regulatory policies and incentives for promotion of renewable energy sources in competitive electricity market are discussed in this paper. This will make renewable more attractive in the future electricity market.

Wind power is one of the most rapidly growing clean and renewable energy sources. However, due to the uncertainty and intermittency of wind power, the increasing penetration of wind power into the electric power system will pose challenges to power system operators. Moreover, as a participant in a competitive electricity market, a wind power producer's behavior and profit will be influenced by other participants' behaviors. This paper proposes a model of using stochastic programming to generate optimal bidding strategies to maximize the total profits of wind and conventional power producers in both the energy market and a bilateral reserve market, where the reserve price is settled between wind and conventional power producers by using game theory. Case studies using real-world data for games in an electricity market with different types of players are performed to show the effectiveness of the proposed model.

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.

Chapter 11 - Texas: The Most Robust Competitive Market in North America