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Article
Publication date: 13 September 2011

Binbin Xun, Fushuan Wen and Shulin Tong

The purpose of this paper is to investigate the gaming equilibrium among fossil‐fueled generation companies (GenCos), wind generation companies, the grid company and customers…

Abstract

Purpose

The purpose of this paper is to investigate the gaming equilibrium among fossil‐fueled generation companies (GenCos), wind generation companies, the grid company and customers participating in an emission trading (ET) market and the day‐ahead electricity market.

Design/methodology/approach

The complementarity method is used in this work to obtain the Nash equilibrium. By combining the Karush‐Kuhn‐Tucker (KKT) conditions of each kind of market participants with market clearing and consistency conditions, a mixed linear complementarity problem could be established.

Findings

Simulation results show that: the enforcement of ET could increase the share of generation outputs of wind generation units, and decrease the emissions from fossil‐fueled generation units; the bilateral contracts between GenCos and customers could limit the ability of exercising market power by GenCos; and when the emissions allowances allocated by the government shrink, the price of emissions allowance will increase and as the result the dispatching order of fossil‐fueled generation units will change, and the shares of generation outputs from wind generation units and combined‐cycle gas turbines increase. However, it should be mentioned that because the cost of wind generation is still very high, the increase of the share from wind generation units in the electricity market should mainly rely on cost reduction rather than the enforcement of ET.

Originality/value

The original contribution and the value of this study lie in developing a model framework to explore the gaming equilibrium that thermal and wind generating plants both play in the emissions trading environment and electricity market.

Article
Publication date: 23 November 2010

S. Subramanian and S. Ganesan

The purpose of this paper is to solve commitment problem of generating units in thermal power plants and to find the optimal dispatches of the committed units.

Abstract

Purpose

The purpose of this paper is to solve commitment problem of generating units in thermal power plants and to find the optimal dispatches of the committed units.

Design/methodology/approach

The unit commitment (UC) problem has been solved in two stages. In the first stage, the optimal units are identified using contribution factor. Initially, the generating units to be committed for each interval in the time horizon are obtained without considering the unit operational constraints such as minimum up time, minimum down time and initial state. Then the unit operational constraints are enforced and the optimal UC schedule is obtained. In the second stage, sequential approach with a matrix framework has been proposed to obtain the optimal dispatches of the committed units.

Findings

The simple methodologies have been developed for unit selection and to find the optimal dispatches of the committed units. The results of proposed methodology illustrate an improvement in the savings of total cost. The proposed approach is computationally efficient for solving large‐scale systems and successive UC problems.

Research limitations/implications

UC has a major role in electric thermal power plant operation. The problem with one day and one week scheduling horizon has a large potential of use, especially for small‐ and medium‐scale power systems. It reflects reality in a closer way and provides a more complete and realistic knowledge about the system in operation. The techniques developed for UC problem will provide a support to electric power companies for their economic operation and the concepts presented are useful in both graduate teaching and research to understand the UC problem.

Originality/value

The contribution of the paper is the simple methodologies which have been developed for unit selection and economic dispatch.

Details

International Journal of Energy Sector Management, vol. 4 no. 4
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 11 January 2021

Yerzhigit Bapin and Vasilios Zarikas

This study aims to introduce a methodology for optimal allocation of spinning reserves taking into account load, wind and solar generation by application of the univariate and…

Abstract

Purpose

This study aims to introduce a methodology for optimal allocation of spinning reserves taking into account load, wind and solar generation by application of the univariate and bivariate parametric models, conventional intra and inter-zonal spinning reserve capacity as well as demand response through utilization of capacity outage probability tables and the equivalent assisting unit approach.

Design/methodology/approach

The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern probability density function (PDF). The study also uses the Bayesian network (BN) algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

Findings

The results show that the utilization of bivariate wind prediction model along with reserve allocation adjustment algorithm improve reliability of the power grid by 2.66% and reduce the total system operating costs by 1.12%.

Originality/value

The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern PDF. The study also uses the BN algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

Article
Publication date: 28 June 2011

Yajvender Pal Verma and Ashwani Kumar

With the inclusion of significant wind power into the power system, the unit commitment (UC) has become challenging due to frequent variations in wind power, load and requirement…

Abstract

Purpose

With the inclusion of significant wind power into the power system, the unit commitment (UC) has become challenging due to frequent variations in wind power, load and requirement of reserves with sufficient ramp rate. The pumped storage units with lesser startup time and cost can take care of these sudden variations and reduce their impact on power system operation. The aim of this paper is to provide a solution model for UC problem in a hybrid power system.

Design/methodology/approach

The model developed has been implemented through GAMS optimization tool with CONOPT solver. The model has been called into MATLAB platform by using GAMS‐MATLAB interfacing to obtain solutions.

Findings

The model provides an efficient operating schedule for conventional units and pumped storage units to minimize operating cost and emission. The effects of wind power and load profiles on emission, operating cost and reserve with enough ramping capabilities have been minimized with the use of pumped storage unit. The commitment schedule of thermal and pumped storage units have been obtained with significant wind power integrated into the system for best cost commitment (BCC) and for a combined objective of cost and emission minimization.

Originality/value

This paper finds that the operating cost and emission in a commitment problem can be reduced significantly during variable wind and load conditions in a hybrid system. The model proposed provides operational schedules of conventional and pumped storage units with variable wind power and load conditions throughout operating horizon. The coordinated optimization approach has been implemented on a hybrid system with IEEE‐30 bus system.

Details

International Journal of Energy Sector Management, vol. 5 no. 2
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 1 June 2004

K.L. Lo and A.H. Hashim

A system operator (SO) of a transmission network consistently aims to minimise operating costs whilst still maintaining a certain degree of system adequacy. One of the ways to…

Abstract

A system operator (SO) of a transmission network consistently aims to minimise operating costs whilst still maintaining a certain degree of system adequacy. One of the ways to achieve this is by minimising the level of spinning reserve (SR) in the system. In order to do so, the level of SR must be analysed. This study looks at quantifying the risk of inadequacy when the SR is varied. A study was done for a period of 24 h with 30 m intervals to determine the risk level at each period. The number of generators despatched, system power margin and the system sell price was all taken into account. Risk was then computed by factoring the probability of generation inadequacy and the cost of purchasing the imbalance from the balancing market.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 23 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 22 November 2011

S. Subramanian, R. Anandhakumar and S. Ganesan

The purpose of this paper is to solve the maintenance management problems of generating units under the reliability criterion.

Abstract

Purpose

The purpose of this paper is to solve the maintenance management problems of generating units under the reliability criterion.

Design/methodology/approach

The problem has been formulated as a combinatorial optimization task, with explicit and simultaneous treatment of multiple objectives: maximization of reliability, minimization of fuel costs and minimization of constraint violations. This paper formulates a general generator maintenance management (GMM) problem using a reliability criterion and a novel bio‐inspired search technique, namely, artificial bee colony (ABC) algorithm is applied to determine the optimal generator maintenance schedule.

Findings

A novel meta‐heuristic search technique based algorithm has been developed to determine the optimal maintenance schedule of generating units to improve the system reliability.

Originality/value

The contribution of the paper is that an efficient bio‐inspired algorithm based solution technique has been developed to solve a very important problem for a power utility, i.e. the economical and reliable operation of a power system.

Article
Publication date: 5 June 2017

Janagaraman Radha, Srikrishna Subramanian, Sivarajan Ganesan and Manoharan Abirami

This study aims to minimize operating cost, adhere to pollution norms and maintain reserve and voltage levels subject to various operational concerns, including non linear…

Abstract

Purpose

This study aims to minimize operating cost, adhere to pollution norms and maintain reserve and voltage levels subject to various operational concerns, including non linear characteristics of generators and fuel limitation issues, which are useful for the current power system applications.

Design/methodology/approach

Improved control settings are required while considering multiple conflicting operational objectives that necessitate using the modern bio-inspired algorithm ant lion optimizer (ALO) as the main optimization tool. Fuzzy decision-making mechanism is incorporated in ALO to extract the best compromise solution (BCS) among set of non-dominated solutions.

Findings

The BCS records of IEEE-30 bus and JEAS-118 bus systems are updated in this work. Numerical simulation results comparison and comprehensive performance analysis justify the applicability of the intended algorithm to solve multi-objective dynamic optimal power flow (DOPF) problem over the state-of-art methods.

Originality/value

Optimal control settings are obtained for IEEE-30 and JEAS-118 bus systems with the objectives of minimizing fuel cost and emission in dynamic environment considering take-or-pay fuel contract issue. The fuzzy supported ALO (FSALO) is applied first time to solve the DOPF problem.

Details

International Journal of Energy Sector Management, vol. 11 no. 2
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 1 October 2018

Umamaheswari E., Ganesan S., Abirami M. and Subramanian S.

Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most…

Abstract

Purpose

Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues.

Design/methodology/approach

The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS.

Findings

As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique.

Originality/value

As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 9
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 January 2012

Frans Dijkhuizen, Willy Hermansson, Konstantinos Papastergiou, Georgios Demetriades and Rolf Grünbaum

This paper presents the world's first high voltage utility‐scale battery energy storage system in the multi megawatt range.

Abstract

Purpose

This paper presents the world's first high voltage utility‐scale battery energy storage system in the multi megawatt range.

Design/methodology/approach

The objectives are achieved by the series connection of switching semiconductor devices of the type Insulated Gate Bipolar Transistor (IGBT) and the series and parallel connection of Li‐ion batteries.

Findings

After tests at ABB laboratories, where its performance to specification was confirmed, a first pilot will be installed in the field, in EDF Energy Networks' distribution network in the United Kingdom during 2010 to demonstrate its capability under a variety of network conditions, including operation with nearby wind generation.

Practical implications

This holds the development of a distributed dc breaker, the diagnostics of detecting fault locations as well as fault isolation and the balancing of the batteries.

Originality/value

The paper presents the world's first high voltage utility‐scale battery energy storage system in the multi megawatt range suitable for a number of applications in today's and future transmission and distribution systems.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 31 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

Expert briefing
Publication date: 14 July 2017

Global reserves outlook.

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