Joint Energy and Spinning Reserve Market Clearing Incorporating Wind Power and Load Forecast Uncertainties

Reddy, S. Surender; Bijwe, P.R.; Abhyankar, A. R.

doi:10.1109/jsyst.2013.2272236

Cited by 111 publications

(63 citation statements)

References 48 publications

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“…In a competitive electricity market, the suppliers can offer both energy and spinning reserves through bids; consumers can consume energy, and can offer reserves. The problem considering demand response/demand-side reserve (DR) offers option, with conventional thermal generators and wind energy generators, is formulated as [34,35]: Minimize,…”

Section: Study 3: Scheduling Energy and Srs In A Wind-thermal Power Smentioning

confidence: 99%

Optimal scheduling of wind-thermal power system using clustered adaptive teaching learning based optimization

Reddy

2016

Electr Eng

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This paper proposes an optimal scheduling/ allocation of energy and spinning reserves for a wind-thermal power system. There is a considerable need for the renewable energy resources in the modern power system; therefore, in this paper, wind energy generators are used. Here, two different market clearing models are proposed. One model includes reserve offers from the conventional thermal generators, and the other includes reserve offers from both thermal generators, and demand/consumers. The stochastic behavior of wind speed and wind power generation is represented by the Weibull probability density function. The objective function considered in this paper includes cost of energy provided by conventional thermal and wind generators, cost of reserves provided by conventional thermal generators and load demands. It also includes costs due to under-estimation and over-estimation of available wind power generation. Clustered adaptive teaching learning based optimization algorithm is used to solve the proposed optimal scheduling problem for both conventional and wind-thermal power systems considering the provision for spinning reserves. To show the effectiveness and feasibility of the proposed frame work, various case studies are presented for two different test systems.

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“…In this model, reserves are supplied by only conventional thermal generators [22]. The objective function in Model 1 is formulated as [22,23], Minimize,…”

Section: Model 1 (Only Conventional Thermal Generators Will Supply Rementioning

confidence: 99%

“…Generator constraints The power output of each thermal generator is restricted by their minimum, maximum limits and generator ramp rate constraints (GRC) [22].…”

Section: Total Spinning Reserve (Tsr) Requirement Constraintsmentioning

confidence: 99%

Optimum day-ahead clearing of energy and reserve markets with wind power generation using anticipated real-time adjustment costs

Reddy

Bijwe

Abhyankar

2015

International Journal of Electrical Power & Energy Systems

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“…Taking both system economy and reliability into consideration, Literature [7] propose a conditional value-at-risk-based optimal spinning reserve model and incorporate it into the generation scheduling model in wind power integrated systems, in order to minimize total generation cost. Considering uncertainties in wind power and load forecasts, a multi-objective energy and spinning reserve scheduling method for a wind-thermal power system is investigated in a market environment [8]. Cobos, et al [9] establishes a mathematical optimization model for the minimum cost of conventional generators and spinning reserve, and then adopts a robust linear optimization to get the optimal reserve capacity with the wind uncertainty, so as to guarantee the feasibility of the optional solutions for all the realizations of the uncertain data.…”

Section: Introductionmentioning

confidence: 99%

Spinning Reserve Capacity Optimization of a Power System When Considering Wind Speed Correlation

Zhang

Zhuang

Zhang

et al. 2018

ASI

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Usually, the optimal spinning reserve is studied by considering the balance between the economy and reliability of a power system. However, the uncertainties from the errors of load and wind power output forecasting have seldom been considered. In this paper, the optimal spinning reserve capacity of a power grid considering the wind speed correlation is investigated by Nataf transformation. According to the cost-benefit analysis method, the objective function for describing the optimal spinning reserve capacity is established, which considers the power cost, reserve cost, and expected cost of power outages. The model was solved by the quantum-behaved particle swarm optimization (QPSO) algorithm, based on stochastic simulation. Furthermore, the impact of the related factors on the optimal spinning reserve capacity is analyzed by a test system. From the simulation results, the model and algorithm are proved to be feasible. The method provided in this paper offers a useful tool for the dispatcher when increasing wind energy is integrated into power systems.

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“…In the early years of electricity market, energy and ancillary services used to be settled in separate markets; however, there is wide consensus today that energy and reserve should be o ered and cleared simultaneously in integrated markets to minimize the overall cost of supplying energy and provision of reserve [14]. In recent years, various papers have dealt with the simultaneous settlement of energy and Spinning Reserve (SR) [15][16][17][18][19]. In [18] a thorough literature review on joint energy and reserve markets modeling is presented.…”

Section: Introductionmentioning

confidence: 99%

A New Solution Approach for Supply Function Equilibrium-based Bidding Strategy in Electricity Markets

Hematabadi

Foroud

2017

Scientia Iranica

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Abstract. This paper presents a new analytical solution method for Supply FunctionEquilibrium-based (SFE) bidding strategy in electricity markets. It is assumed that every Generation Company (GenCo) has some generation units and bids a Linear Supply Function (LSF) for each of its units to the Independent System Operator (ISO). The problem is modeled as a bi-level optimization problem; in the inner level, ISO clears the market to maximize social welfare; in the outer level, each GenCo tries to maximize its individual welfare. The proposed method is used to solve the outer-level problem using an iterative algorithm, in which LSF coe cients are parameterized. The formulation is developed for both elastic and non-elastic demands for single-and multi-generator cases and also for integrated energy and Spinning Reserve (SR) markets with three models of competitions: a-, b-, and k-parameterization. Three sample networks are used to evaluate the proposed method. The results show that the proposed method is e ective and accurate for GenCos' strategic bidding in electricity markets compared with other optimization algorithms.

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Joint Energy and Spinning Reserve Market Clearing Incorporating Wind Power and Load Forecast Uncertainties

Cited by 111 publications

References 48 publications

Optimal scheduling of wind-thermal power system using clustered adaptive teaching learning based optimization

Optimum day-ahead clearing of energy and reserve markets with wind power generation using anticipated real-time adjustment costs

Spinning Reserve Capacity Optimization of a Power System When Considering Wind Speed Correlation

A New Solution Approach for Supply Function Equilibrium-based Bidding Strategy in Electricity Markets

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