Optimizing Spinning Reserve Requirement of Power System With Carbon Capture Plants

Lou, Suhua; Lu, Siyu; Wu, Yaowu; Kirschen, Daniel S.

doi:10.1109/tpwrs.2014.2341691

Cited by 39 publications

(16 citation statements)

References 11 publications

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“…From the above equations (4) and (10)- (11), and the equations (27), (30)- (32), and (35)- (40) shown in Appendix A, the model of i-th DG can be rewritten into a matrix formation as…”

Section: B the Design Of Pdga Combined With Nonlinear Dg Modelmentioning

confidence: 99%

“…From the perspective of control method, the angle and amplitude deviations between Main-Grid and Energy Internet are within a small range all the time, thus Energy Internet can be connected to the Main-Grid at any time. Furthermore, various methods on the optimization of spinning reserve condition have also been investigated in [38], [39] and [40], which is out the scope of this paper.…”

Section: A Graph Theorymentioning

confidence: 99%

See 1 more Smart Citation

A Multiagent-Based Consensus Algorithm for Distributed Coordinated Control of Distributed Generators in the Energy Internet

Sun

Han

Zhang

et al. 2015

IEEE Trans. Smart Grid

369

133

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“…From the above equations (4) and (10)- (11), and the equations (27), (30)- (32), and (35)- (40) shown in Appendix A, the model of i-th DG can be rewritten into a matrix formation as…”

Section: B the Design Of Pdga Combined With Nonlinear Dg Modelmentioning

confidence: 99%

Section: A Graph Theorymentioning

confidence: 99%

A Multiagent-Based Consensus Algorithm for Distributed Coordinated Control of Distributed Generators in the Energy Internet

Sun

Han

Zhang

et al. 2015

IEEE Trans. Smart Grid

369

133

View full text Add to dashboard Cite

show abstract

“…Analogously, the conditional expression of Equation (12) can be equivalent to the linear constraints that…”

Section: Discretization Of the Load Forecast Errormentioning

confidence: 99%

“…Sustainability 2017, 9, 758 2 of 20 with a certain proportion of the forecast load or the maximum capacity of the operating units. This deterministic means has left out multiple uncertainties, such as the wind forecast error, the load forecast error, and the forced outage rate of units [12,13]. During recent years, the stochastic assessment of the spinning reserve has been applied in many articles [14][15][16].…”

mentioning

confidence: 99%

An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability

Ding

Zheng

2017

Sustainability

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Demand response (DR) has become an impressive option in the deregulated power system due to its features of availability, quickness and applicability. In this paper, a novel economic dispatch model integrated with wind power is proposed, where incentive-based DR and reliability measures are taken into account. Compared with the conventional models, the proposed model considers customers' power consumption response to the incentive price. The load profile is optimized with DR to depress the influence on the dispatch caused by the anti-peak-shaving and intermittence of wind generation. Furthermore, a probabilistic formulation is established to calculate the expected energy not supplied (EENS). This approach combines the probability distribution of the forecast errors of load and wind power, as well as the outage replacement rates of units into consideration. The cost of EENS is added into the objective to achieve an optimal equilibrium point between economy and reliability of power system operation. The proposed model is solved by mixed integer linear programming (MILP). The applicability and effectiveness of this model is illustrated by numerical simulations tested on the IEEE 24-bus Reliability Test System. Sustainability 2017, 9, 758 2 of 20 with a certain proportion of the forecast load or the maximum capacity of the operating units. This deterministic means has left out multiple uncertainties, such as the wind forecast error, the load forecast error, and the forced outage rate of units [12,13]. During recent years, the stochastic assessment of the spinning reserve has been applied in many articles [14][15][16]. With this approach, the spinning reserve is optimized to satisfy the expected energy not supplied (EENS). In [17], a triangular approximate distribution model is used to quantify EENS due to the stochastic feature of wind. Then, a security-constrained unit commitment algorithm is proposed to schedule conventional units and wind generation considering probabilistic forecast models of wind power. Another day-head scheduling model involving reliability criteria is described in [18]. EENS is calculated with the historical outage replacement rates of generators or lines. MILP is utilized to deal with the proposed model. In [19], the forecast errors of both wind power and load are supposed to follow normal distributions. These errors are discretized into several intervals for a new formulation of reliability measures. In [20,21], a two-stage stochastic problem is formulated to address various uncertainties in the system, such as wind power, solar generation, loads and even electric vehicles. The sample average approximation, which is a Monte Carlo simulation technique, is utilized to deal with uncertainties for scenario generation purposes. These works have integrated the system with distribution-free uncertainties, but given a rise to the computational burden.As an effective way for peak load shedding and shaving, DR has been widely investigated in the electricity market. Consuming wind power with DR will re...

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“…However, low-carbon generation technologies, such as nuclear and CCS, may be designed or financed to be technically and/or commercially inflexible. Several studies have proposed unit commitment formulations with CCS equipped power plants [12], [13]. However, CCS power plants have their own operational characteristics and have the capability to respond dynamically to market prices by adjusting the CO2 capture rate.…”

Section: Take Down Policymentioning

confidence: 99%

Operational Flexibility of Future Generation Portfolios Using High Spatial- and Temporal-Resolution Wind Data

Bruce

Gibbins

Harrison

et al. 2016

IEEE Trans. Sustain. Energy

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Optimizing Spinning Reserve Requirement of Power System With Carbon Capture Plants

Cited by 39 publications

References 11 publications

A Multiagent-Based Consensus Algorithm for Distributed Coordinated Control of Distributed Generators in the Energy Internet

A Multiagent-Based Consensus Algorithm for Distributed Coordinated Control of Distributed Generators in the Energy Internet

An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability

Operational Flexibility of Future Generation Portfolios Using High Spatial- and Temporal-Resolution Wind Data

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