Power dispatch and load control with generation uncertainty

Samadi, Pedram; Bahrami, Shahab; Wong, Vincent W. S.; Schober, Robert

doi:10.1109/globalsip.2015.7418373

Cited by 9 publications

(9 citation statements)

References 27 publications

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“…The main objective of this energy management is to meet the load demand while keeping the battery constraints such as SOC and discharge rate within the limits. In [14], an algorithm which reduced the generation cost while fulfilling load demand with fewer voltage variations at different nodes was proposed. Optimal energy management to find the minimum operating cost (OC) of grid-connected MG is presented in [15,16].…”

Section: Introductionmentioning

confidence: 99%

“…The main objective in many works related to this context focuses on solving economic dispatch problem for MG sources utilising batteries at a suitable location, which might not give optimal battery size. In [14][15][16], the location and size of the batteries were mostly found by taking into account the minimum cost of operation of MG. However, higher battery life with optimal CC was not considered during the planning stage of the BESS.…”

Section: Introductionmentioning

confidence: 99%

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Optimal battery and fuel cell operation for energy management strategy in MG

Jabir

Mokhlis

Muhammad

et al. 2019

IET Generation, Transmission & Distribution

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal battery and fuel cell operation for energy management strategy in MG

Jabir

Mokhlis

Muhammad

et al. 2019

IET Generation, Transmission & Distribution

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“…• Risk Evaluation: Inspired by the works in [23], [24], we deploy a penalty based on the conditional value-atrisk (CVaR) into the objective functions of the ISO's centralized problem and the generators' local problems to address the uncertainties of the renewable generation. It enables the generators with renewable plants to sell electricity and gain profit, while limiting the risk of high generation shortage within a certain confidence level.…”

Section: Introductionmentioning

confidence: 99%

A decentralized trading algorithm for an electricity market with generation uncertainty

Bahrami

Amini

2018

Applied Energy

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The uncertainties of the renewable generation units and the proliferation of price-responsive loads make it a challenge for independent system operators (ISOs) to manage the energy trading market in the future power systems. A centralized energy market is not practical for the ISOs due to the high computational burden and violating the privacy of different entities, i.e., load aggregators and generators. In this paper, we propose a dayahead decentralized energy trading algorithm for a grid with generation uncertainty. To address the privacy issues, the ISO determines some control signals using the Lagrange relaxation technique to motivate the entities towards an operating point that jointly optimize the cost of load aggregators and profit of the generators, as well as the risk of the generation shortage of the renewable resources. More, specifically, we deploy the concept of conditional-value-at-risk (CVaR) to minimize the risk of renewable generation shortage. The performance of the proposed algorithm is evaluated on an IEEE 30-bus test system. Results show that the proposed decentralized algorithm converges to the solution of the ISO's centralized problem in 45 iterations. It also benefits both the load aggregators by reducing their cost by 18% and the generators by increasing their profit by 17.1%.

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“…It considers the combination of a wind generation company and a hydro-generation company. Related power exchange modeling is discussed in [11,12], a closely related topic of power dispatching in operation and planning is presented in [13][14][15] while power networks control issues are presented in [16]. The [17] discusses the impact of joint bidding of wind power plant and a hydro generating unit on the wind farm revenue in a pool-based electricity market, considering the uncertainty of wind power prediction.…”

Section: Introductionmentioning

confidence: 99%

Duality Based Risk Mitigation Method for Construction of Joint Hydro-Wind Coordination Short-Run Marginal Cost Curves

et al. 2018

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This study analyzes the short-run hydro generation scheduling for the wind power differences from the contracted schedule. The approach for construction of the joint short-run marginal cost curve for the hydro-wind coordinated generation is proposed and applied on the real example. This joint short-run marginal cost curve is important for its participation in the energy markets and for economic feasibility assessment of such coordination. The approach credibly describes the short-run marginal costs which this coordination bears in "real life". The approach is based on the duality framework of a convex programming and as a novelty combines the shadow price of risk mitigation, which quantifies the hourly cost of mitigating risk, and the water shadow price, which quantifies the marginal cost of electricity production. The proposed approach is formulated as a stochastic linear program and tested on the case of the Vinodol hydropower system and the wind farm Vrataruša in Croatia. The result of the case study is a family of 24 joint short-run marginal cost curves. The proposed method is expected to be of great interest to investors as it enables risk mitigation for investors with diverse risk preferences, from risk-averse to risk-seeking.

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Power dispatch and load control with generation uncertainty

Cited by 9 publications

References 27 publications

Optimal battery and fuel cell operation for energy management strategy in MG

Optimal battery and fuel cell operation for energy management strategy in MG

A decentralized trading algorithm for an electricity market with generation uncertainty

Duality Based Risk Mitigation Method for Construction of Joint Hydro-Wind Coordination Short-Run Marginal Cost Curves

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