Optimal DR and ESS Scheduling for Distribution Losses Payments Minimization Under Electricity Price Uncertainty

Soroudi, Alireza; Siano, Pierluigi; Keane, Andrew

doi:10.1109/tsg.2015.2453017

Cited by 134 publications

(83 citation statements)

References 51 publications

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“…Thus, the EDNs demanded power will possess more flexibility and controllability in a smart grid. Herein, demand response (DR) programs have been suggested to be implemented in EDNs …”

Section: Introductionmentioning

confidence: 99%

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A stochastic formulation for distribution automation planning incorporating emergency demand response programs

Mohammadi

Soleymani

Mozafari

et al. 2019

Int Trans Electr Energ Syst

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Summary Advanced distribution automation (ADA) is a vital basis of the smart grid, which leads to enhancement of reliability level. Moreover, demand response programs are highly proposed to be employed in the smart grid. In this paper, a cross‐sectional benefit of smart grid maturity model is proposed in which the emergency demand response programs (EDRPs) are considered in the ADA planning problem. In fact, the role of EDRPs is considered in the service restoration process that affects the ADA plan. The service restoration process possesses several uncertain parameters including the demanded power of customers during service restoration, which are considered in the proposed formulation for ADA planning. The objective function of the optimization problem includes various costs imposed to the distribution system operator due to contingency occurrence including the expected total customer interruption cost, total investment cost of automatic sectionalizing switches, circuit breakers, and fuses deployment, and the total expected cost of implementing EDRP programs in the service restoration. The presented ADA planning methodology is tested on the fourth bus number of Roy Bilinton test system (RBTS4) to investigate its effectiveness.

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“…Thus, the EDNs demanded power will possess more flexibility and controllability in a smart grid. Herein, demand response (DR) programs have been suggested to be implemented in EDNs …”

Section: Introductionmentioning

confidence: 99%

“…In recent years, several remarkable efforts have been conducted in order to utilize the benefits of DR programs in EDNs operation and planning . Balijepalli et al presented a comprehensive review of different advantages of executing DR programs for EDNs.…”

Section: Introductionmentioning

confidence: 99%

A stochastic formulation for distribution automation planning incorporating emergency demand response programs

Mohammadi

Soleymani

Mozafari

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

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“…With the advent of smart grid infrastructure, ESS plays an indispensable role in diverse areas, and this is why many researchers have investigated its applications with interest. DR can be used with ESS to minimize the losses payments in distribution networks under the condition that electricity price has uncertainty [9]. The authors in [10] implemented a scheduling optimization with DR to reduce the influence of wind power uncertainty in power systems.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost

Choi

Hongseok

2016

Energies

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A self-sustainable base station (BS) where renewable resources and energy storage system (ESS) are interoperably utilized as power sources is a promising approach to save energy and operational cost in communication networks. However, high battery price and low utilization of ESS intended for uninterruptible power supply (UPS) necessitates active utilization of ESS. This paper proposes a multi-functional framework of ESS using dynamic programming (DP) for realizing a sustainable BS. We develop an optimal charging and discharging scheduling algorithm considering a detailed battery wear-out model to minimize operational cost as well as to prolong battery lifetime. Our approach significantly reduces total cost compared to the conventional method that does not consider battery wear-out. Extensive experiments for several scenarios exhibit that total cost is reduced by up to 70.6% while battery wear-out is also reduced by 53.6%. The virtue of the proposed framework is its wide applicability beyond sustainable BS and thus can be also used for other types of load in principle.

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“…At the real-time stage, a multiagent-based gametheoretic reverse auction model is presented in [17] for MG market operations. Considering the uncertainties of market prices, the loss payment is minimized in [18] by scheduling DR and energy storage system (ESS). To maximize the profit of a commercial virtual power plant (CVPP), a three-stage stochastic bilevel model is used to make offering strategies on the basis of various DERs and storages [19].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Trading Strategies of Proactive DISCO with Heterogeneous DG Owners

Zhang¹,

Wang

et al. 2016

IEEE Trans. Smart Grid

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Abstract-This paper presents a methodology to obtain the optimal trading strategies between the proactive distribution company (PDISCO), heterogeneous distributed generation owners (DGOs) and wholesale market in a real-time trading framework. In this framework, the PDISCO's decisions cover the power procurements from DGOs and the transactions within the real-time market. A one-leader multi-follower-type bilevel model is proposed to embody the PDISCO-DGO gaming structure. The upper-level (UL) problem is to maximize the PDISCO's profit, while the lower-level (LL) problem indicates the profit maximization per DGO. Since the UL problem is non-linear and non-convex and the LL problems are linear and convex, we reformulate the proposed model to a solvable mathematical program with equilibrium constraints (MPEC) by an equivalent primal-dual approach. The numerical results of the case studies show the effectiveness and scalability of the proposed model. Mapping of the set of DGs and SDs onto the set of DGOs. NOMENCLATURE Sets and IndicesBidding price and generation quantity of respective Type1,2,3 DGOs at time t .Active and reactive power generated by respective Type1,2,3 DGOs at time t for scenario ω. P Reactive power supplied by the shunt compensator at bus i at time t for scenario ω. P f t,ij,ω , Q f t,ij,ω Active and reactive power flows through feeder ij at time t for scenario ω. e tiω , δ tiω Voltage magnitude and phase angle at bus i at time t for scenario ω. Profit guarantee factor of the DGO of Type1,2,3 respectively at time t.

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Optimal DR and ESS Scheduling for Distribution Losses Payments Minimization Under Electricity Price Uncertainty

Cited by 134 publications

References 51 publications

A stochastic formulation for distribution automation planning incorporating emergency demand response programs

A stochastic formulation for distribution automation planning incorporating emergency demand response programs

Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost

Real-Time Trading Strategies of Proactive DISCO with Heterogeneous DG Owners

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