Coordination of EVs Participation for Load Frequency Control in Isolated Microgrids

Vahedipour‐Dahraie, Mostafa; Rashidizaheh-Kermani, Homa; Najafi, Hamidreza; Anvari‐Moghaddam, Amjad; Guerrero, Josep M.

doi:10.3390/app7060539

Cited by 49 publications

(32 citation statements)

References 23 publications

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“…The last term is the switching cost which includes the number of switching actions and switching cost per action. The quadratic active power loss term in Equation (3) can be revised into a linear format by utilizing piecewise linearization techniques proposed in [28,29].…”

Section: Problem Formulationmentioning

confidence: 99%

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

et al. 2018

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Due to the recent developments in the practical implementation of remotely controlled switches (RCSs) in the smart distribution system infrastructure, distribution system operators face operational challenges in the hourly reconfigurable environment. This paper develops a stochastic Model Predictive Control (MPC) framework for operational scheduling of distribution systems with dynamic and adaptive hourly reconfiguration. The effect of coordinated integration of energy storage systems and demand response programs through hourly reconfiguration on the total costs (including cost of total loss, switching cost, cost of bilateral contract with power generation owners and responsive loads, and cost of exchanging power with the wholesale market) is investigated. A novel Switching Index (SI) based on the RCS ages and critical points in the network along with the maximum number of switching actions is introduced. Due to nonlinear nature of the problem and several existing binary variables, it is basically considered as a Mixed Integer Non-Linear Programming (MINLP) problem, which is transformed into a Mixed Integer Linear Programming (MILP) problem. The satisfactory performance of the proposed model is demonstrated through its application on a modified IEEE 33-bus distribution system.

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Section: Problem Formulationmentioning

confidence: 99%

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

et al. 2018

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“…Therefore, to properly balance power generation and consumption, efficient mechanisms for reliable system operation in the presence of uncertainties imposed by stochastic behavior of energy sources is needed. With active participation of end-use consumers in demand response (DR) programs, it is very probable to compensate power mismatch in an islanded MG [7]- [8]. The positive impact of DR on the operation and costs of MGs has been studied in the literature [8]- [13].…”

Section: Ns T I R mentioning

confidence: 99%

Optimal scheduling of distributed energy resources and responsive loads in islanded microgrids considering voltage and frequency security constraints

Vahedipour‐Dahraie

Najafi

Anvari‐Moghaddam

et al. 2018

Journal of Renewable and Sustainable Energy

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Low inertia of distributed energy resources (DERs), high penetration levels of renewable energy sources (RESs) and load demand variations put the islanded microgrids (MGs) security at risk of instability. This paper proposes a twostage stochastic model for coordination of DERs and responsive loads in islanded MGs with regard to voltage and frequency security constraints. Based on the proposed model, scheduling of the controllable units in both supply and demand sides is done in a way not only to maximize the expected profit of MG operator (MGO), but also to minimize the energy payments of customers under the premise of security and stability of MG. An AC optimal power flow (AC-OPF) procedure is also used to study operating condition of the system under uncertainties and to guarantee acceptable nodal voltages and system frequency during different scenarios. The proposed stochastic optimization model is then applied to a typical autonomous MG and its effectiveness is demonstrated through different scenarios under uncertainties in load consumption and renewable energy resources (RESs) productions. Simulation results demonstrate that customers' participation in DR programs have significant effect on the system's performance in terms of voltage and frequency stability. Moreover, optimal coordination of DERs and responsive loads can increase the expected profit of MGO significantly. The effectiveness of the proposed scheduling approach is verified on an islanded MG test system over a 24-h period.Index Terms-Demand response (DR), microgrid (MG), distributed energy resource (DER), voltage and frequency security, renewable energy sources (RESs). DR t j D BIncome of group j of customer at period t after implementing DR programs. ,t j BIncome of group j of customer at period t when the demand is at nominal value. Energy bid submitted by wind unit w (PV v) in period t (cents/kWh).Bid of the up (down)-spinning reserve submitted by DG i in period t (cents/kWh).Bid of the non-spinning reserve submitted by DG i in period t (cents/kWh).Bid of the up (down)-spinning reserve submitted by load j in period t (cents/kWh).Demand of load j in period t (and scenario s) (kW).Demand of load group j after implementing DR programs in period t (kW).Self-elasticity (Cross-elasticity) of load group j. LFMaximum power flow from node n to r (kW). 2I. Introduction Recently, microgrid (MG) idea has been introduced to transform the conventional power systems to a more reliable, economic and environmentally friendly system. The diversified load consumption pattern and availability of power from green distributed energy resources (DERs) cause supply-demand mismatch in MGs. Optimal operation of MGs both technically and economically mainly relies on the coordination between different components including DERs, energy storage systems (ESSs), and responsive loads [1]- [2]. In grid-connected MGs, normally the economic operation is the main objective as there is a stiff-grid on upstream to support the system frequency and voltage at the point of ...

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“…The non-anticipativity is expressed in (7). The limitation for the energy traded in the positive and negative balancing market is represented in (8) and (9), respectively.…”

Section: Upper Level: Aggregator's Viewpointmentioning

confidence: 99%

“…In [6], the impact of the market price and reserve market uncertainties via a stochastic programming structure is expressed to obtain the EV scheduling problem. Integrated scheduling of EVs and renewable resources in a microgrid is investigated in [7] in order to control the intermittency of renewable energy generations through the stored energy in EVs' batteries. Coordination of charging schedules of EVs with the objective of minimizing the total charging cost while considering varying…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Bi-Level Scheduling Approach for the Participation of EV Aggregators in Competitive Electricity Markets

et al. 2017

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This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggregator in a competitive environment. In this approach, the EV aggregator decides to participate in day-ahead (DA) and balancing markets, and provides energy price offers to the EV owners in order to maximize its expected profit. Moreover, from the EV owners' viewpoint, energy procurement cost of their EVs should be minimized in an uncertain environment. In this study, the sources of uncertainty-including the EVs demand, DA and balancing prices and selling prices offered by rival aggregators-are modeled via stochastic programming. Therefore, a two-level problem is formulated here, in which the aggregator makes decisions in the upper level and the EV clients purchase energy to charge their EVs in the lower level. Then the obtained nonlinear bi-level framework is transformed into a single-level model using Karush-Kuhn-Tucker (KKT) optimality conditions. Strong duality is also applied to the problem to linearize the bilinear products. To deal with the unwilling effects of uncertain resources, a risk measurement is also applied in the proposed formulation. The performance of the proposed framework is assessed in a realistic case study and the results show that the proposed model would be effective for an EV aggregator decision-making problem in a competitive environment.

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Coordination of EVs Participation for Load Frequency Control in Isolated Microgrids

Cited by 49 publications

References 23 publications

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

Optimal scheduling of distributed energy resources and responsive loads in islanded microgrids considering voltage and frequency security constraints

A Stochastic Bi-Level Scheduling Approach for the Participation of EV Aggregators in Competitive Electricity Markets

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