Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework

Rezaei, Navid; Kalantar, Mohsen

doi:10.1016/j.enconman.2014.12.049

Cited by 118 publications

(77 citation statements)

References 40 publications

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“…Islanding protection using wavelet analysis and neuro-fuzzy system in inverter based distributed generation was researched into [16], and an adaptive ANN-controlled was proposed into [25] to reduce the NDZ consisting in passive islanding detection methods. Variable impedance insertion [30] and droop control [31] methods also offer different solutions to the subject. There have been a few FPGA-based islanding detection studies in recent years [32], but these studies present only particular, not general solutions to the problem.…”

Section: A Short Discussion Of Previous Workmentioning

confidence: 99%

A remote islanding detection and control strategy for photovoltaic-based distributed generation systems

Bayrak

2015

Energy Conversion and Management

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Section: A Short Discussion Of Previous Workmentioning

confidence: 99%

A remote islanding detection and control strategy for photovoltaic-based distributed generation systems

Bayrak

2015

Energy Conversion and Management

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“…Uncertainty modeling of renewable resources and electric demand In order to model the variation of wind power generation, the historical data records of wind speed, v, is used and modeled by Rayleigh PDF [22]. The general Rayleigh PDF for wind speed can be formulated as follows [27]:…”

Section: B Proposed Solution Methodologymentioning

confidence: 99%

“…In the same work, the authors only concentrate on static performance of DERs and the effect of DR participants on voltage and frequency security is not considered. Likewise, an energy management strategy is proposed in [22] to coordinately manage the generating units and DR resources in a MG such that both static and dynamic frequency security constraints are met, however, the effect of DR participants on voltage security is not investigated. A control framework for the participation of responsive loads in the voltage and frequency control of a given MG is proposed in [23].…”

Section: Ns T I R mentioning

confidence: 99%

“…Equations (20)- (21) Constraints (22)- (23) couple the first stage decisions with possible realizations of stochastic processes. Equation (22) represents the relationship between the scheduled power of DGs and their deployed powers and reserves in scenarios. Also, Equation (23) stipulates the relationship between the scheduled values of load and deployed energy and reserves in the scenarios for each group of customers.…”

Section: B Ac-power Flow Constraintsmentioning

confidence: 99%

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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 simulations are performed over a modified residential MG which is presented in Figure 1 [30]. There are different types of distributed generation (DG) units in the MG including two micro-turbines (MT 1 & MT 2 ), two fuel cell (FC 1 & FC 2 ) units, and one gas engine (GE) unit.…”

Section: Test Casementioning

confidence: 99%

Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

et al. 2017

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Abstract:In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response to energy price changes and get incentives in return. In this paper, we study the effect of various time-based rate (TBR) programs on the stochastic day-ahead energy and reserve scheduling in residential islanded microgrids (MGs). An effective approach is presented to schedule both energy and reserve in presence of renewable energy resources (RESs) and electric vehicles (EVs). An economic model of responsive load is also proposed on the basis of elasticity factor to model the behavior of customers participating in various DR programs. A two-stage stochastic programming model is developed accordingly to minimize the expected cost of MG under different TBR programs. To verify the effectiveness and applicability of the proposed approach, a number of simulations are performed under different scenarios using real data; and the impact of TBR-DR actions on energy and reserve scheduling are studied and compared subsequently.

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Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework

Cited by 118 publications

References 40 publications

A remote islanding detection and control strategy for photovoltaic-based distributed generation systems

A remote islanding detection and control strategy for photovoltaic-based distributed generation systems

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

Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

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