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The paper proposes a technique for the on-line estimation of Thevenin equivalent (TE) which only needs the present phasor measurements. The technique is based on the wide-area measurements including voltage and current phasors of the system loads and synchronous generators, so that it can simultaneously estimate TE of the system seen from the interested buses. The technique has two main steps. In the first step, the conventional impedance matrix $\bar Z_{\rm bus}$ is modified to be suitable for TE estimation. In the second step, a correction coefficient based on the sensitivity theory calculated by using two consecutive phasor measurements is applied to correct the diagonal terms of the $\bar Z_{\rm bus}$ matrix. Simulation results carried on the IEEE 39-bus and 118-bus test systems show that the proposed technique can accurately estimate the TE for both generation and consumption buses under any load-increase scenario. The comparison scenarios verify the superiority of the proposed technique over others.

Prolonged voltage level reduction caused by the fault induced delayed voltage recovery (FIDVR) event may lead to a decrease in distance relays security. Therefore, some distance relays are prone to mal-operation under severely prolonged depressed-voltage conditions, and their security should be considered in the FIDVR event studies. The present paper investigates the possible operation of distance relay during the FIDVR event and proposes an auxiliary protection algorithm to effectively prevent its mal-operation during short-term dynamic voltage transient. The proposed algorithm estimates the critical time and voltage level at which the impedance trajectory arrives in Zone 3 of the critical relays using the rate of change of the impedance trajectory, relay margin index, and time-variant NERC/WECC severity indices. Then, the critical voltage is compared with the expected voltage level at the estimated critical time calculated by piecewise cubic spline interpolation (PCSI) method and three consecutive voltage phasors to decide about the block of relays which entering the impedance trajectory to their Zone 3 is probable during the FIDVR event. The efficacy of the proposed method is demonstrated by simulating some short-term voltage transient scenarios on the IEEE 39-bus test system

Demand response modelling have paved an important role in smart grid at a greater perspective. DR analysis exhibits the analysis of scheduling of appliances for an optimal strategy at the user’s side with an effective pricing scheme. In this proposed work, the entire model is done in three different steps. The first step develops strategy patterns for the users considering integration of renewable energy and effective demand response analysis is done. The second step in the process exhibits the learning process of the consumers using Robust Adversarial Reinforcement Learning for privacy process among the users. The third step develops optimal strategy plan for the users for maintaining privacy among the users. Considering the uncertainties of the user’s behavioral patterns, typical pricing schemes are involved with integration of renewable energy at the user’ side so that an optimal strategy is obtained. The optimal strategy for scheduling the appliances solving privacy issues and considering renewable energy at user’ side is done using Robust Adversarial Reinforcement learning and Gradient Based Nikaido-Isoda Function which gives an optimal accuracy. The results of the proposed work exhibit optimal strategy plan for the users developing proper learning paradigm. The effectiveness of the proposed work with mathematical modelling are validated using real time data and shows the demand response strategy plan with proper learning access model. The results obtained among the set of strategy develops 80 % of the patterns created with the learning paradigm moves with optimal DR scheduling patterns. This work embarks the best learning DR pattern created for the future set of consumers following the strategy so privacy among the users can be maintained effectively.

Transient behaviour of high‐voltage direct current transmission lines under direct current faults can be easily affected by many factors, namely, fault location, fault resistance and transmission line length. In order to design a suitable protective scheme, the impact of these factors should be thoroughly investigated. An impedance‐based analysis is more suitable in evaluating high‐voltage direct current system behaviour during direct current line faults, and consequently, in comparison to similar harmonic current or voltage‐based schemes, a characteristic harmonic impedance‐based protection is more capable in fault detection. Therefore, this paper presents a novel pilot protection method for line‐commutated converter based high‐voltage direct current transmission lines, which relies on continuous monitoring of characteristic harmonic impedances. The proposed method can accurately calculate location of faults along the line, and estimate additional valuable information, such as fault resistance. The validity of the proposed method is evaluated by a wide range of fault scenarios using the CIGRE high‐voltage direct current benchmark model, simulated in PSCAD/EMTDC and codes written in MATLAB software environments. It will be shown that the proposed protection method sounds promising, and can serve as an excellent backup option in the case of primary protection malfunction.

State of health (SOH) and remaining useful life (RUL) are two major key parameters which plays a major role in battery management system. In recent years, various machine learning approaches have been proposed to estimate SOH and RUL effectively for establishing the battery conditions. In the proposed work establishes an effective method to predict the battery aging process with accurate battery health estimation with real time simulations and hardware approach. This paper effectively exhibits a process to estimate SOH and RUL of a Li-Ion 18650 cell which are based on various factors like state of charge, discharge voltage transfers characteristics, internal resistance and capacity. To identify an optimal SOH and RUL machine learning based estimation approach, various battery’s statistical models are developed and implemented on a standalone hardware platform. The experimental results in this real time application shows that SOH is predicted by deep neural network approach which are found to be within the accepted error rate of ±5% and long short time memory neural network model estimates a battery’s RUL effectively with an accuracy of ±10 cycles. This approach exhibits various machine learning models in an realistic hardware platform which establishes optimal battery life.

In this paper, the significance of cross-tied link between the solar photovoltaic (PV) modules in an array during partial shading conditions (PSCs) is introduced. In order to conduct a detailed analysis, twenty numbers of 20W PV modules ( $4\times 5$ ) are arranged in a series-parallel (SP) configuration. The change in the pre-arranged SP configured PV array is implemented using a cross-link matrix switch between parallels based on shadow patterns. The switch matrix based modified PV array configuration is called Adaptive-cross-tied (A-CT) configuration. An embedded system based adaptive switch matrix (ASM) controller is developed to control the cross-linking connections between the PV modules under the PSCs to improve global maximum power. In addition, a performance analysis is carried out and compared all PV modules arranged in conventional SP and A-CT configurations. Moreover, realistic shadow test cases are under consideration to characterize current-voltage (I-V) and power-voltage (P-V) characteristics. The output power of the PV array decreases as well as the P-V curves show multiple power maxima points., such as the local maximum power point (LMPP) and the global maximum power point (GMPP). LMPP and GMPP locations, mismatch loss (ML), enhanced fill factor (FF), decreased power loss (PL) and performance ratio (PR) are indicators of performance during experimental and MATLAB/Simulink studies.

This paper proposes a novel, fully decentralized load frequency control (LFC) approach based on dynamic state estimation (DSE). The proposed approach employs an unknown input observer (UIO) for each power system area for tracking the dynamic states in real time operation. In order to achieve the fully decentralized control approach, the demand fluctuation and tie-line power deviations are modeled as unknown inputs to the UIO of each area. An optimal state feedback control method based on the observed states is used next to control each area separately. This approach reduces the complexity of the designed observer, achieves fully decentralized control, improves the robustness of the controllers, and makes the estimation process highly efficient, accurate, and easy to implement. The applicability of the proposed method is shown on a representative model of four areas interconnected via various transmission links. Simulation results demonstrate the efficiency and accuracy of the designed observer and verify the superiority and robustness of the proposed control approach compared to alternative approaches.

Frequency-based relays, commonly used for islanding detection of synchronous distributed generation (SDG), may either have large non-detection zones (NDZs) or wrongly operate for non-islanding disturbances unless they are efficiently adjusted. Trial and error simulation-based methods, employing application region (AR) and/or power imbalance AR (PIAR), are presented in the literature to adjust these relays for quick islanding detection without false trips. However, the associated settings are not optimal and finding them is time-consuming. In this study, an approach utilising particle swarm optimisation algorithm is proposed to adjust a rate of change of frequency (ROCOF) relay, one of the most effective relays in SDG islanding detection. The proposed approach needs a set of analytical formulas for determining the ROCOF relay performance curve and NDZ as well as AR and PIAR. These formulas are developed to be employed in the relay adjustment. By applying the developed analytical formulas to the optimisation-based approach, the ROCOF relay is adjusted fast and systematically. It is shown that while the performance of the relay adjusted by the proposed approach is close to the one with setting obtained by corresponding trial and error-based method, the latter is much more time-consuming than the former.

This paper proposes a novel, unknown input functional observer based optimal load frequency control approach for real-world complex nonlinear power systems. In the proposed control approach, the control signal applied to each power plant is directly estimated via the well-designed functional observer. The proposed functional dynamic estimator is able to handle parametric and nonparametric uncertainties, control loop and sensor faults, unknown inputs, and cyber-attacks. The observer for each power plant is decoupled from the other plants resulting in a more feasible implementation, reducing the complexity of the estimator and improving the reliability of the proposed control system. The applicability of the proposed method is shown on IEEE 39 bus-system divided into three control areas. The effectiveness of the proposed control scheme is verified by comparing results with well-known control schemes. Tolerance of the proposed technique to unknown inputs, uncertainties, and possible cyber-attacks is verified by several simulation scenarios.

High penetration of renewables in power systems would decrease the inertia and frequency control reserve. Hence, preserving the frequency stability of power systems with high penetration of renewables is a challenge. In this paper, a comprehensive frequency control scheme is proposed which uses the capacity of both loads and online generating units coordinately. To preserve the frequency stability while the generating units maneuvering and costumers’ inconvenience are minimized, tuning the parameters of the proposed frequency control scheme has been modeled as two multi-objective optimization problems with appropriate objective functions. A proper method has been proposed for solving the optimization problems which is successful in obtaining solutions that guarantee achieving the goals determined for the frequency control scheme. The proposed scheme enables the system operator to optimally manage the frequency control reserve provided by loads and online generating units. Presented results certify that, as decreasing the inertia of the system does not have a considerable impact on the proposed frequency control scheme, it is a good choice to be implemented in power systems with high penetration of renewables.

Ancillary reserve is one of the most critical issues for guaranteeing the safe operation of modern power systems. Generation-side secondary-reserve scheduling, which is responsible for keeping the balance between the generation and demand in power systems, has a direct impact on active power, frequency regulation, and load-frequency control (LFC) studies. This chapter presents a comprehensive framework for the generation-side reserve scheduling and LFC in modern power systems. An overview of power system stability and security is first introduced for highlighting the need for such reserve. Based on the power system security constraints, an optimization problem of both secondary-reserve scheduling and optimal tuning of frequency controllers parameters in modern power system is also presented. Furthermore, some scenarios have been applied to show the superiority of the suggested LFC technique compared to others. Moreover, the effectiveness of the fractional calculus–based control scheme is investigated to show the importance of decision-making methods in these topics.

When a disturbance occurs in a power system which leads to a decline in frequency, the power grid voltage stability is also at risk. In this research, we propose an improved under frequency load shedding technique that incorporates both the estimated disturbance and the voltage index of load buses. Based on the swing equation the disturbance is estimated in real time and the value is used for load shedding. Instead of shedding prefixed load-buses, all load-buses participate in the shedding process. When a disturbance occurs the voltage drop of each bus is expressed as a fraction of the total calculated voltage drops, and this gives the bus voltage index of the load buses. The greater the bus voltage index the more the load that is to be shed from the respective bus. It is also shown that the use of phasor measurements reduces the complexities of using the Jacobian to calculate voltage stability indicators.

Due to the great importance of the performance of load frequency controllers in power systems, a lot of effort have been performed to improve the performance of these controllers by fine tuning the...

High distributed generation (DG) penetration can lead to significant changes in the operation of high voltage transmission systems. In this paper, a methodology is proposed, which can optimally allocate synchronous DG (SDG) units to sub-transmission substations based on defining an SDG planning model for maximizing the profit of regional transmission system operators under the conditions existing in the Iranian system by taking into account their relevant costs and revenues. The constraints include the network and the DG capacity constraints. The formulated problem is executed by a heuristic approach comprising three main parts. The algorithm starts with determining the maximum DG capacity at each bus by short-circuit studies in order to satisfy short-circuit-level constraints. In the second part, the SDG planning problem is tackled by the Tabu search algorithm. The final stage is to investigate the constraints of protection blinding and false tripping for the solution of the second part. The proposed model, in different scenarios, was put to test in Isfahan Regional Electricity Company network in Iran. According to the results, significant profit related to the transmission and sub-transmission systems was achieved by the proposed model.

To deal with high variability of stochastic market operations and with the aim of assuring a feasible and economic operation under high renewable energy sources penetration, in this paper two applicable solutions are proposed: 1) the incorporation into the electricity market of emerging flexible resources, including demand response, bulk energy storages, and plug-in electric vehicle parking Lots considering their own specific characteristics; and 2) a new flexible ramp market in order to cope with sudden variations and guarantee the rampability of reserve capacity provided by a generation portfolio. On this basis, an integrated stochastic day-ahead market clearing model has been developed to solve the energy, reserve, and flexible ramp scheduling considering a real-time power balance problem, reflecting the 5 min.-by-5 min. renewable energy source and demand changes. Numerical tests are conducted on a modified IEEE RTS 24-bus and the obtained results validate the applicability of proposed model.

This paper aims at providing a novel techno-economic flexibility index to quantify the relative flexibility of different conventional generation technologies. The proposed measure takes into account a comprehensive set of technical flexibility characteristics of generation units including minimum stable generation level, operating range, minimum up/down times, and ramp up/down capability. The impact of various technical parameters on the flexibility restriction is determined based on the additional costs imposed to the system operator in order to satisfy that constraint. Afterward, the calculated flexibility index is incorporated into day-ahead market clearing procedure as a new objective function beside operation cost using a multiobjective decision-making approach. Simulation results show that the need of different flexibility levels changes the optimal generation dispatch and results in different operation costs. Furthermore, the impact of two emerging flexible options, i.e., bulk energy storages and a typical demand response program in the flexibility contribution of other generation technologies is also investigated. The results reveal that the integration of emerging flexible options frequently changes the flexibility share of conventional units and can provide the required flexibility level at a lower cost.

The ability of riding through the grid disturbances can increase the integration of microgrids into the distribution system. Consequently, a grid-connected microgrid should provide ancillary services such as low voltage ride-through (LVRT) capability and reactive power support to sustain the power system operations during abnormal grid conditions. The objective of this paper is to propose an LVRT scheme that improves the power quality of the entire microgrid. The developed method is implemented as the controller of the interface voltage-sourced converter (VSC) of a distributed energy resource and consists of primary and secondary control levels. The former includes the cascaded voltage and current control loops and the droop controller, while the latter controls the reactive power injection during the balanced/unbalanced voltage sags/swells. The proposed scheme is developed based on the independent control of each phase and does not require calculation of symmetrical components. Moreover, it can be employed in the VSC control systems with various reference frames and is effective for droop-based grid-connected microgrids with both single-phase and three-phase four-wire configurations. The proposed strategy is implemented using the hierarchical control system and preserves the plug and play capability. Several case studies are presented to verify the effectiveness of the proposed strategy.

Preserving the frequency stability of low inertia microgrids (MGs) with high penetration of renewables is a serious challenge. To rise to this challenge, the inertia constant of MGs would be virtually increased using energy storages. However, it is important to determine the suitable value of inertia constant for these systems such that the frequency stability is preserved with a lower cost. Frequency droop coefficient of distributed energy resources (DERs) and load frequency controllers’ parameters would also affect the frequency response of MGs. Hence, in this paper, inertia constant is tuned together with frequency droop coefficient of DERs and load frequency controllers’ parameters. Determining these parameters is modeled as a multi-objective optimization problem and, because the number of objectives is higher than three, the problem is solved by a many-objective optimization algorithm. Comparative simulation studies have been done on an MG with different types of DERs to prove that using the proposed strategy for tuning the MG parameters not only the frequency deviation is highly decreased but also the amount of load shedding is considerably diminished. This would increase the customers’ satisfaction. Moreover, considering the inertia constant as a minimization objective, frequency stability would be preserved with a lower cost.

The high penetration of renewable energy sources in modern power systems introduces opportunities and challenges to power system operators. The frequency, which is a global variable in power systems, is being affected due to the increase of the renewable energy shares. This paper suggests dynamic models of power systems for assessing the frequency response due to different types of disturbances and uncertainties from renewable energy sources. The introduced model is built based on the sub-transient model of synchronous generating units. Likewise, a simplified system frequency response model is presented, in which the demand-side participation in providing ancillary services is considered. Different types of power systems are considered to verify the introduced models. The results show the effectiveness of the presented models in evaluating the impact of different parameters on power system frequency response. The impacts of increasing the renewable energy shares and its uncertainties are also investigated.

A new decentralized load frequency control (LFC) scheme based on the concept of dynamic state estimation is proposed in this paper. The suggested novel, scheme makes use of an efficient deterministic state estimator, known as unknown input observe (UIO) utilized in each area-control for online observing of the dynamic states of the system. To achieve a decentralized approach, the demand and transferred power among areas are considered as unknown inputs to the power system operators. Then, the optimal control theory is adopted to control the frequency deviation in each area which is designed based on the observed dynamic states. An interconnected power system with four-areas is used to verify the applicability of the proposed scheme, while the robustness, accuracy, and superiority of the proposed method is shown by several comparisons with other methods recently published in literature.

The rapid growth of residential rooftop photovoltaic (PV) systems may cause significant power quality problems, such as severe voltage fluctuation and unbalance which can restrict further PV integrations to the network. In this paper, the potential capability of residential PV inverters is investigated to develop a distributed reactive power compensation scheme for voltage regulation in three-phase four-wire unbalanced low voltage distribution networks (LVDNs). For this purpose, an effective method is proposed by means of single-phase PV inverters arbitrarily connected among different phases. The aims are improving voltage profile along the feeder and reducing the voltage unbalances. The PV inverters are connected in such a way that they form distributed delta and wye configurations to compensate the negative and zero sequence components of voltage, respectively and to regulate voltage within the allowed limits as well. The proposed consensus-based algorithm considers each PV system as a smart agent and updates its reactive power control setting based on only local measurements and data communications with neighboring agents. The effectiveness of the proposed strategy in terms of voltage regulation and unbalance and energy losses is shown through detailed simulations over a 24-hr period on a three-phase four-wire unbalanced LVDN with realistic data.

The increase in penetration of renewables has decreased the available frequency control reserve provided by conventional generating units. As a result, alternative options for provision of frequency control reserve are required to keep the frequency quality of the system. Using loads for this purpose is one of the available options. However, this should be done with the minimum negative effect on the devices life-time and on the customers' convenience. In this paper, a framework to evaluate the effect of loads' participation in primary frequency control effect on the devices' life-time and customers' convenience is proposed and several strategies used to reduce these negative effects are compared.

In the event of a power system disturbance, it is important that the decision to implement under frequency load shedding is based on both the minimum frequency and the magnitude of the disturbance. In this paper, we propose the use of higher order polynomial curve fitting to estimate the minimum frequency. If the prediction shows that the minimum frequency threshold will be violated, the magnitude of the total disturbance is estimated using the swing equation. In addition, the minimum amount of load that must be shed to restore the frequency just above the minimum value can also be directly calculated. Simulations are carried out for the considered Taiwan power system and the results prove the efficiency of the proposed technique.

Power systems that are known as the most complex systems encounter different types of disturbances and emergence events. To operate such systems in a stable mode, several control protection techniques are in need. Frequency plays a vital role in power systems and needs to be properly maintained in a permissible level. To this end, under-frequency load-shedding (UFLS) techniques are used to intercept the frequency decline when a system encounters a severe disturbance. In this paper, a novel, wide-area measurement system (WAMS)-based optimal UFLS technique is proposed. The system frequency response (SFR) model is identified online based on the real-time measurements collected by phasor measurement units (PMUs). Then, the SFR model is used to design a new optimal multi-stage UFLS scheme. Imperialist competitive algorithm (ICA), which is a powerful evolutionary computing method, is then adopted for solving the suggested multi-stage UFLS optimization problem. The applicability of the proposed method is shown on a practical test system. The effectiveness of the proposed optimal multi-stage UFLS scheme is verified by several simulation and comparison scenarios.

The rapid growth of rooftop photovoltaic (PV) arrays installed in residential houses leads to serious voltage quality problems in low voltage distribution networks (LVDNs). In this paper, a combined method using the battery energy management of plug-in electric vehicles (PEVs) and the active power curtailment (APC) of PV arrays is proposed to regulate voltage in LVDNs with high penetration level of PV resources. A distributed control strategy composed of two consensus algorithms is used to reach an effective utilization of limited storage capacity of PEV battery considering its power/capacity and state of charge (SoC). A consensus control algorithm is also developed to fairly share the required power curtailment among PVs during overvoltage periods. The main objective is to mitigate the voltage rise due to the reverse power flow and to compensate the voltage drop resulting from the peak load. Overall, the proposed algorithm contributes to a coordinated charging/discharging control of PEVs battery which provides a maximum utilization of available storage capacity throughout the network. In addition, the coordinated operation minimizes the required active power which is going to be curtailed from PV arrays. The effectiveness of the proposed control scheme is investigated on a typical three-phase four-wire LVDN in presence of PV resources and PEVs.

The increasing share of uncertain wind generation has changed traditional operation scheduling of power systems. The challenges of this additional variability raise the need for an operational flexibility in providing both energy and reserve. One key solution is an effective incorporation of plug-in electric vehicles (PEVs) into the power system operation process. To this end, this paper proposes a two-stage stochastic programming market-clearing model considering the network constraints to achieve the optimal scheduling of conventional units as well as PEV parking lots (PLs) in providing both energy and reserve services. Different from existing works, the paper pays more attention to the uncertain characterization of PLs takes into account the arrival/departure time of PEVs to/from the PL, the initial state of charge (SOC) of PEVs, and their battery capacity through a set of scenarios in addition to wind generation scenarios. The results reveal that although the cost saving as a consequence of incorporating PL to the grid is below 1% of total system cost, however, flexible interactions of PL in the energy and reserve markets can promote the integration of wind power more than 13.5%.

This paper proposes an offering strategy for a wind power producer (WPP) that participates in both day-ahead (DA) and balancing oligopoly markets as a price maker. Penetration of demand response (DR) resources into smart grids is modeled by intraday demand response exchange (IDRX) architecture. A bilevel optimization framework is proposed based on multiagent system and incomplete information game theory. Modeling the WPPs in high penetration of wind power as price makers can reflect the capability of this market player to directly affect the market prices. Simulation results indicate that the price-taker model of WPP is not accurate for WPPs that have significant market shares. By comparing the results obtained from modeling the WPPs as price makers with the ones as price takers, it can be concluded that WPPs have the market power not only to increase the prices of both DA and balancing markets, but also to reduce the amount of DR through IDRX market mechanism.

The intermittent nature of wind generation will lead to greater demands for operational flexibility. Traditionally, reserves came from conventional power plants provide the majority of additional required flexibility leading to higher efficiency losses due to technical restrictions of such units. Recently, demand response programs and emerging utility-scale energy storages gained much attention as other flexible options. Under this perspective, this paper proposes a robust optimization scheduling framework to derive an optimal unit commitment decision in systems with high penetration of wind power incorporating demand response programs as well as bulk energy storages in co-optimized energy and reserve markets. In this regard, an improved demand response model is presented using the economic model of responsive loads based on customer’s behavior concept that gives choice right opportunity to customers in order to participate in their desired demand response strategy. Moreover, bulk energy storages are considered to be as active market participants. Computational results demonstrate how coordinated operation of different type of demand response programs and bulk energy storages can help accommodate wind power uncertainty from the economic and technical points of view.

Demand Response (DR) is known as an effective solution for many power grid problems such as high operating cost as well as high peak demand. In order to achieve full potential of DR programs, DR must be implemented optimally. On this basis, determining optimal DR location, appropriate DR program and efficient penetration rate for each DR program is of great practical interest due to the fact that it guides the system operators to choose proper DR strategies. This paper presents a novel linear framework for DR optimization problem incorporated into the network-constrained unit commitment with the aim of determining optimal location, type and penetration rate of DR programs considering several practical limitations. To this end, a number of tariff-based and incentive-based DR programs have been taken into account according to the customer’s benefit function based on the price elasticity concept. The IEEE 24-bus Reliability Test System (RTS 24-bus) is used to demonstrate the applicability of the proposed model. Finally, DR optimization is analyzed with regards to different customer’s elasticity values and also different number of candidate load buses which reveal the applicability and effectiveness of the proposed methodology.

A more efficient Volt-VAr optimization (VVO) for transmission and distribution systems can be realized with considering the interaction between distribution system operators (DSOs) and transmission system operator (TSO) and using flexibility resources such as Distributed Generations (DGs) with high penetration in distribution systems. In this paper, a competitive decentralized framework is proposed for interactive VVO of transmission and distribution systems, in the presence of high penetration of distributed energy resources (DERs). In the proposed scheme, while TSO and DSOs are self-interested and individually solve VVO sub-problem according to their own objectives and constraints, they are interactive and receive feedback from each other to understand the mutual effects of their decisions and give an appropriate response. Each optimization sub-problem minimizes power losses of its own network for each load level subjected to the network and reactive power resources constraints. The defined interactive VVO problem is solved by a new decentralized algorithm based on the decomposition of boundary bus variables between transmission and distribution systems. Furthermore, some heuristic techniques are applied to convert the sub-problems formulation to a linear or at least convex one. Some case studies on IEEE 14-bus test system connected to three IEEE 69-bus distribution systems and IEEE 118-bus test system connected to thirty IEEE 69-bus distribution systems confirm the efficiency of the proposed framework in view of power loss, voltage profile and reactive power generation of transmission and distribution networks in comparison with isolated and interactive cooperative methods.

Providing additional required flexibility as a consequence of variable wind generation is an essential challenge in future power grids. Demand Response (DR) is a relatively economic tool which can create considerable flexibility by motivating the customers to change their typical consumption patterns. This paper aims at quantitative evaluation of flexibility level of a comprehensive set of DR programs in power grid with significant amounts of wind generation through an applicable metric. The employed metric determines the flexibility of different DR programs based on their impacts on releasing technical constraints of conventional generation units which are restricted flexibility amount including minimum stable generation level, operating range, minimum up/down times and ramp up/down capability. To this end, a comprehensive portfolio of DR programs consists of tariff-based, incentive-based, and combinational DR programs have been modeled considering the customer’s benefit function based on price elasticity concept. The paper concludes with applicable guidelines for power system operators to design and implement an appropriate DR program from both the flexibility and economic aspects in wind integrated power grids.

As power systems continue to expand, the need arises for more robust monitoring, control and protection techniques especially under abnormal conditions. In the event of generator tripping or major tie-line disconnection due to a fault, the system frequency might drop to unacceptable levels, well below secure threshold values. Under such conditions, under frequency load shedding (UFLS) protective schemes are implemented to balance quickly generation and demand. In this paper, the merits and weaknesses of different UFLS schemes are discussed. In particular, focus is placed on wide area monitoring systems (WAMS)-based UFLS schemes, which are becoming popular due to the availability of real time measured phasors. A comprehensive comparison between the different UFLS techniques is provided and research gaps and future research trends are highlighted.

Correct measurement of different signals used in the micro-grids control center (MGCC) is crucial for their operation, control, and stability. This is especially true for micro-grids operating in island mode. To keep their operation efficient and safe, faulty sensors should be instantly isolated. To this end, novel sensor fault detection and isolation schemes are proposed in this paper that are built based on unknown input observer method (UIO). In this method, load fluctuations and output power variations of renewable energy sources are modeled as unknown inputs. Theoretical analysis and simulation scenarios are carried out on a micro-grid system which consists of different types of energy generation sources and energy storage systems to prove the robustness of the proposed sensor fault detection and isolation schemes. The simulation results also show the ability of the proposed schemes in detecting and isolating faulty sensors in real time, including cases of simultaneous faults.

With the increase in world population and the advancement of industries, demand for power and energy has also sharply increased. Consequently, power systems are usually loaded very close to the steady state stability limit to meet this growing demand. This threatens the secure operation of power systems, therefore schemes that are more intelligent are needed to effectively handle power systems disturbances. In the event of a generation-demand imbalance caused by generator outage under frequency load shedding (UFLS) schemes are implemented. In this paper we propose an UFLS scheme based on the minimum predicted frequency and the extrapolated disturbance magnitude. Based on polynomial curve fitting techniques the future behavior of the system frequency can be predicted. A few data points soon after the disturbance are required to predict the minimum frequency the system will reach. The load to be shed can then be determined from the linear relationship between the frequency drops and load to be shed.

The use of wide area measurements at a central monitoring and control center has brought greater flexibility in the monitoring, control and protection of modern power systems. Under frequency load shedding (UFLS) is one of the many areas experiencing the advantages involved with using wide area measurement systems (WAMS). Conventional UFLS techniques follow a pre-set and rigid threshold of frequency to shed loads at dedicated load buses in the network without considering the magnitude of the disturbance. In this paper, based on the wide area phasor measurements, the actual disturbance in the system is determined a few seconds before performing load shedding. Time domain simulations on an analytic system frequency response model of wide area power system verify the efficiency of the proposed method.

Inertia constant and damping coefficient are the most important parameters in the frequency and stability studies of interconnected power systems. Online determination of such parameters has a great implementation in power system operation, security, and control. In this paper, a new method is proposed for online estimation of both the inertia and damping constants. The proposed method makes use of wide area measurement systems (WAMS) for online gathering of the required data for the estimation method. Furthermore, the proposed method can diminish the effect of missing some required data by estimating the frequency response curve using the polynomial fitting techniques. Moreover, the results verify the superiority of the proposed method for online estimation of both inertia and damping constants in bulk multi-machine power systems where applied to IEEE 68-bus system.

Power systems are the most complex systems that have been created by men in history. To operate such systems in a stable mode, several control loops are needed. Voltage frequency plays a vital role in power systems which need to be properly controlled. To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems. Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance. Likewise, the power exchanges between different control areas are controlled by LFC approaches. In recent decades, many control approaches have been suggested for LFC in power systems. This paper presents a comprehensive literature survey on the topic of LFC. In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems. Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups. The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC.

The voltage rise problem in low voltage (LV) distribution networks with high penetration of photovoltaic (PV) resources is one of the most important challenges in the development of these renewable resources since it may prevent the maximum PV penetration considering the reliability and security issues of distribution networks. In this paper, the battery energy storage (BES) systems are used in order to solve the voltage rise during the peak PV generation as well as the voltage drop while meeting the peak load. A coordinated control strategy is proposed to regulate the charge/discharge of BESs using a combination of the local droop based control method and a distributed control scheme which ensures the voltages of feeder remain within allowed limits. Therefore, two different consensus algorithms are used: The first algorithm determines the BESs participation in voltage regulation in terms of their installed capacity whereas the second one modifies the BESs performance in terms of their state of charge (SoC) to prevent the excessive saturation or depletion of batteries. The proposed controller enables the effective use of storage capacity in different conditions. Finally, the simulation results based upon real data of a radial distribution feeder validate the effectiveness of this approach.