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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.

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.

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.

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 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 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%.

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.

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.

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.

One of the major challenges in protection of the inverter-interfaced islanded microgrids is their limited fault current level. This degrades the performance of traditional overcurrent protection schemes. This paper proposes a fault detection strategy based on monitoring the transient response of the inverter current waveform using a transient monitoring function. To enhance the ability of the proposed fault detection scheme, an auxiliary control system is employed in addition to the main control system of the inverter. The proposed scheme can also differentiate asymmetrical and symmetrical fault conditions from normal load switching events and is effective for various inverter topologies (i.e., three/four-leg), main current limiting strategies, and all reference frames of the multi-loop control system. The merits of the proposed fault detection scheme are demonstrated through several time-domain simulation case studies using the CIGRE benchmark low voltage microgrid network.

There has been a considerable importance for the islanding detection due to the growing integration of distributed generations (DGs) in the modern power grids. This paper proposes a novel active islanding detection scheme for synchronous DGs, considering two additional compensators and a positive feedback for each of active and reactive power control loops. The added blocks are designed using the small gain theorem and stability margins definition considering characteristics of open loop transfer functions of synchronous DG control loops. Islanding can be detected using the proposed method even where there is an exact match between generation and local load without sacrificing power quality. In addition, the performance of the proposed method can be retained even with high penetration of motor loads. The proposed scheme improves the stability and power quality of the grid, when the synchronous DG is subjected to the grid-connected disturbances. Furthermore, this method augments the stability margins of the system in the grid-connected conditions to enhance the disturbances ride-through capability of the system and reduce the negative impact of the active methods on the power quality. Simultaneous advantages of the proposed scheme are demonstrated by modeling a test system in MATLAB software and time-domain simulation achieved by PSCAD.

With high penetration of distributed energy resources (DER), fault management strategy is of great importance for the distribution network operation. The objective of this paper is to propose a current and voltage limiting strategy to enhance fault ride-through (FRT) capability of inverter-based islanded microgrids (MGs) in which the effects of inverter control system and inverter topology (four/three-wire) are considered. A threephase voltage-sourced inverter (VSI) with multi-loop control system implemented in synchronous, stationary, and natural reference frames is employed in this study for both four- and three-wire configurations. The proposed strategy provides high voltage and current quality during overcurrent conditions, which is necessary for sensitive loads. Several time-domain simulation studies are conducted to investigate the FRT capability of the proposed strategy against both asymmetrical and symmetrical faults. Moreover, the proposed method is tested on the CIGRE benchmark microgrid to demonstrate the effectiveness of the proposed limiting strategy.

This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.

In the event of a generator loss or disturbance, the power system frequency declines quickly and overall system stability is at risk. During these scenarios, under frequency load shedding is triggered to restore the power system frequency. The main stage of modern adaptive under frequency load shedding techniques is disturbance estimation. However, the swing equation is widely used in disturbance estimation but has some critical estimation errors. In this paper, instead of using the swing equation we proposed the use of a disturbance observer to estimate the curtailed power. By making use of wide area measurements, a system frequency response model, which is a representative of the whole power system, can be realized in real time. Using different power system states of the developed model, a disturbance observer can be designed as well. The main advantage of the disturbance observer is that it can accurately estimate the disturbance magnitude and its location in a very short time. Further investigations show that by using the disturbance observer disturbances, which occur at the same time or at different times in different areas regardless of the magnitude or size, accurate estimations can be made. To ascertain the efficiency of the proposed scheme, simulations are done for a four-area power system using Matlab/Simulink.

The penetration level of the renewable energy resources (RER), such as wind power turbines and solar photovoltaic generation, in interconnected power systems has been increased in many countries. A high penetration level of RERs causes some problems to the grid operator, e.g., lack in primary reserve. Due to environmental concern and energy security risk, many countries around the world decided to increase their electric vehicles (EV) in the near future which provides a good chance to use them as a mobile battery energy storage system (BESS). This paper proposes a new scheme to provide necessary primary reserve from electric vehicles by using hierarchical control of each individual vehicle. An EV aggregator based on the vehicle's information such as the required state of charge (SOC) for the next trip, departure time, and initial SOC is proposed. The proposed aggregation scheme determines the primary reserve and contracts it with system operator based on electricity market negotiation. The effectiveness of the proposed scheme is shown by the several simulation studies in the Taiwan power (Tai-power) system to enhance frequency nadir and steady state frequency after a large disturbance.

Participation of consumers in Demand Response (DR) programs improves system stability and reliability as well as market efficiency. Retailers and distributors purchase DR to advance business and system reliability, respectively. Meanwhile, large consumers, Distribution System Operators (DSOs), Load Service Entities (LSEs), and DR aggregators sell DR to increase their own profits. In this context, DR aggregators are key elements of power systems that enhance the participation of consumers in electricity markets. These market participants can negotiate their aggregated DR with other market players in Demand Response eXchange (DRX) markets, and participate in the energy and ancillary service markets. Hence, this paper proposes a stochastic model to optimize the performance of a DR aggregator to take part in the day-ahead energy, ancillary services and intraday DRX markets. In order to mitigate the negative impacts of uncertainties, Conditional Value at Risk (CVaR) is also incorporated to the proposed model. Numerical studies indicate that the proposed model for DR aggregator can arrange its offering/bidding strategies to participate in the mentioned markets simultaneously.

Summary Industrial parks are forming industrial microgrids (IMGs) with factories, distributed energy resources, electric loads, heat loads, and combined heat and power systems as well as renewable distributed energy resources and plug-in electric vehicles (PEVs). Generation scheduling (GS) in IMGs is affected by the stochastic behavior of electric and heat loads due to outages of production processes or production lines and the uncertainties in solar irradiance and combined heat and power systems. This paper presents a stochastic scenario-based GS framework to consider uncertainties in an IMG coordinated with PEV charging. Although the scenario-based methods are usually very time consuming, this paper shows that their applications in IMGs will not significantly increase the calculation time. The proposed formulation guaranties that occurrence of each condition of uncertainty will not affect the PEV activities. An IMG with 12 factories, photovoltaic generations, and 6 types of electric vehicles with different battery sizes is considered and simulated. The main contributions are (1) a new stochastic GS problem formulation to minimize the cost of IMGs while fully charging all PEVs within their requested periods considering the network security, factories, and PEV constraints; (2) changing the nonlinear constraints to linear forms suitable for scenario-based optimization; and (3) considering the stochastic behavior of electric loads without requiring any data about their internal process in each factory.