Mohamed Ahmed (Sadek), Ph.D., P.Eng., MIEEE

The continuity of power supply is affected by many factors; the weather conditions to which power system components are exposed are considered the most effect. A new methodology to assess the reliability of distribution system considering the impact of different weather conditions is presented in this paper. The proposed method considers possible future changes in the weather patterns that might occur differently from what it was in the past. Modified sets of reliability indices are presented… Show more

The continuity of power supply is affected by many factors; the weather conditions to which power system components are exposed are considered the most effect. A new methodology to assess the reliability of distribution system considering the impact of different weather conditions is presented in this paper. The proposed method considers possible future changes in the weather patterns that might occur differently from what it was in the past. Modified sets of reliability indices are presented for mathematically predicting reliability performance based on historical reliability data under specific past weather conditions combined with forecasted future weather conditions. The proposed method is applied to the distribution system components of RBTS; the results demonstrate the significance of considering the forecast of weather conditions in reliability assessment. Show less

In recent years, battery energy storage systems (BESS) have been considered promising resources to provide regulation services because of their operational flexibility. In this article, a novel framework and mathematical model are proposed for simultaneously procuring primary regulation (PR) and secondary regulation (SR) reserves alongside energy, in a BESS integrated, locational marginal price (LMP) based real-time market. The BESS submits discharge offers considering degradation cost, based… Show more

In recent years, battery energy storage systems (BESS) have been considered promising resources to provide regulation services because of their operational flexibility. In this article, a novel framework and mathematical model are proposed for simultaneously procuring primary regulation (PR) and secondary regulation (SR) reserves alongside energy, in a BESS integrated, locational marginal price (LMP) based real-time market. The BESS submits discharge offers considering degradation cost, based on the depth of discharge and discharge rate. The proposed model considers a priori cleared day-ahead market (DAM) schedules and accounts for scenarios of load deviations and contingencies in real-time operations. The impact of BESS participation on system operation and market settlement is examined considering two participation options: 1) BESS bidding as the generator/load with price quantity pair; 2) BESS participation using the offers based on degradation cost. The proposed model is validated on the IEEE Reliability Test System to demonstrate its functionalities. Show less

This article investigates the impact of battery energy storage systems (BESSs) on the distribution system energy management (DSEM). The article introduces a linearized multiobjective DSEM framework for reconfigurable smart distribution systems (DSs) in the presence of renewable distributed generators (DGs) and BESSs. The proposed framework aims to achieve three objectives:
minimizing the operating cost, minimizing the energy losses, and improving the voltage profiles. The proposed framework… Show more

This article investigates the impact of battery energy storage systems (BESSs) on the distribution system energy management (DSEM). The article introduces a linearized multiobjective DSEM framework for reconfigurable smart distribution systems (DSs) in the presence of renewable distributed generators (DGs) and BESSs. The proposed framework aims to achieve three objectives:
minimizing the operating cost, minimizing the energy losses, and improving the voltage profiles. The proposed framework determines the optimal operational schedules for the network reconfiguration, the charging/discharging of BESSs, and the dispatch of the energy resources. The proposed DSEM framework is tested on two smart DSs that include BESSs and different types of energy resources. A comparison of the results obtained from different operational scenarios demonstrates the effectiveness of the proposed DSEM framework. The developed framework with BESSs has successfully achieved significant benefits: saving in the DS operating cost, reduction in the DS energy losses, and improvement in the DS voltage profiles. Show less

This paper proposes a framework for solving voltage-sag and voltage-deviation problems in distribution networks using battery energy storage systems (BESSs). The proposed framework is divided into two parts. In the first part, a proposed stochastic planning algorithm determines the optimal sizes and locations of the BESSs that mitigate voltage sags in distribution systems (DSs). The objective of the planning algorithm is to minimize the system annualized costs that include the BESS costs as… Show more

This paper proposes a framework for solving voltage-sag and voltage-deviation problems in distribution networks using battery energy storage systems (BESSs). The proposed framework is divided into two parts. In the first part, a proposed stochastic planning algorithm determines the optimal sizes and locations of the BESSs that mitigate voltage sags in distribution systems (DSs). The objective of the planning algorithm is to minimize the system annualized costs that include the BESS costs as well as the economic losses associated with voltage-sag events. In the second part, a post-fault network-reconfiguration (PFNR) algorithm is proposed to guarantee the optimal and reliable post-fault operation of the system. The objective function is to minimize the post-fault operation costs that include the generation costs, load-curtailment costs, and BESS costs. The main goal of the second part is to use the BESSs obtained from the planning algorithm to ensure the full satisfaction of the system operational constraints that include the voltage limits. The two parts proposed in this paper have been tested on IEEE 33-bus and IEEE 69-bus distribution systems. The obtained results demonstrate the effectiveness of the proposed algorithms in mitigating voltage-sag and voltage-deviation problems at the system level using BESSs. Show less

This paper presents a new generic approach for developing a Jacobian matrix for use with the optimization unit in real-time energy management systems (EMS) for unbalanced smart distribution systems. The proposed formulation can replace approximated calculations for real-time optimal power flow in an optimization unit while providing greater accuracy and requiring less computational time, which is critical for real-time EMS. The effectiveness and robustness of the proposed approach have been… Show more

This paper presents a new generic approach for developing a Jacobian matrix for use with the optimization unit in real-time energy management systems (EMS) for unbalanced smart distribution systems. The proposed formulation can replace approximated calculations for real-time optimal power flow in an optimization unit while providing greater accuracy and requiring less computational time, which is critical for real-time EMS. The effectiveness and robustness of the proposed approach have been tested through simulations with different distribution networks. The simulation results demonstrate a significant reduction in the computational time with the new proposed formulation. Moreover, the results demonstrate the scalability of the proposed approach as the reduction in the computational time is more significant for large practical systems. The proposed approach is characterized by evaluating the scalability and low computational time; thus, it can be used by grid operators in real-time energy management applications for large-scale practical distribution systems. Show less

High penetration of distributed generation (DG) results in technical problems as voltage rise, voltage unbalance, substation reverse power, and transformer overloading. These problems adversely affect the connectivity of DGs either in the planning stage by decreasing the number of connected DGs, or in the operation stage by applying DGs' active power curtailment (APC). This paper presents a techno-economic approach for the enhancement of photovoltaic (PV) DGs connectivity. The proposed approach… Show more

High penetration of distributed generation (DG) results in technical problems as voltage rise, voltage unbalance, substation reverse power, and transformer overloading. These problems adversely affect the connectivity of DGs either in the planning stage by decreasing the number of connected DGs, or in the operation stage by applying DGs' active power curtailment (APC). This paper presents a techno-economic approach for the enhancement of photovoltaic (PV) DGs connectivity. The proposed approach firstly employs a probabilistic economic technique for determining the noncurtailable portion of the PV DG power that ensures profitable DG investment. This portion is integrated, as an economic constraint, in the planning phase of the proposed approach that aims to maximize the number of PV DGs connected to the system. In the operation phase, the proposed approach utilizes the capabilities of the existing equipment on the system; i.e. regulators, capacitors, DGs reactive power, and DGs APC to mitigate all technical problems. The overall objective of this stage is to minimize the total DGs APC while fulfilling all technical and economic constraints. The proposed approach is tested on the modified IEEE 123-bus feeder. The results clarify the efficiency of the proposed techniques in increasing the connectivity of PV DGs while maintaining profitable DG project. Show less

Planning photovoltaic (PV) power systems integration into the grid necessitates accurate modelling of renewable power generation. Global solar irradiance, weather temperature and PV power losses due to overheating specifically in hot regimes are major factors contributing to PV power generation uncertainty. This study targets demonstrating the effectiveness of deploying advanced five parameter probabilistic distribution ‘Wakeby’ for modelling PV uncertain power generation, measured as a… Show more

Planning photovoltaic (PV) power systems integration into the grid necessitates accurate modelling of renewable power generation. Global solar irradiance, weather temperature and PV power losses due to overheating specifically in hot regimes are major factors contributing to PV power generation uncertainty. This study targets demonstrating the effectiveness of deploying advanced five parameter probabilistic distribution ‘Wakeby’ for modelling PV uncertain power generation, measured as a function of such factors, in power system planning applications. The impact of different approaches for incorporating weather temperature on PV energy estimation is studied. Wakeby-Monte Carlo Simulation for PV power data training with an emphasis on MCS stopping criteria for such advanced distribution is presented. The model is tested and verified in 31-bus distribution system to demonstrate its effectiveness over other literature uncertainty modelling approaches when planning integration of PV systems' integration into the grid to minimise the grid losses cost. Real PV power measurements are utilised as benchmark verifying the accuracy and suitability of the presented uncertainty modelling approach. Simulation results demonstrate a small error of $4.7 in the expected annual cost of grid losses when deploying Wakeby model compared to the benchmark case and that error can vary significantly when deploying other PV models. Show less

Recent Federal Energy Regulatory Commission (FERC) Order 841 requires that Independent System Operators (ISOs) facilitate the participation of energy storage systems (ESSs) in energy, ancillary services, and capacity markets, by including ESS bidding parameters that represent the physical and operational characteristics. However, in the existing market frameworks that allow Battery Energy Storage Systems (BESSs) to participate, the bids and offers do not explicitly represent the physical and… Show more

Recent Federal Energy Regulatory Commission (FERC) Order 841 requires that Independent System Operators (ISOs) facilitate the participation of energy storage systems (ESSs) in energy, ancillary services, and capacity markets, by including ESS bidding parameters that represent the physical and operational characteristics. However, in the existing market frameworks that allow Battery Energy Storage Systems (BESSs) to participate, the bids and offers do not explicitly represent the physical and operational characteristics such as the state of charge (SOC), discharge rate, degradation, etc. This paper proposes a novel BESS operational cost model considering degradation cost, based on depth of discharge and discharge rate. The model is developed considering Lithium-ion batteries, and the approach can be applied to other conventional electrochemical batteries, but not flow batteries. A detailed bid/offer structure based on the proposed BESS operational cost functions is formulated. Thereafter, a new framework and mathematical model for BESS participation in an LMP based, co-optimized, energy and spinning reserve market, are developed. Three case studies are presented to investigate the impact of BESS participation on system operation and market settlement. The proposed model is validated on the IEEE Reliability Test System (RTS) to demonstrate its functionalities. Show less

A major concern associated with the connection of distributed generators (DGs) to distribution systems is the voltage rise problem. A solution introduced in many voltage control schemes is DG active power curtailment. However, this measure has a negative effect on both DG revenue and DG investment. This paper proposes the use of existing system resources to mitigate the voltage rise problem. Based on the big bang-big crunch optimization and the reactive power compensation method, the new… Show more

A major concern associated with the connection of distributed generators (DGs) to distribution systems is the voltage rise problem. A solution introduced in many voltage control schemes is DG active power curtailment. However, this measure has a negative effect on both DG revenue and DG investment. This paper proposes the use of existing system resources to mitigate the voltage rise problem. Based on the big bang-big crunch optimization and the reactive power compensation method, the new technique controls the distribution system voltage profile while avoiding DG active power curtailment. The proposed method minimizes voltage deviations by determining the regulator taps and reactive power contributions of both the capacitors and the DGs. The approach is implemented online by a central control unit that optimally determines appropriate control decisions and then communicates them to the voltage regulators, capacitors, and DGs. Eliminating the voltage deviation problem associated with the network installation of DGs provides a cost-effective means of increasing DG penetration. The new algorithm was implemented and tested on the 33-bus test feeder. The results demonstrate the effective control of the voltage profile and fast convergence speed provided by the developed technique. Show less

For distribution network operators to make effective decisions about real-time applications, they should have complete knowledge of all system variables. However, measuring all variables is infeasible due to the large number of system buses and the consequently high cost of measurement devices. Network operators are thus in serious need of methods that can estimate system voltages and currents with only a few measuring devices. This paper presents a novel voltage, current, and power loss… Show more

For distribution network operators to make effective decisions about real-time applications, they should have complete knowledge of all system variables. However, measuring all variables is infeasible due to the large number of system buses and the consequently high cost of measurement devices. Network operators are thus in serious need of methods that can estimate system voltages and currents with only a few measuring devices. This paper presents a novel voltage, current, and power loss estimation technique for distribution networks characterized by a high level of distributed generation (DG) penetration. The proposed method is based on online measurements from smart meters (SMs) placed at a few selected locations in addition to the measurements from DGs production meters; the estimation is derived without any pseudo measurements. The ingenuity of the proposed technique is that the SM locations are dependent on the network topology only, which means that their locations remain unchanged regardless of penetration levels and/or DG injection points. The proposed technique also includes consideration of variations in X/R ratios and laterals. The developed algorithm was implemented and tested on three radial distribution feeders to show the capability of the proposed technique for estimation for balanced as well as unbalanced distribution networks. The results of a comparison with the actual load flow demonstrate the accuracy and effectiveness of the new technique. Show less

Demand Response (DR) is an important tool for Independent System Operators (ISO) for reliable operation of electricity markets, and there has been considerable interest from load-side market participants to offer their services for DR provisions. In this environment, the ISO needs to develop effective mathematical models for procurement of DR so as to maximize its benefits, such as reducing the peak demand, regulating electricity price shocks, and mitigating market power. In this paper, a new… Show more

Demand Response (DR) is an important tool for Independent System Operators (ISO) for reliable operation of electricity markets, and there has been considerable interest from load-side market participants to offer their services for DR provisions. In this environment, the ISO needs to develop effective mathematical models for procurement of DR so as to maximize its benefits, such as reducing the peak demand, regulating electricity price shocks, and mitigating market power. In this paper, a new mathematical model for a Locational Marginal Price based, loss included, day-ahead, cooptimized, energy and spinning reserve market including DR provisions, is proposed. The proposed model includes a new proposition for load-side participants to submit price responsive demand (PRD) and load curtailment based DR bids simultaneously, in a unified market framework. Case studies considering DR providers participating in energy market only, in both energy and spinning reserve markets, and in spinning reserve market only, are presented, which examine the impact on system operation, market prices, and DR provider's benefits. The proposed model is tested on the IEEE Reliability Test System to demonstrate its functionalities and the results clearly justify the merits of simultaneous consideration of PRD bids and load curtailment based DR offers in a co-optimized energy and spinning reserve market. Show less

Wind energy has become one of the most cost-effective renewable sources nowadays. However, the stochastic nature associated with wind-energy production represents a great challenge for power-system operations. Therefore, probabilistic techniques are necessary to evaluate the performance of power systems with substantial amounts of wind generation. This paper presents a probabilistic based bi-level optimization approach for evaluating the impact of wind farm location and control strategy on the… Show more

Wind energy has become one of the most cost-effective renewable sources nowadays. However, the stochastic nature associated with wind-energy production represents a great challenge for power-system operations. Therefore, probabilistic techniques are necessary to evaluate the performance of power systems with substantial amounts of wind generation. This paper presents a probabilistic based bi-level optimization approach for evaluating the impact of wind farm location and control strategy on the penetration level of wind farms and electricity market prices. The bi-level optimization model is formulated as mathematical program with equilibrium constraints (MPEC) and solved by means of the NLPEC solver in the General Algebraic Modeling System (GAMS) environment. Several cases studies are presented in this paper to determine to the optimal wind generation penetration and market prices with different locations and control strategies for wind farms. Moreover, some scenarios are discussed in regards to the practical allocation of wind farms. Show less

Modeling wind generation for use in reliability assessment requires a large database of historical wind speeds so that the stochastic nature of the wind at a particular site can be accurately captured. The alternative is to use reliable stochastic simulation techniques that can replicate the desired synthetic wind power time series. This paper proposes an assessment framework that uses a Markov chain Monte Carlo (MCMC) method to enable the inclusion of wind farm modeling in conventional… Show more

Modeling wind generation for use in reliability assessment requires a large database of historical wind speeds so that the stochastic nature of the wind at a particular site can be accurately captured. The alternative is to use reliable stochastic simulation techniques that can replicate the desired synthetic wind power time series. This paper proposes an assessment framework that uses a Markov chain Monte Carlo (MCMC) method to enable the inclusion of wind farm modeling in conventional techniques for evaluating generation adequacy. The synthetic wind power time series based on the MCMC model has been verified against measured results based on consideration of statistical factors. The model presented in this paper has also been applied on the well-known Roy Billiton Test System (RBTS). As a further demonstration of the effectiveness of the proposed methodology, the reliability indices obtained using the MCMC model have been compared with those produced by the ARMA model, which is often used in reliability studies. The results indicate the effectiveness of the proposed technique for incorporating wind power into generation adequacy evaluation. Show less

Evaluation of the adequacy of generating capacity is one of the main planning challenges within the field of power system. With respect to the evaluation of power system reliability, a variety of criteria and techniques have been developed and utilized by numerous utilities over a number of decades. Of these, deterministic and probabilistic techniques are the ones widely used for the evaluation of generating capacity adequacy. Nowadays, modern power systems have emphasized the need for… Show more

Evaluation of the adequacy of generating capacity is one of the main planning challenges within the field of power system. With respect to the evaluation of power system reliability, a variety of criteria and techniques have been developed and utilized by numerous utilities over a number of decades. Of these, deterministic and probabilistic techniques are the ones widely used for the evaluation of generating capacity adequacy. Nowadays, modern power systems have emphasized the need for probabilistic techniques to address the challenges that power system undergone and ensure generation adequacy where the applicability of deterministic techniques is no longer valid.

The goal of this roadmap research paper is to provide a comprehensive and adequate overview of commonly used probabilistic techniques for generating system adequacy assessment: analytical, non-sequential, and sequential Monte Carlo simulation. The literature review presented in this paper, which includes theories, methodologies, analyses, and discussions, aims to provide useful information to planners or developers who endeavor to assess the reliability of existing power generation systems and plan for future generating capacity additions. Moreover, a valuable background review assembled from different sources is expected to serve students and researchers who are interested in studying in this area. Show less

This article focuses on offline residential load management in a developing country. This load management is based on scheduling linear load models under the stochastic weather conditions. The weather condition is modeled using the probability theory and Monte Carlo simulation. The seasonality effect, the type of day, and the stochastic hourly variation of weather conditions are considered as factors governing load management.

This paper presents a novel fault current management (FCM) technique for radial distribution systems with embedded inverter-based distributed generators (IB-DGs). At the point of connection to a power system, many distributed generators (DGs) require power electronic (PE) interfaces, which are normally idle during faults. The proposed FCM method employs these PE interfaces for control of the fault current. For this purpose, operation of IB-DGs is modified to FCM mode at the moment of fault and… Show more

This paper presents a novel fault current management (FCM) technique for radial distribution systems with embedded inverter-based distributed generators (IB-DGs). At the point of connection to a power system, many distributed generators (DGs) require power electronic (PE) interfaces, which are normally idle during faults. The proposed FCM method employs these PE interfaces for control of the fault current. For this purpose, operation of IB-DGs is modified to FCM mode at the moment of fault and new current references are applied. Of the two controllable parameters of the IB-DG output current-current magnitude and current phase angle-the current phase angle is chosen as the means of controlling the fault current magnitude. The reference current phase angle is calculated based on the relation between the fault current elements and their phase angles. As a result of this novel operation, IB-DGs with larger capacity can be connected at different locations of the system without affecting the fault current magnitude. Also, implementing this technique in smart grids is economically proven, since the asset of power system which have been designed for normal operation are employed to manage the fault current magnitude. Moreover, possibilities of synchronization problems are reduced by keeping IB-DGs connected to the system at all the time. The evaluation of the proposed FCM technique using the standard IEEE 33-bus distribution system demonstrates the effectiveness of the proposed method for managing the fault current magnitude. Show less

The increasing interest in smart home technologies has created a need for a comprehensive literature survey. This article reviews the goals of a smart home energy management system, along with related definitions, applications, and information about the manufacturing of its components. The challenges associated with smart home energy management systems and possible solutions are examined, and the energy factors that contribute to a customer's electricity bill are discussed. A number of price… Show more

The increasing interest in smart home technologies has created a need for a comprehensive literature survey. This article reviews the goals of a smart home energy management system, along with related definitions, applications, and information about the manufacturing of its components. The challenges associated with smart home energy management systems and possible solutions are examined, and the energy factors that contribute to a customer's electricity bill are discussed. A number of price schemes and the load models needed for solving related scheduling optimization problems are also presented, including a review of the literature related to energy management system scheduling with respect to its control, automation, and communication. Show less

This paper presents a novel probabilistic distribution load flow (PDLF) algorithm to study the effect of connecting a wind turbine (WT) to a distribution system. This probabilistic approach is used to capture the stochastic behavior of the generation of WTs. Three different models of WTs are developed to be embedded in the PDLF. Consequently, a probabilistic approach to evaluate the impact of wind penetration into distribution systems is developed. Furthermore, the effect of WT penetration on… Show more

This paper presents a novel probabilistic distribution load flow (PDLF) algorithm to study the effect of connecting a wind turbine (WT) to a distribution system. This probabilistic approach is used to capture the stochastic behavior of the generation of WTs. Three different models of WTs are developed to be embedded in the PDLF. Consequently, a probabilistic approach to evaluate the impact of wind penetration into distribution systems is developed. Furthermore, the effect of WT penetration on feeder losses, voltage profile and substation powers is presented. Show less

This article presents a new algorithm for analyzing the effects of wind generation uncertainties on short-term power system operation. Monte Carlo simulation is used to obtain a set of wind generation scenarios, and then the scenario reduction algorithm is applied to obtain a reduced set of scenarios. These reduced scenarios are then incorporated into the unit-commitment problem formulation with a locational marginal price based electricity market settlement and a dispatch model to examine the… Show more

This article presents a new algorithm for analyzing the effects of wind generation uncertainties on short-term power system operation. Monte Carlo simulation is used to obtain a set of wind generation scenarios, and then the scenario reduction algorithm is applied to obtain a reduced set of scenarios. These reduced scenarios are then incorporated into the unit-commitment problem formulation with a locational marginal price based electricity market settlement and a dispatch model to examine the effects of wind generation on electricity market prices, load cleared, social welfare, and system capacity. Show less