Capacity Of Distributed Energy Resources Research Articles

Integrated Active and Reactive Power Control Methods for Distributed Energy Resources in Distribution Systems for Enhancing Hosting Capacity

Recently, there has been a significant increase in the integration of distributed energy resources (DERs) such as small-scale photovoltaic systems and wind turbines in power distribution systems. When the aggregated outputs of DERs are combined, excessive reverse current may occur in distribution lines, leading to overvoltage issues and exceeding thermal limits of the distribution lines. To address these issues, it is necessary to limit the output of DERs to a certain level, which results in constraining the hosting capacity of DERs in the distribution system. In this paper, coordination control methodologies of DERs are developed and executed to mitigate the overvoltage and overcurrent induced by DERs, thereby increasing the hosting capacity for DERs of the distribution system. This paper proposes three coordinated approaches of active and reactive power control of DERs, namely Var Precedence, Watt Precedence, and Integrated Watt and Var Control. The Var and Watt Precedence prioritizes reactive power for voltage (Q–V) and active power for current (P–I) to address network congestion, thereby enhancing hosting capacity. Conversely, the Integrated Var and Watt Precedence propose a novel algorithm that combines four control indices (Q–V, P–V, Q–I, and P–I) to solve network problems while maximizing hosting capacity. The three proposed methods are based on the sensitivity analysis of voltage and current to the active and reactive power outputs at the DER installation locations on the distribution lines, aiming to minimize DER active power curtailment. Each sensitivity is derived from linearized power equations at the operating points of the distribution system. To minimize the computation burden of iterative computation, each proposed method decouples active and reactive power and proceeds with sequential control in its own unique way, iteratively determining the precise output control of distributed power sources to reduce linearization errors. The three proposed algorithms are verified via case studies, evaluating their performance compared to conventional approaches. The case studies exhibit superior control effectiveness of the proposed DER power control methods compared to conventional methods when issues such as overvoltage and overcurrent occur simultaneously in the distribution line so that the DER hosting capacity of the system can be improved.

Simulation-based probabilistic-harmonic load flow for the study of DERs integration in a low-voltage distribution network

<abstract><p>The integration of distributed energy resources (DERs) and, therefore, power electronic devices into distribution networks leads to harmonic distortion injection. However, studying harmonic distortion solely through deterministic approaches presents challenges due to the inherent random behavior of DERs. This study introduced a strategy that leverages PowerFactory's harmonic load flow tool. By combining it with Python co-simulation, probabilistic load flows can be developed. These load flows utilize current sources to represent harmonic distortion emitters with predefined harmonic spectra. The proposed strategy was implemented on a real network, where two different capacities of DERs were integrated at various locations within the network. The distributions for the total harmonic distortion of voltage ($ THD_{v} $) and the total harmonic distortion of current ($ THD_{i} $) were obtained 24 hours a day in nodes and lines of the network. The procedure allowed considering the uncertainty associated to the DERs integration in distribution networks in the study of harmonic distortion, which, speaking from a simulation approach, is scarce in the literature.</p></abstract>

Bi-Level Optimization Model for DERs Dispatch Based on an Improved Harmony Searching Algorithm in a Smart Grid

To satisfy the large-scale grid-connected demands of distributed energy resources (DERs), a bi-level optimization model is proposed for private DER dispatch managed by a virtual power plant (VPP) in a smart grid environment in this paper. The optimization models of the upper and lower layers serve as the planning layer and the operational layer, respectively, wherein the upper optimization model is mainly aimed at the optimization allocation of DERs under an unchanged network topology, and the lower-level optimization model is mainly responsible for the optimization of the distributed network topology from the optimization results of the upper layer. An improved harmony searching algorithm (HSA) is then applied to resolve the model through continuous iterations and communications between the upper and lower levels until an expected aim is achieved, which can satisfy the aim demand of the upper and the lower levels at the same time. Finally, six optimization scenarios are planned and selected in order to evaluate the performance of the bi-level optimization strategy in the IEEE33 bus distribution system and the 69-bus distribution system, and the optimized results show that the proposed method can effectively improve the grid-connected capacity of DERs and their system performance, and are more flexible in facing a growing ambient smart environment.

Decentralized and Coordinated V-f Control for Islanded Microgrids Considering DER Inadequacy and Demand Control

This paper proposes a decentralized and coordinated voltage and frequency (V-f) control framework for islanded microgrids, with full consideration of the limited capacity of distributed energy resources (DERs) and V-f dependent load. First, the concept of DER inadequacy is illustrated with the challenges it poses. Then, a decentralized and coordinated control framework is proposed to regulate the output of inverter-based generations and reallocate limited DER capacity for V-f control. The control framework is composed of a power regulator and a V-f regulator, which generates the supplementary signals for the primary controller. The power regulator regulates the output of grid-forming inverters according to the real-time capacity constraints of DERs, while the V-f regulator improves the V-f deviation by leveraging the load sensitivity to V-f. Next, the static feasibility and small signal stability of the proposed method are rigorously proven through mathematical formulation and eigenvalue analysis. Finally, a MATLAB-Simulink simulation demonstrates the functionalities of the control framework. A few goals are fulfilled within the decentralized and coordinated framework, such as making the best use of limited DERs' capacity, enhancing the DC side stability of inverter-based generations, and reducing involuntary load shedding.

Approaches to Building AC and AC–DC Microgrids on Top of Existing Passive Distribution Networks

The process of building microgrids on top of existing passive distribution networks warrants a multi-criteria analysis. Besides the calculation of the investment outlays needed for the modernization of distribution networks, such an analysis covers an assessment of the technological and economic effects of building microgrids. The resulting effects depend on the topology and configuration of distribution networks, specific microgrid features, the choice of the current type for the entire microgrid or its individual parts, the methods of connecting distributed energy resources (DERs), the availability and maturity of information and communications technology (ICT) infrastructure, and other factors. Comprehensive input data allow for designing an optimal microgrid configuration, but the main technological and economic effects are determined by the algorithms of operation and the parameter settings of the automatic control system (ACS) and the protection system. The known approaches to designing microgrids focus on addressing basic tasks while minimizing the investment required for their implementation. The above is fully justified when constructing new microgrids, but building microgrids on top of existing distribution networks, given the uniqueness of their topology and configuration, does not allow the use of standardized solutions. The development of approaches to the design of microgrids under such constraints, with minimized investment in the modernization of existing distribution networks, is an urgent task. The use of different types of current for individual microgrid segments determines the choice of the particular ACS and protection system, which depends on the availability of information and communications technology infrastructure. This article contributes a review of approaches to designing AC and AC–DC microgrids so as to maximize their technological and economic effects. We review techniques for analyzing the existing distribution networks aimed at choosing the type of current for the entire microgrid or its individual parts, the optimal points for the connection of microgrids to distribution networks, and the mix and capacity of DERs, with such choices informed by the conditions of the switching devices and information and communications technology infrastructure. This article presents the results of the analysis of approaches to choosing the optimal configuration of microgrids, microgrid ACS, and protection system, with an evaluation of the technological and economic effects subject to the minimization of investment in the modernization of the existing distribution networks.

Optimization of Distributed Energy Resources in Distribution Networks: Applications of Convex Optimal Power Flow Formulations in Distribution Networks

The increasing penetration of distributed energy resources (DER) has imposed several challenges in the analysis and operation distribution networks. In the last decade, the implementation of battery energy storage systems (BESS) in electric networks has caught the interest in research since the results have shown multiple positive effects when deployed optimally. However, a complex formulation of the optimization problem regarding DER implementations can easly become nonconvex, thus limiting the scope of the results (quality) and affecting the computational efficiency. In this paper, convex formulations of the optimal power flow (OPF) problem for DER (PV and BESS) installations in San Andres distribution network were implemented to minimize power losses. Four main simulation cases were stablished covering convex power flow analysis, convex optimal power flow to locate and size dispatchable and nondispatchable DER (PV) with demand and irradiation profiles, and the inclusion of aggregated and distributed PV and BESS systems. The computational realization of those formulations was made with three different software packages: CVX in python, CPLEX, and MATLAB (MATPOWER/PSO). The results show that installing DER capacity (both PV and/or BESS) can substantially improve the power losses in distribution networks, especially if considered distributed instead of aggregated, achieving reductions up to 75% for power losses and up to 57% for conventional generation utilization. Besides power losses, it was observed that optimal DER (PV and BESS) implementations behaved similarly as demand response signals do, potentially increasing economic benefits for DISCOs. In terms of computational efficiency, convex formulations help substantially to reduce computation times, especially if scalability is to be considered when distributed DER installations were studied.

Value of distribution system information for DER deployment

AbstractIntegration of Distributed Energy Resources (DERs) in power systems exacerbates the existing information problems between power utilities and regulators. DER policies oblivious to the trilemma of information asymmetry between power utilities, DER aggregators, and regulators result in distorted price signals to DER investors, and socially inefficient DER roll‐out. Therefore, in this paper, a game‐theoretic approach is proposed for modeling information asymmetry in distribution network information and consumer data between the DER aggregators and the power utilities. The proposed framework is based on Single Leader Single Follower (SLSF) games, reformulated as Mathematical Programs with Equilibrium Constraints (MPECs), and solved using the Scholtes's relaxation technique. The results, based on the 7‐bus Manhattan power network, show that unless the DER aggregators have complete information about the distribution network characteristics, the welfare along with the realized installed capacity of DERs in the system decreases. Moreover, progressively decreasing DER investment costs alleviate the effects of information asymmetry, suggesting that early adopters face disproportionately high welfare losses attributed to incomplete information between the DER stakeholders. Hence, policy interventions to alleviate the rampant information problems are imperative to ensure an optimal DER roll‐out.

An analytical optimum method for simultaneous integration of PV, wind turbine and BESS to maximize technical benefits

AbstractThe present paper introduces an analytical approach for integrating distributed energy resources (DERs) and battery energy storage systems (BESSs) into power grids. The given method aims to simultaneously identify optimal buses and capacities of DERs and BESSs, with regard to the responsive load demand along with the stochastic nature of wind turbine (WT) and photovoltaic (PV) units, and then to minimize energy losses and improve voltage profiles. For this purpose, the responsive load model, the uncertainties in the WT and PV units, and the BESSs are firstly modeled. Secondly, the output curve of BESSs is obtained so that demand and supply can be balanced effectively, so as to utilize the full‐potential output of DERs. Thirdly, a set of formulation is developed for simultaneous integration of the DERs and the BESSs. This formulation reflects on different levels of loads and DERs for each period as well as each segment with their corresponding probability density. Finally, the proposed method is tested on the standard IEEE 33‐bus network. These results verify that sizing and sitting of DERs and BESSs can significantly shape the planning results of DERs and increase their penetration in the power grids at the same time.

Fast Coordination of Distributed Energy Resources Over Time-Varying Communication Networks

In this article, we consider the problem of optimally coordinating the response of a group of distributed energy resources (DERs) controlled by distributed agents so they collectively meet the electric power demanded by a collection of loads while minimizing the total generation cost and respecting the DER capacity limits. This problem can be cast as a convex optimization problem, where the global objective is to minimize a sum of convex functions corresponding to individual DER generation cost while satisfying 1) linear inequality constraints corresponding to the DER capacity limits and 2) a linear equality constraint corresponding to the total power generated by the DERs being equal to the total power demand. We develop distributed algorithms to solve the DER coordination problem over time-varying communication networks with either bidirectional or unidirectional communication links. The proposed algorithms can be seen as distributed versions of a centralized primal–dual algorithm. One of the algorithms proposed for directed communication graphs has a geometric convergence rate even when communication out-degrees are unknown to agents. We showcase the proposed algorithms using the standard IEEE 39-bus test system and compare their performance against other ones proposed in the literature.

Enhancing the unbalanced distribution network’s hosting capacity for DERs via optimal load re-phasing

Maximizing the distribution systems’ hosting capacity (HC) for distributed energy resources (DERs) is an integral part of the efforts to increase the share of renewable energy sources (RES) in electricity grids. Hence, a novel strategy is proposed in this paper to enhance the network’s HC for DERs, which considers the technical issues such as voltage unbalance caused by the high share of DERs. Through a novel three-stage optimization model, this paper shows that the HC for DERs such as solar photo-voltaics (PV), residential and public electric vehicle chargers (EVCs), and heat pumps (HPs) can be increased. The proposed approach uses a novel re-phasing strategy to determine the optimal network configuration, which can decrease the voltage unbalance, and hence the available network capacity can accommodate more DERs. In the first stage, the network’s HC for DERs is maximized without any further structural modifications on the existing network. In the second stage, the best configuration of the system is obtained to mitigate the voltage unbalance caused by the DER penetration. Finally, at the third stage and based on the obtained optimal configuration of the network, the HC of the modified system is maximized by adding more DER capacity. The results show that using the proposed re-phasing technique can improve the network’s HC for DERs, without any need to reinforce the existing network.

Operational planning of distributed energy generation for a semiconductor fabrication plant

The semiconductor industry is well known for its high resource consumption due to its clean room usage and power-intensive manufacturing technology. This is a significant financial burden for semiconductor fabrication plant owners who wish to minimize the cost needed to cover the electricity and gas loads for their daily operations. From a historical perspective, those electricity and gas cost reductions have been enabled by more energy-efficient manufacturing technologies. Due to the complexity of factors influencing the energy system of a semiconductor plant, other aspects have often been neglected and also not been studied intensively in the academic literature so far. One possibility for reducing energy costs is the integration of a microgrid as on-site distributed energy resources (DER) may offer a less cost-intensive way to supply the energy needed. Therefore, this paper seeks to answer the following research question: How much expected cost can be saved and risk mitigated at a semiconductor fabrication plant via DER? More precisely, in this paper, a microgrid at a semiconductor fabrication plant that has installed DER with combined heat and power (CHP) applications and demand response (DR) is used to simulate the expected annual energy costs under given uncertain electricity and gas prices at different installed capacity levels. A simulation-based approach is used to evaluate several DER capacity sizes. The results of the simulation show that installations of DER at a semiconductor microgrid can dominate the base case of doing nothing, considering the expected minimized cost, the expected CO2 emissions, and conditional value-at-risk (CVaR). In fact, DER can reduce the expected annual energy bill by up to 6%, whereas annual expected CO2 emissions can even be reduced by up to 22%. Moreover, with DER, a microgrid’s risk is reduced as it can react to market conditions and local demand. Additionally, the true potential of microgrid cost savings can only be enabled when DR is allowed and proves particularly effective when energy prices are more volatile.

A techno-economic analysis of distributed energy resources versus wholesale electricity purchases for fueling decarbonized heavy duty vehicles

Electric and hydrogen vehicles can help decarbonize heavy duty vehicles (HDV). Few studies examine how to meet energy requirements of decarbonized HDVs, and all assume electricity will come from centralized systems. However, decarbonized HDVs could significantly increase energy demands in areas with limited transmission access, potentially favoring deployment of distributed energy resources (DERs). In this paper, we develop an optimization-based techno-economic model that minimizes costs of meeting HDV energy demands by optimizing investments in and operations of DERs, investments in transmission interconnections, and wholesale electricity purchases. We apply it to a modeled U.S. dataset of electric HDV charging demands to quantify the deployment and value potential of three DERs — solar, batteries, and nuclear small modular reactors (SMRs) in the year 2040. For fleets of 100% electric HDVs to 60% electric and 40% hydrogen HDVs, DERs are deployed at 78% to 95% of all charging stations and meet between 24% to 30% of total HDV energy demand. Investments in DERs reduce annual costs by $647 million to $1.9 billion across all stations, while individual stations can save $20 million to over $100 million annually. SMRs make up over 99% of total deployed DER capacity, indicating significant potential for SMR deployment in this emerging market. Widespread DER deployment is robust to capital cost uncertainty in SMRs and transmission lines, wholesale electricity prices, and other factors.

A two-stage stochastic programming model for the sizing and location of DERs considering electric vehicles and demand response

This article addresses the optimal distributed energy resources (DER) allocation and sizing into an LV distribution network (DN) considering demand response (DR) and high penetration of plug-in electric vehicles (PEV) in a two-stage stochastic programming framework. The model includes (i) economic variables related to the capital cost of the DERs capacity installed with their respective operational costs and (ii) operational technical constraints based on the AC power flow equations. The formulation estimates the distributed generation (DG) capacity in terms of apparent power, i.e., the capacity found by the model relates the active and reactive power injected from DG to the DN simultaneously. A linearization and a modified version of the genetic algorithm (GA) solve the mix-integer non-linear problem (MINLP), and the backward algorithm is applied to reduce the number of scenarios. The model is tested in the IEEE 69-bus system under 18 different scenarios of 24 h to measure the DERs capacity installed variability. Finally, the results showed that (i) the set of scenarios selected are decisive for the optimal capacity installed affecting the investment and the Grid dependence, (ii) the PEVs affect the total DERs capacity installed and the operation costs, and (iii) the reactive power provided by the DERs might supply the total reactive power demand.

Ambiguities and nonmonotonicities under prosumer power

Prosumers adopt distributed energy resources (DER) to cover part of their own consumption and to sell surplus energy. Although individual prosumers are too dispersed to exert operational market power, they may collectively hold a strategic advantage over conventional generation in selecting DER capacity via aggregators. We devise a bilevel model to examine DER capacity sizing by a collective prosumer as a Stackelberg leader in an electricity industry where conventional generation may exert market power in operations. At the upper level, the prosumer chooses DER capacity in anticipation of lower-level operations by conventional generation and DER output. We demonstrate that exertion of market power in operations by conventional generation and the marginal cost of conventional generation affect DER investment by the prosumer in a nonmonotonic manner. Intuitively, in an industry where conventional generation exerts market power in operations similar to a monopoly (MO), the prosumer invests in more DER capacity than under perfectly competitive operations (PC) to take advantage of a high market-clearing price. However, if the marginal cost of conventional generation is high enough, then this intuitive result is reversed as the prosumer adopts more DER capacity under PC than under MO. This is because the high marginal cost of conventional generation prevents the market-clearing price from decreasing, thereby allowing for higher prosumer revenues. Moreover, competition relieves the chokehold on consumption under MO, which further incentivises the prosumer to expand DER capacity to capture market share. We prove the existence of a critical threshold for the marginal cost of conventional generation that leads to this counterintuitive result. Finally, we propose a countervailing regulatory mechanism that yields welfare-enhancing DER investment even in deregulated electricity industries.

Application of precautionary and corrective energy management strategies in improving networked microgrids resilience: A two-stage linear programming

Increasing the frequency of natural hazards affecting critical infrastructures such as power systems has necessitated upgrading planning and operation strategies to cope with such an issue. This study develops a comprehensive two-stage resilient energy management strategy (TS-REMS) for networked microgrids (NMGs), exploiting the demand side flexibility and distributed energy resources capacity. The first stage of the proposed TS-REMS follows a precautionary procedure that optimizes the operation of NMGs. In contrast, the second stage applies corrective actions for improving the resilience of NMGs. Multiple uncertainties of renewable generation and system demand are considered through the scenario-based approach. The uncertainty scenarios are reduced by introducing a novel scenario reduction technique capable of dealing with a large number of scenarios. Two resilience and recovery indices are introduced to evaluate the model's effectiveness while constraining the energy exchange with the distribution feeder. Thanks to a linear model, the proposed approach benefits from computational efficiency. The simulation results demonstrate the efficiency of the proposed TS-REMS model in tackling extreme natural hazards without demanding high expenditure.

Digital at the Speed of Sunlight: Transform with Distributed Energy Resources

Distributed Energy Resources (DERs) are a primary driver requiring utilities to become more digitalized. DERs are disrupting traditional distribution utility business models, creating new opportunities in the way utilities and customers generate electricity, manage load, and finance and procure resources. With more than 33 states having clean energy action plans and a majority of Americans in all 50 states supporting the actions to move the country toward 100 percent clean energy generation by 2035, utilities are being called upon to support investment in DERs. DER capacity is expected to grow through both FERC Order 2222, which would enable DER aggregators to participate in wholesale electricity markets, and in support of electric vehicles infrastructure development. The rise of DERs in response to decarbonization and clean energy goals provides an opportunity for both utilities and developers to improve grid reliability and improve the load profile on the distribution grid. The increased penetration of DERs continues to foster greater customer participation in meeting their loads while increasing pressure on utilities to interconnect and derive value from DERs and grid‐edge assets. These complexities require a significant shift in thinking and paves the way for industry leaders to think digitally.

System Level-Based Voltage-Sag Mitigation Using Distributed Energy Resources

As the growing demand for battery energy storage systems (BESSs) generally follows the renewable energy sources (RESs) trend, the active management of BESS- and RES-based distributed energy resources (DERs) could effectively solve voltage-sag problems in active distribution systems (ADSs). DERs are typically interfaced with the grid through power-electronic inverters. They are considered power resources with adjustable active/reactive power injections that could contribute to the enhancement of the grid's performance. This article proposes a new framework for active/reactive power management of inverter-based DERs to mitigate voltage-sag problems in ADSs. The new framework utilizes a novel zonal-based voltage control algorithm for mitigating voltage-sag problems in ADSs. The algorithm identifies mitigation zones' virtual boundaries based on a proposed electrical influence intensity index that reflects the electrical connectivity of the network. A novel zone capability index (ZCI) ranks the mitigation zones according to DER capacity, zonal loading conditions, and the number of nodes within each mitigation zone. The voltage mitigation algorithm minimizes the energy injected from DERs’ inverters to achieve maximum voltage sag alleviation in each mitigation zone. This zonal-based mitigation algorithm is applied to the IEEE 33-bus distribution system under voltage-sag conditions to verify the proposed algorithm's feasibility and effectiveness.

Transmission Hosting Capacity of Distributed Energy Resources

Distributed energy resources (DERs) are transforming the operation and planning of both distribution and transmission grids. Stability impacts from the increasing generation contribution of DERs have been widely recognized in distribution systems and are emerging in transmission systems. There is a need for the development of transmission hosting capacity studies of DERs so utilities will be able to predict and prevent instabilities, reductions in reliability on the electrical grid, and create planning methodologies that enable the continued growth of DERs. This paper evaluates the impact of different modeling considerations for assessing hosting capacity of DERs in transmission systems through analysis on a 2,000-bus synthetic grid test system. The modeling considerations include transient and steady state contingencies, use of dynamic load and DER models with voltage support control, dynamic load composition, and seasonal and loading scenarios. The results demonstrate that transient stability evaluations are more limiting than steady state analysis, the use of voltage support control in DERs can increase hosting capacity in the system, and large variations in hosting capacity can be found when assessing between seasonal variations. From comparing system factors the amount of wind generation in the system was a critical factor for hosting capacity in this study.

A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids

The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency.

Optimal Distributed Energy Resources Allocation for Enriching Reliability and Economic Benefits Using Sine-Cosine Algorithm

This paper presents an optimization algorithm called sine-cosine algorithm (SCA) for optimal distributed energy resources (DERs) allocation in various configurations of radial distribution networks. This study is demonstrated in two statuses to find the optimal locations and sizes of DERs to be installed on the distribution system. First status; the most candidate locations for connecting DERs are suggested by using the loss sensitivity factor theory and the proposed SCA is applied to select the optimal capacities of DERs. Second status; the SCA is used to determine both the optimal locations and sizes of DERs. The positive impact of DERs on distribution systems reliability has been investigated in addition to the system power losses and bus voltages. The fitness function is to maximize the savings produced by not only power losses reduction but also reliability enhancement. The proposed algorithm is applied to IEEE 33 and 69-bus radial distribution networks with installing different number of DERs. The simulation results using Matlab programming environment show that the proposed methodology is viable, supporting reliability as well as fulfilling the conventional objectives such as cost minimization, voltage profile improvement, system losses reduction. A comparison between SCA and other methods is introduced to verify the superiority of SCA where SCA fulfils the maximum saving and maximum reduction of power losses equals to 61.3% and 69.2% for IEEE 33-bus and 69-bus networks, respectively.