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IET Generation, Transmission and Distribution (17518687) 19(1)
Peak load management is a pivotal aspect of power generation and distribution, representing one of the primary challenges for power companies. A key feature of smart grids is their capability to manage available resources effectively to mitigate peak load while accounting for the inherent uncertainties in load demand and the generation of all renewable energy sources. Thereby, this paper proposes a two-stage coordination approach that integrates price-based demand response (PBDR) and energy storage systems, encompassing Battery Energy Storage Systems (BESS) and Compressed Air Energy Storage (CAES). This approach integrates CAES with BESSs to optimise the charging and discharging processes while minimising degradation costs. Specifically, it aims to address the substantial degradation expenses of BESSs by strategically utilising CAES as a complementary storage solution. The objective is to minimise operational costs while controlling peak demand load in smart microgrids. Moreover, to simultaneously address the inherent uncertainties associated with the demanded load and the generating power of renewable energy sources, a method incorporating scenario generation and reduction is introduced to improve scheduling accuracy and enhance the reliability of energy management. To tackle this multifaceted challenge, a novel scenario-based Developed Two-Stage Interval Optimisation (DTSIO) model has been proposed to effectively address uncertainty. By employing the scenario generation method in conjunction with the k-means technique to reduce scenarios with low probabilities of occurrence, the analysis process is optimised for better problem-solving efficiency. The proposed model's efficacy is validated through its implementation on a 33 and 69 bus microgrid, showcasing its ability to enhance profitability, manage peak load, reduce reliance on the upstream grid, and lower carbon dioxide emissions. © 2025 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
IET Generation, Transmission and Distribution (17518687) 18(20)pp. 3234-3246
In response to growing reliance on electricity and gas systems, this paper introduces a stochastic bi-level model for the optimized integration of these systems. This integration is achieved through sizing and allocating of power-to-gas (P2G) and gas-to-power (G2P) units. The first level of the model focuses on decisions related to P2G and G2P unit installations, while the second level addresses optimal system operation considering decisions made from first level and stochastic scenarios. The primary aim is to enhance energy-sharing capabilities through coupling devices and mitigate wind generation curtailment. An economic evaluation assesses the model's effectiveness in reducing costs. N − 1 contingency analysis gauges the integrated system's ability to supply load under emergency conditions. Two new indices, performance of the electricity system and performance of the natural gas system, are proposed for N − 1 contingency analysis. These indices quantify the proportion of the supplied load to the total load, thereby illustrating the system's capacity to meet demand. For numerical investigation, the proposed model is applied to a modified IEEE 14-bus power system and a 10-node natural gas system. Numerical results demonstrate a 9.426% reduction in investment costs and a significant 10.6% reduction in wind curtailment costs through proposed planning model. © 2024 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
IEEE Transactions on Transportation Electrification (23327782) 10(4)pp. 8235-8245
In this article, a transactive-based scheduling approach is proposed to optimize electric vehicle (EV) charging/discharging scheduling taking into account the technical requirements of EVs with different state-of-charge (SOC) levels and EV owners' preferences. In the proposed approach, an EV aggregator (EVA) solves an optimization problem to determine the charging/discharging schedule of each individual EV in the EV Parking Lot (PL) in which the response curves of individual EVs are used to consider the EV owners' charging/discharging preferences. Then, the EVAs provide their optimum day-ahead bids to the corresponding DSO based on calculated distribution locational marginal prices (DLMPs). The DSO's transactive market-clearing procedure is simulated to iteratively calculate DLMPs in the local distribution area (LDA) nodes. The Monte Carlo (MC) scenarios are used to model the uncertainties associated with the EVs' parameters and the driving behavior of the EV owners. Also, the robust optimization method is used to model the uncertainties associated with LMPs of the transmission network (TN) bus, distributed renewable energy resources (DRERs), and load demand. The proposed model is implemented on the modified IEEE-33 node distribution system and the effectiveness of the model is investigated and presented. © 2024 IEEE.
IEEE Transactions on Power Systems (08858950) 38(2)pp. 1894-1905
In this paper, a robust distribution system expansion planning (DSP) approach is presented to supply the load growth locally and move toward nearly zero energy local distribution areas (LDAs). In the proposed approach, a distribution system operator (DSO) is responsible for secure and optimum operation of LDAs. Therefore, investors on distribution system upgrades use this approach to maximize the profit on investments by determining the installation year of new distribution feeders and energy resources, distributed energy resource (DER) placements and sizes considered by corresponding DSOs. The accurate AC power flow solution is used and mathematical methods are developed to model the DSP as a quadratically constrained programming (QCP) problem. The Benders decomposition is applied to investigate the reliability and the optimality of the proposed plan and correspondingly modify the investment plan as required. The uncertainty of renewable DER forecast errors, locational marginal price (LMP) of an LDA at a transmission bus, and transactive power associated with a load bus is modeled using robust optimization. The proposed transactive DSP (TDSP) approach is implemented on the IEEE 33-bus distribution test system and the results are analyzed and validated. The proposed numerical results show the optimality and the robustness of the proposed approach. © 1969-2012 IEEE.
IET Renewable Power Generation (17521416) 16(15)pp. 3368-3383
The electric industry is developing towards a more efficient, reliable, and resilient electric power network. In this way, utilizing distributed energy resources (DERs), especially renewable DERs (RDERs) are a paradigm change. DERs offer many advantages in power systems, including transmission loss reduction, environmental benefits of RDERs, and enhancement of security, reliability, and resiliency of the network. However, high penetration of DERs increases uncertainty and challenges the efficient and reliable operation of the power system. This paper provides a thorough review of the transactive distribution platform which is essential to address the aforementioned challenges. This distribution platform includes a transactive distribution system operator providing a seamless and coordinated control to dynamically balance supply and demand and follow uncertain generations of RDERs. Indeed, this review paper highlights the capability of transactive energy (TE) by considering its key aspect in providing energy sharing opportunities for the integration of DERs into smart grids (SGs). TE is acombination of economic and control methods that enable optimum, reliable, sustainable, and efficient operation of SGs. Furthermore, a fully transactive framework offers more choices for DERs to control and manage the energy transactions in the retail market, as well as improves the inter operability among various market players. © 2022 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Kabiri renani, Y. ,
Ehsan, M. ,
Shahidehpour, M. ,
Fotuhi-firuzabad, M. ,
Mohammadi-ivatloo, B. ,
Wang, X. IET Generation, Transmission and Distribution (17518687) 13(21)pp. 4987-4997
The main motivation of this study is to address the challenges due to high penetration of renewable distributed energy resources (DERs) and efficiently benefit from DERs in distribution system planning (DSP). This paper considers a decentralized enhanced platform for DSP which is coordinated with bulk power system planning (PSP) to keep the optimality and security of the whole power system. In the proposed coordinated approach, distribution system operators (DSOs) plan and operate DERs to upgrade their local distribution areas (LDAs), supply forecasting local load growth, and avoid or defer costly generation and transmission expansion planning at the bulk power system. The proposed DSP model consists of two main loops pertaining to the DSO's planning and operation in the first loop and the ISO's simulated operation in the second loop. The Benders decomposition (BD) is employed to iteratively solve the problems. The robust and stochastic programming are used for modelling uncertainties. The DSP problem is modelled as a mixed-integer linear problem (MILP). The CPLEX solver in GAMS is applied to the modified 24-bus IEEE RTS in a 10-year horizon for numerical validation. The results show the performance of the proposed approach in reducing the total cost of supplying growing loads. © The Institution of Engineering and Technology 2019.
IEEE Transactions on Smart Grid (19493053) 9(6)pp. 6692-6701
Distribution system operator (DSO) has traditionally been responsible for the reliable operation of power distribution systems. The advent of distributed energy resources (DERs) and microgrids in distribution networks has required a new platform for DSOs. The new DSO, which is for the most part an independent agent, is responsible for aggregating a widely dispersed DERs (which include small thermal generation units, energy storage, and demand response) and flexible loads in electricity markets. DSO coordinates and balances the transactive dispatch of supply and demand at the distribution level and links wholesale and retail electricity markets. In this paper, a framework for the day-ahead transactive market is proposed which includes end-to-end power system participants starting from the bulk power ISO and ending at DSO, which includes the management of retail customers with small loads. In this paper, DERs are considered in a local distribution area (LDA). The day-ahead transactive scheduling of LDA is modeled as an MILP and solved using the CPLEX solver. This paper offers numerical results considering a DSO that is responsible for the optimal and secure operation of LDA with microgrids. The simulation results show that the proposed DSO framework in a transactive market can efficiently reduce the supply cost of LDA and increase the GenCos' payoff considering the optimal power exchange with the ISO. © 2010-2012 IEEE.
IEEE Transactions on Sustainable Energy (19493029) 8(3)pp. 1260-1268
In this paper, a self-generation scheduling method for a power generation company (GenCo) with renewable generation units is presented. In the proposed method, locational market prices (LMPs) are calculated using the incomplete information on competing market participants by simulating the ISO's market clearing program and considering the effect of physical limitations of transmission lines. The errors associated with forecasted LMP and renewable production are modeled in the GenCo's generation scheduling using a robust optimization approach. The scheduling problem is modeled as a mixed-integer linear programming which is solved by a CPLEX solver in GAMS. An eight-bus system is employed to illustrate the applications of the proposed method. The numerical results show the efficiency of proposed method to reduce the GenCo's financial risks pertaining to uncertain parameters in a competitive electricity market. © 2017 IEEE.
Kabiri renani, Y. ,
Abyaneh, H.A. ,
Sadeghi s.h.h., ,
Dezaki, H.H. ,
Nafisi h., ,
Talebi a., H.A. pp. 89-94
In this paper, the effect of PV/FC hybrid power generation system on total line loss of distribution network has been studied. Studies have been conducted on a real life 20 kV distribution network. A DPL (DIgSILENT Programming Language) code is developed to analyze the effect of the PV/FC hybrid system on total line loss in distribution network. Simulations, in three loading conditions and by considering worst environmental conditions (cloudy weather, at nights, etc) that output power of PV system is zero have been done. Sample distribution network has been considered in two structures: 1-sample distribution network by PV system as DG and 2-same distribution network but by PV/FC hybrid power system as DG. The Simulation results illustrate the effectiveness of PV/FC hybrid system in order to decrease the total line loss. ©2010 IEEE.
Advances in Electrical and Computer Engineering (18447600) 10(4)pp. 143-148
Development of distribution network and power consumption growth, increase voltage drop on the line impedance and therefore voltage drop in system buses. In some cases consumption is so high that voltage in some buses exceed from standard. In this paper, effect of the fuel cell and photovoltaic hybrid system on distribution network for solving expressed problem is studied. For determining the capacity of each distributed generation source, voltage limitation on the bus voltages under different conditions is considered. Simulation is done by using DIgSILENT software on the part of the 20 kV real life Sirjan distribution system. In this article, optimum location with regard to system and environmental conditions are studied in two different viewpoints. © 2010 AECE.
In this paper, the effect of fuel cell (FC) unit as distributed generation, on network bus voltages has been studied. Under different loading conditions, considering the voltage limit which is determined by the standard, the minimum and maximum power that FC unit can inject to the network has been calculated. Nowadays, participate in competitive market for the renewable energy sources are not possible. So in this paper, two supportive strategies have been supposed. These strategies, applied to a 77 buses real life distribution network and the results have been compared.
