Papers by Moein Moeini-Aghtaie
Applied Energy, 2014
h i g h l i g h t s An energy system model (OSeMOSYS) was set up based on 12 time periods per yea... more h i g h l i g h t s An energy system model (OSeMOSYS) was set up based on 12 time periods per year. Results for 2020 were compared to a TIMES-PLEXOS model with 8784 time periods. Adding operational constraints to OSeMOSYS allowed reproducing TIMES-PLEXOS results. In OSeMOSYS, capacities in 2050 differed by 24% when omitting this operating detail. Omitting this detail may result in underestimated climate change mitigation costs.
International Journal of Electrical Power & Energy Systems
2020 10th Smart Grid Conference (SGC)
Providing sufficient flexibility in modern power systems has become an unavoidable feature of sus... more Providing sufficient flexibility in modern power systems has become an unavoidable feature of sustainable energy systems. This flexibility should be supplied by different sectors and players of power systems. The role of demand especially prosumers in providing flexibility have recently been highlighted. In this regard, this paper presents a new flexibility-based algorithm for a Home Energy Management System (HEMS). The HEMS focuses on Electric Vehicles (EVs) and Electrical Energy Storage (EES) as main sources of flexibility products. Two main products, namely, positive and negative flexibility are defined as deviations from optimal energy schedules attained by the HEMS. Each flexibility’ offer related to the device is offered at a specific price in the flexibility platform. Final flexibility plans are extracted after running a linear optimization model. It has been shown that these products can properly enhance the flexibility level of distribution systems and simultaneously impose no additional cost for prosumers.
2019 Smart Grid Conference (SGC), 2019
With high growth rate of demand for energy in different societies, the need for energy resources ... more With high growth rate of demand for energy in different societies, the need for energy resources has been increased significantly. This has resulted in introduction of new energy resources, i. e. renewable energy resources in generation sector of energy systems. However, the intrinsic features of these energy resources call for higher flexibility in different sectors of energy systems. Flexibility in a comprehensive sense tries to cover the amount of imbalance between production and demand in energy systems. This paper has attempted to introduce the concept of operational flexibility in microgrids and it also has presented a step-by-step algorithm to assess this operational index based on a linear optimization model. This study focuses on the thermal flexibility provided by combined heat and power (CHP) units to address the ability of these units to meet the difference between production and demand in microgrids and it has been implemented on a test system.
Scientia Iranica, 2020
Increases in tightening the correlation of gas and electricity systems (G&ES), affected by divers... more Increases in tightening the correlation of gas and electricity systems (G&ES), affected by diverse factors, ranging from anthropogenic climate change to the advent of new conversion/generation technologies, have remarkably brought the co-expansion of G&ES using a new concept, the socalled Energy Hub (EH), as well as the potential of storage systems into focus. To assess the effectiveness of EH approach and the role of storages in the coordinated plans of G&ES, this paper proposes a comprehensive EH-based planning model for co-expansion of G&ES supply chains with respect to the role of gas storage systems (GSSs). As a mixed-integer linear programming (MILP) problem, the model is applied to a real large-scale case study, i.e. the Iranian G&ES and is solved via the GAMS package. The simulation results reveal that incorporation of the interactions existing between G&ES into their planning problems in the framework of an EH can reach more flexible, realistic and optimal expansion plans compared with their traditional integrated expansion planning methods. Furthermore, findings show that the involvement capacities of GSSs provides the opportunity of optimal matching of demand with supply by increasing the productivity of the gas pipelines, allowing technically and economically sensible long-term management of gas supply systems.
The transmission network expansion planning is necessary for supplying the future needs, consider... more The transmission network expansion planning is necessary for supplying the future needs, considering load growth. Furthermore, in restructured environments, transmission lines provide the required infrastructure for creating a competitive environment. In recent years, there has been a significant advancement in storage technologies. This advancement leads to using energy storage systems to postpone the construction or replacement of transmission lines. Therefore, in this paper, the problems of transmission expansion planning and energy storage systems deployment are investigated simultaneously. Considering the presence of storage devices and their effect on network operation cost, in this paper, the operation cost is modeled as an independent objective function along with investment cost. Moreover, the problems of transmission and storage expansion planning are modeled as a tri-objective optimization problem with the objectives of reducing costs and increasing the social welfare index in the power market. The multiobjective shuffled frog leaping evolutionary algorithm is used to solve these problems. The presented model for expansion planning is implemented and analyzed on IEEE 24-bus test system in the presence and absence of energy storage systems, and the effect of change in the price of energy storage systems is studied. The results of this research show that as the technology advances and the storage costs decrease, energy storage systems can play a pivotal role in reducing expansion planning costs of the power network and improving market-based indices in the restructured environment.
Iet Generation Transmission & Distribution, Jun 10, 2022
Increasing the intermittent outputs of renewable energy sources (RESs) has forced planners to def... more Increasing the intermittent outputs of renewable energy sources (RESs) has forced planners to define a new concept named flexibility. In this regard, some short-and long-term solutions, such as transmission expansion planning (TEP) and energy storage systems (ESSs) have been suggested to improve the flexibility amount. A proper optimization procedure is required to choose an optimal solution to improve flexibility. Therefore, a mixed-integer linear programming (MILP) direct-optimization TEP versus ESSs coplanning model is presented in this paper to enhance power system flexibility. In doing so, a novel RES-BESS-based grid-scale system flexibility metric is proposed to investigate the improvement of flexibility amount via ESSs modules in the numerical structure. In this paper, a novel repetitive fast offline method has been proposed to quickly reach the desired amount of flexibility by defining an engineering price/benefit trade-off to finally find the best investment plan. Also, multiple uncertainties associated with wind farms and demanded loads and a practical module-type battery energy storage system (BESS) structure for each node are defined. The proposed model is applied to the modified IEEE 73-bus test system including wind farms, where the numerical results prove the model efficiency as BESS impacts on flexibility, investment plans and power system economics. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
In modern power systems, technical virtual power plants (TVPPs) play an important role enabling p... more In modern power systems, technical virtual power plants (TVPPs) play an important role enabling presence of distributed energy resources (DERs) in electricity markets. In this paper, strategy of using the available energy resources for a TVPP is put under investigation. A new optimization framework is presented for problem of TVPP energy scheduling by taking operational constraints of distribution network into account. In the proposed model, photovoltaic (PV) units and micro turbines along with the electric vehicles (EVs) are scheduled in such a way that the profit of TVPP owner would be maximized. The uncertainty in output generation of PV units is modeled by adopting fuzzy c-means (FCM) clustering algorithm. Also, the predicted amount of the load of TVPP is included in the scheduling problem using scenario-based approach. The model is mathematically formulated in the format of mixed integer linear programming which guarantees obtaining the global optimum solution. The capability of the model is examined through its implementation on the IEEE RBTS-Bus5 distribution test system. The obtained results demonstrate the applicability and effectiveness of the proposed model.
Iet Generation Transmission & Distribution, Jul 20, 2023
This paper presents a two‐stage adaptive robust optimization framework for day‐ahead energy and i... more This paper presents a two‐stage adaptive robust optimization framework for day‐ahead energy and intra‐day flexibility self‐scheduling of a technical virtual power plant (TVPP). The TVPP exploits diverse distributed energy resources’ (DERs) flexibility capabilities in order to offer flexibility services to wholesale flexibility market as well as preserving the distribution network's operational constraints in the presence of DER uncertainties. The TVPP aims at maximizing its profit in energy and flexibility markets considering the worst‐case uncertainty realization. In the proposed framework, the first stage models the TVPP's participation strategy in day‐ahead energy market and determines the DERs’ optimal energy dispatch. The second stage addresses the TVPP's strategy in intra‐day flexibility market to determine the DERs’ optimal flexibility capability provision by adjusting their energy dispatch for the worst‐case realization of uncertainties. The uncertainty characteristics associated with photovoltaic units, electric vehicles, heating, ventilation and air conditioning systems, and other responsive loads as well as the transmission network's flexibility capability requests are considered using an adaptive robust approach. Adopting the duality theory, the model is formulated as a mixed‐integer linear programming problem and is solved using a column‐and‐constraint generation algorithm. This model is implemented on a standard test system and the model effectiveness is demonstrated.
Active distribution network (ADN) expansion planning by modeling network active management is add... more Active distribution network (ADN) expansion planning by modeling network active management is addressed in this paper. In this regard the expansion of distributed energy resources (DERs) and distribution network assets are jointly planned. In the proposed model active management is applied to efficiently utilize the DERs in the planning problem and alleviated the uncertainties. In this paper energy storage systems (ESSs) as an important DER are utilized in active management framework. To model active management of the network, based on load and renewable energy resources’ behavior, some operating levels are regarded for each planning time stage. The objective is to minimize the net present worth of investment, maintenance and operation costs for all planning stages and operating levels. As the problem is solved the expansion plans of network alternatives including feeders, transformers, and substations as long as DERs including micro turbines, wind turbines and ESSs are extracted. Furthermore, the optimal operations of the network and DERs are obtained through the operating levels. Associated uncertainties are considered using a correlated scenario based approach. The problem is mathematically modeled in the form of mixed integer linear programming (MILP).
In this paper the reliability of distribution network is modeled in joint multistage expansion pl... more In this paper the reliability of distribution network is modeled in joint multistage expansion planning of distribution network assets and distributed generations (DGs). The imposed costs due to network reliability weakness are considerable in the distribution level. Therefore in the proposed model distribution network operator (DNO) considers the costs associated with load interruptions in the planning problem. In this regard, reliability evaluation of the network is modeled in the joint multistage distribution network expansion planning (MDNEP) problem in an integrated manner while the network topology is unknown until the planning problem is not solved. In the proposed joint MDNEP problem the investment plan of network assets including feeders, substations and transformers as well as DGs are jointly obtained. Involving the reliability costs in the joint MDNEP problem is based on linearized mathematical model for calculating reliability index of expected energy not served (EENS). Therefore the proposed model is formulated in the form of mixed integer linear programming (MILP) which can be efficiently solved using off-the-shelf software.
IEEE Transactions on Smart Grid, Sep 1, 2019
Expanding the electricity market into the retail domain calls for inexpensive mass-produced smart... more Expanding the electricity market into the retail domain calls for inexpensive mass-produced smart devices that enable the small customers to participate in local energy transactions by managing the energy production/consumption and submitting buy/sell bids to the market. In this context, this paper presents a mathematically proven as well as practical approach for bidding of an autonomous smart transactive agent in local energy markets. To reach this goal, behaviors of both riskneutral and risk-averse agents selling energy to the market are modeled taking into account expected profit and risk criteria. Based on this modeling procedure, an optimal multi-step quantity-price bidding strategy is extracted. This paper mainly contributes by: (i) introducing the effective metrics and criteria for evaluating a bidding strategy, (ii) providing all theorems and lemmas required for reaching an optimal bidding strategy for either a risk-neutral or risk-averse agent, (iii) evaluating and presenting the developed approach for different market environments. The developed methodology is shown to be effective in practical applications especially for local markets. Index Terms-Bidding strategy, transactive market, electricity market, local market, risk analysis. I. NOMENCLATURE A. Constants N Number of allowed steps in each bid. max q Maximum production capacity.
IEEE Transactions on Industry Applications, 2021
Industrial loads play an important role in the success of demand response programs (DRPs). Howeve... more Industrial loads play an important role in the success of demand response programs (DRPs). However, these programs may compromise the consumers' convenience, which can overshadow their real-world practicality. In response, this article provides a two-level decision-making tree approach to effectively determine the participation abilities of different industrial processes in DRPs considering various features and abilities of these customers. The level I of this framework introduces several classifying variables by which a basic criterion is extracted to classify different industrial processes applying the analytic hierarchy process (AHP). A participation factor is then introduced in level II of the suggested decision tree to estimate the participation level of different classes attained in level I. Finally, a desirability coefficient is formulated, offering the system operators an efficient indicator to verify the attractiveness of different incentive-based programs in the viewpoint of industrial customers. Implementing the presented framework on industrial customers of a region in Iran, it is shown that applying this method lends the decision-makers a hand in practically and effectively introducing DRPs for industrial customers.
IEEE Transactions on Power Systems, Nov 1, 2019
This paper aims at proposing a mixed-integer linear formulation to incorporate reliability orient... more This paper aims at proposing a mixed-integer linear formulation to incorporate reliability oriented costs into the expansion planning model of electricity distribution networks. In this respect, revenue lost associated with the undelivered energy caused by network interruptions, as well as costs incurred by the widely-used reward-penalty regulations are considered as the major reliability related costs from distribution companies point of view. A set of mixed-integer linear equations is proposed to calculate the most common distribution system reliability indices, i.e. EENS, SAIFI, and SAIDI. It is found that these equations can also facilitate the formulation of radiality constraint in the presence of DG units. Moreover, application of the proposed method is investigated through various case studies performed on two test distribution networks with 24 and 54 nodes.
Iet Renewable Power Generation, Nov 4, 2022
In this paper, a two-stage charging management framework is proposed to exploit the potential fle... more In this paper, a two-stage charging management framework is proposed to exploit the potential flexibility of Electric Vehicles (EVs). The aim is to reduce drastic variations in distribution system net load caused by integration of intermittent renewable distributed generation (DG) units. In the first stage, a home-based charging method is formulated in which the desired charging schedule of EVs is obtained by minimizing the cost of energy taking into account owners' preferences. The attained charging schedules are then announced to EVs Coordinator Agent (ECA) which, as the second stage, applies an LP optimization to reduce the cost of ramp provision. Moreover, an incentive scheme is considered to motivate EV owners to participate in the controlled charging program which allows the ECA to modify their desired schedules in exchange for financial bonuses. The simulation results show that the proposed framework can efficiently reduce the system net load ramp and associated costs without disturbing individual convenience.
Technical virtual power plant (TVPP) plays an important role in modern power systems by coordinat... more Technical virtual power plant (TVPP) plays an important role in modern power systems by coordinating distributed energy resources (DERs) to participate in wholesale electricity market. This paper presents a framework for TVPP's energy management in an active distribution system with diverse uncertain DERs. The TVPP participates in wholesale day-ahead (DA) market and schedules DERs in order to maximize its profit, while considers actual locations of DERs in the network and takes network operational constraints into account. Many diverse DERs including DGs, renewable energy sources (RESs), and several load sectors comprising EVs, heating, ventilation, and air conditioning (HVAC) systems and diverse responsive appliances (RAs) are considered. Furthermore, the customers' welfare constraints are considered to be strictly satisfied. In addition, uncertainties associated with RESs' output power and customers' load profiles are considered effectively. The proposed model is formulated as a mixed integer linear programming (MILP) problem with global optimum solution. Implementing the model on an IEEE standard test system demonstrates the efficiency and effectiveness of the model.
Iet Generation Transmission & Distribution, Jun 9, 2021
The concept of flexibility is defined as the power systems' ability to effectively respond to cha... more The concept of flexibility is defined as the power systems' ability to effectively respond to changes in power generation and demand profiles to maintain the supply-demand balance. However, the inherent flexibility margins required for successful operation have been recently challenged by the unprecedented arrival of uncertainties, driven by constantly changing demand, failure of conventional units, and the intermittent outputs of renewable energy sources (RES). Tackling these challenges, energy storage systems (ESS) as one important player of the new power grids can enhance the system flexibility. It, therefore, calls for an efficient planning procedure to ensure flexibility margins by considering ESS's role in modern power systems. This paper proposes a novel mixed integer linear programming (MILP) model for transmission expansion planning (TEP) framework taking into account the role of compressed air energy storage (CAES) integration on improvements in system flexibility. The proposed framework is housed with a quantitative metric of gridscale system flexibility, while a new offline repetitive mechanism is suggested to account for the N − 1 reliability criterion. The model is applied to different test systems, where the numerical results demonstrate the impacts of CAES units on system flexibility, investment plans, and the total costs. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
IEEE Systems Journal, Dec 1, 2021
Both frequency and intensity of natural disasters have intensified in recent years. It is, theref... more Both frequency and intensity of natural disasters have intensified in recent years. It is, therefore, essential to design effective strategies to minimize their catastrophic consequences. Optimizing recovery tasks, including distribution system reconfiguration (DSR) and repair sequence optimization (RSO), are the key to enhance the agility of disaster recovery. This article aims to develop a resilience-oriented DSR and RSO optimization model and a mechanism to quantify the recovery agility. In doing so, a new metric is developed to quantify the recovery agility and to identify the optimal resilience enhancement strategies. The metric is defined as “the number of recovered customers divided by the average outage time of the interrupted customers.” A Monte-Carlo-based methodology to quantify the recovery agility of different DSR plans is developed. It will be shown that if the total number of interrupted customers over the recovery horizon is minimized, the metric will be maximized. Accordingly, the DSR and RSO optimization models are modified to maximize the introduced metric. The proposed optimization model is formulated as a mixed-integer linear programming model that can be solved via commercial off-the-shelf solvers. Finally, the proposed methodology is applied to several case studies to examine its effectiveness. It will be also shown how the proposed methodology can be utilized for distributed generator (DG) and tie-line placement problems in planning for enhanced structural resilience.
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Papers by Moein Moeini-Aghtaie