Ashkan Rahimi-Kian

• PhD, IEEE Senior Member
• Chief Technology Officer at IEMS Solution Limited

The transactive energy market (TEM) is a recent development in energy management that enables prosumers to trade directly, promising many environmental and economic benefits. Prosumer trading necessitates sharing information to facilitate transactions. Additionally, many TEMs propose using blockchains to manage auctions and store transactions. Thes...

The transactive energy market is an emerging development in energy economics built on advanced metering infrastructure. Data generated in this context is often required for market operations, while also being privacy sensitive. This dual concern has necessitated the development of various methods of obfuscation in order to maintain privacy while st...

Advances in energy generation and distribution technology have created the need for new power management paradigms. Transactive energy markets are integrated software and hardware systems that enable optimized energy management and direct trading between prosumers. This literature review covers unresolved security and privacy vulnerabilities in the...

The cover image is based on the Research Article Integral Backstepping Lyapunov Redesign Control of Uncertain Nonlinear Systems by Esmaeil Jalalabadi et al., https://doi.org/10.1049/cth2.12229. image

Abstract This paper intends to design an integral backstepping Lyapunov redesign controller (IBLRC) for various uncertain strict‐feedback‐form nonlinear systems. The pros and cons of backstepping Lyapunov redesign resulted in the design idea. An integral term is incorporated in conventional backstepping with Lyapunov redesign to indirectly decrease...

Through transactive energy (TE) platforms, prosumers can enter into a contractual agreement with an Independent Electricity System Operator (IESO) to buy and sell energy. Accordingly, the TE contract holders are liable for contractual violations. Manual compliance checking of such transactions is infeasible due to large number of market rules as we...

In this paper, a detailed mathematical optimization model of electrolyzer/fuel cell technology connected to the grid through limited rating converters is developed. The model is so defined that it can tackle voltage fluctuation and meet the power ramp rate limitations inflicted by integration of constant-speed wind turbines at the Point of Common C...

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 accurac...

A novel procedure for the design of an optimal controller with a predetermined degree of stability to enhance damping of interarea oscillations in interconnected power networks is presented in this paper. The proposed approach includes a feedback controller, which is independent of internal disturbances as a stabilizer. A tuning parameter is also p...

In this paper, an ontology-driven multi-agent based energy management system (EMS) is proposed for monitoring and optimal control of an integrated homes/buildings and microgrid system with various renewable energy resources (RESs) and controllable loads. Different agents ranging from simple-reflex to complex learning agents are designed and impleme...

Buildings play an important role in the energy consumption sector as reports from the US Department of Energy (DOE) declare that most of the electricity usage in USA attributed to the buildings. To improve the energy quality of this important area, novel technologies and operation methods are being industrialized every day. Combined Cooling Heating...

In this paper, an effective energy management system (EMS) for application in integrated building and microgrid system is introduced and implemented as a multi-objective optimization problem. The proposed architecture covers different key modelling aspects such as distributed heat and electricity generation characteristics, heat transfer and therma...

In modern electric power grids, microgrids are utilized in order to improve electric power grids' technical, economical, and environmental performance. In other words, both operator and consumers benefit the gained improvements by microgrids. However, operators confront certain ordeals to plan and operate the specific microgrid. In this paper, Comb...

Smart Energy Management Systems (SEMS) have become indispensable in Micro-Grid (M G) infra-structure for saving energy usage costs and system control considering the time-varying parameter s. In this paper, a new multi-stage SEMS architecture is proposed for optimal energy management in MGs considering various resource uncertainties . The proposed...

One of the most challenging problems associated with operation of Smart Micro-Grids is the optimal energy management of residential buildings with respect to multiple and often conflicting objectives. In this paper, a multi-objective mixed integer nonlinear programming model is developed for optimal energy use in a smart home, considering a meaning...

With the emerging of small-scale integrated energy systems (IESs), there are significant potentials to increase the functionality of a typical demand-side management (DSM) strategy and typical implementation of building-level distributed energy resources (DERs). By integrating DSM and DERs into a cohesive, networked package that fully utilizes smar...

Distributed control can be used against centralized control in terms of computational burden and functional issues. The current paper focuses on offline application of distributed control (by receding horizon approach) to a large-scale production/distribution/inventory network or in the other words, a supply chain system. In some industries, long-t...

Financial market analysis and prediction is one of the interesting areas in financial signal processing. This area is of high importance for professionals in Foreign Exchange market and stock exchange market as they can lead and direct future trends or manage crisis over time. In this paper we introduced price efficiency as a prediction parameter a...

In this paper, a modified model predictive control method has been proposed for voltage control of an inverter in an islanded microgrid. The main objective of this method is to reduce voltage THD and the reference tracking error. In the proposed scheme, some vectors are added to existing vectors, available in FCS-MPC method to reduce the error betw...

3rd International Traffic Accident Conference, May 15-17, 2012, College of Engineering, University of Tehran, Tehran, Iran

Wide area measurement system (WAMS) usually contains three dependent infrastructures called management, measurement, and communication. For optimal operation of a power system, it is necessary to design these infrastructures suitably. In this paper, measurement and communication infrastructures in a wide area network are designed independently from...

Accurate electricity price prediction is one of the most important parts of decision making for electricity market participants to make reasonable competing strategies. Support Vector Machine (SVM) is a novel algorithm based on a predictive modeling method and a powerful classification method in machine learning and data mining. Most of SVM-based a...

In this paper, an intelligent multi-objective energy management system (MOEMS) is proposed for applications in residential LVAC micro-grids where households are equipped with smart appliances, such as washing machine, dishwasher, tumble dryer and electric heating and they have the capability to take part in demand response (DR) programs. The superi...

In this paper, a model-based strategy for the power control of hybrid vehicles is presented. Through a defined discretized model of vehicle and a cost function, the inputs to vehicle are controlled optimally as a constraint dynamic optimization to maximize the distance. The optimization strategy has to stages as in the first stage the optimal power...

This paper presents a new information based method of prediction which helps to obtain more information from a little data set and applies it on a data set of photovoltaic power plant of University of Tehran which only contained data of 100 days at the time of research. In this way some conventional models of time series are applied on the data set...

Abstract—A risk-constrained bidding model for generation companies (GenCos) competing in a pool-based electricity market is presented in this paper. In the proposed model, it is assumed that GenCos submit linear supply functions to the market operator. The intercept of the supply function is the decision variable to be optimized during the strategi...

In this paper the problem of developing bidding strategies for the participants of dynamic oligopolistic electricity markets is studied. Attention is given to strategic bidding of load serving entities (LSE) in these markets. We model oligopolistic electricity markets as non-linear dynamical systems and use discrete-time Nash bidding strategies. We...

Nowadays with the emerging of smart micro-grids(SM-Gs) in residential sectors, a large portion of energy consumption can be saved through optimal scheduling of household devices and management of domestic hybrid energy sources. By the aid of such technologies, residential consumers have the capability to mitigate their energy costs and satisfy thei...

One of the most challenging problems associated with operation of Smart Micro-Grids is the optimal energy management of residential buildings with respect to multiple and often conflicting objectives. In this paper, a multi-objective mixed integer nonlinear programming model is developed for optimal energy use in a smart home, considering a meaning...

Since the beginning of power system restructuring and creation of numerous temporal power markets, transmission congestion has become a serious challenge for independent system operators around the globe. On the other hand, in recent years, emission reduction has become a major concern for the electricity industry. As a widely accepted solution, at...

In an incomplete information game, a big challenge is to find the best way of exploiting available information for optimal decision making of the agents. In this paper, two decision making methods, namely model-based and learning-based bidding strategies are proposed and compared, for repeated Cournot competition of the generators in a day-ahe...

A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production management, can be estimated by advanced methods...

Documentations and supporting evidences for determining the technical, economic and environmental impacts of hydropower plants in competitive electricity markets, as well as estimating the true value of such power plants in ancillary service market.

Since the beginning of power system restructuring and creation of numerous temporal power markets, transmission congestion has become a serious challenge for independent system operators around the globe. On the other hand, in recent years, emission reduction has become a major concern for the electricity industry. As a widely accepted solution, at...

Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multi-layer perceptron neural network and the mutual information (MI) technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the i...

One of the most challenging problems associated with operation of smart micro-grids is the optimal energy management of residential buildings with respect to multiple and often conflicting objectives. In this paper, a multiobjective mixed integer nonlinear programming model is developed for optimal energy use in a smart home, considering a meaningf...

Virtual Power Plant (VPP) is defined as a cluster of energy conversion/storage units which are centrally operated in order to improve the technical and economic performance. This paper addresses the optimal operation of a VPP considering the risk factors affecting its daily operation profits. The optimal operation is modelled in both day ahead and...

Traffic control and management needs accurate estimation and prediction of traffic variables such as flow, speed, volume, travel time etc. Linear stochastic time series methods are powerful analytical tools. The capability of state space reconstruction makes them popular in traffic prediction and estimation. In this study, to overcome the linearity...

Accurate forecasting of renewable energies provides a suitable means for efficient and secure operation of electricity grids and enables optimal energy market planning. This paper presents a number of novel prediction models for solar radiation prediction; and their performances are compared to those of conventional prediction models such as Neural...

This paper proposes an analytical solution for bid-ding strategy problem of transmission-constrained generating companies (GENCOs) in an hour-ahead electricity market. Here, for modeling a bidding strategy problem under a supply function equilibrium model, a bilevel programming (BLP) method is used. In the upper level, the profit of an intended GEN...

To make renewable Micro-Grid (MG) systems work as a sustainable set, one confronts a multi-objective, multi-constraint problem. To optimally operate these hybrid energy systems, one should consider the problems due to huge amount of raw data achieved through several measuring systems in different sections in a MG. In this paper, a new Smart Energy...

In the business world, there are two key factors: customer satisfaction and cost. Delivery of goods from the manufacturer to customer is defined by supply chain management system systematically and the effect of the mentioned elements is seen in this structure. In this paper, current processes in a multi-product, multi-echelon supply chain are form...

Recently, with the growth in population, hiking fuel price and global warming concerns, the utilization of Distributed Energy Resources (DERs) is rising considerably. In this regard, to optimally operate these integrated energy systems decision maker should consider the uncertainties in both energy/reserve markets and consumptions/generations in Mi...

SUMMARY Independent System Operator (ISO) needs to draw sufficient attention to transmission congestion management (TCM) for guaranteeing power system security when deciding about a proposed power generation plan (PGP). To this end, this paper proposes a multi-attribute decision-making approach. The proposed decision-making procedure for a consider...

The aim of this article is to propose that an intelligent agent can be able to decide properly in an incomplete information repeated Cournot game. The market model and the competitors’ decision models are not known to the players. The proposed agent employs a combination of the k-nearest neighbor KNN method and the Bayes classifier to predict the n...

One of the important points in optimal operation of a micro-CHP based microgrids (e.g., a residential building) is to coordinate its thermal and electrical loads. Therefore, in this study, thermal load is analyzed more precisely in terms of the required hot water and desired building temperature. The microgrid is assumed to be equipped with smart m...

This paper studies the design and optimal operation of a grid-connected Micro-Grid. First, different feasible planning schemes has been generated with consideration of uncertainties. In the next step, in order to analyze uncertainty, risk exposure, robustness and flexibility indices have been presented. Also, in order to rank planning schemes, tech...

The voltage quality issues and their proper control, in modern power systems including renewable distributed power sources and FACTS devices such as harmonics, frequency flickering and voltage fluctuations, are very important. In this paper, the power and voltage are divided into microscopic and macroscopic levels to improve the consumers’ mic...

The growing focus on the energy efficiency promotion, deployment of renewable energy resources, and serving the electricity in more reliable ways have recently resulted in a remarkable attention on microgrids. Among different electricity generation options available for a microgrid, the one compromising both technical and economical aspects is of a...

Micro-grid technology provides an opportunity and a desirable infrastructure for improving efficiency of electrical and thermal energy consumption. The key to improve electrical and thermal energy efficiency in operation is to coordinate and optimize the operation of various energy resources and loads. In this paper, a typical micro-grid consisting...

In this paper a smart energy management system for a residential DC micro-grid (DCMG) is presented. A day-ahead deterministic programming for determining optimum operational points in DCMG is proposed. Moreover, the proposed model utilizes data mining techniques in order to reduce, refine and cluster historical data driven from Advanced Metering In...

In this paper, a detailed mathematical model of a grid-connected micro-grid including wind-turbine, photo voltaic cells and CHP with respective uncertainties in electrical loads, thermal loads, PV and wind power outputs with normal distributions is presented. Moreover, the effects of the considered uncertainties on the micro-grid's operation cost a...

This paper presents a multi-attribute DG planning strategy in a typical Micro-Grid based on an Analytic Hierarchy process (AHP) under various uncertainties. At the first step toward solving the planning problem, all DG sources together with their corresponding specifications are projected and initialized in HOMER software. Several plans are generat...

This paper presents a dynamic non-linear model of a micro-grid and then applies the GA algorithm to optimally manage the short-term operation of the studied micro-grid. The original calculus of variations method has been modified and augmented with GA-algorithm to solve non-linear optimal control problems, such as the optimal short-term operation o...

In this paper, a detailed mathematical model of a grid-connected micro-grid including wind-turbine, photo voltaic cells, CHP and elastic loads with respective uncertainties in electrical loads, thermal loads, PV and wind outputs are presented. Moreover, the effects of the considered uncertainties on the micro-grid's operation cost are modeled as ri...

In this paper, we investigated the necessity and effects of optimal control methods in the stability and performance of a micro-grid that operates in islanded mode. The micro-gird is consisted of a combine heat and power (CHP), a capacitor bank (CB), photovoltaic panel (PV) as power generation sources. In addition, battery and the building electric...

In this paper, a novel Smart Energy Management System (SMES) architecture is proposed to solve the multi-objective dispatch of distributed generation problem in a Micro-Grid with different technologies and new concepts such as demand response action. The multi-objective optimization problem is formulated as a constrained mixed integer nonlinear pro...

Micro-grid, in its whole vision, is an exemplar of a macro-grid in which local energy potentials- in forms of renewable (e.g., wind and solar) and non-conventional (micro-turbine, fuel cell, diesel generator) - are connected with each other as well as with the L.V utility and make a small-scaled power grid. In this regard, smart energy management s...

This paper illustrates how a generator profit may be affected by the pricing method of an oligopoly market model. Through utilizing a bilevel optimization technique and game theory concepts, Supply Function Equilibria (SFE) of pay-as-bid pricing (PABP) and marginal pricing (MP) mechanisms are derived. Theoretically, it is demonstrated that in the p...

Motivated by analyzing the dynamic adjustment process of players in an nn-player Cournot game, in this paper a discrete-time quadratic dynamical system is proposed and the stability of its equilibrium is analyzed. Several output adjustment mechanisms (e.g. best reply, adaptive adjustment and myopic) and expectations (e.g. naïve and adaptive) in a C...

In this study a distributed maximum likelihood estimator (MLE) has been presented to estimate ML function of traffic flow and mean traffic speed in a freeway. This algorithm uses traffic measurements including volume, occupancy and mean speed which gathered by some inductive loop detectors. These traffic detectors (traffic sensors) located in certa...

This paper proposes a Trust-Region Based Augmented Method (TRALM) to solve a combined Environmental and Economic Power Dispatch (EEPD) problem. The EEPD problem is a multi-objective problem with competing and non-commensurable objectives. The TRALM produces a set of non-dominated Pareto optimal solutions for the problem. Fuzzy set theory is employe...

Traffic flow prediction is an important problem in the research area of intelligent transportation system such as trip time estimation and light controlling. Recently, intelligent systems modeling have been used in various applications over nonlinear time series prediction such as traffic system control. In these modeling, not important input data...

According to the recent research significant amount of building energy consumption can be saved through optimized operation and management and it is not necessary to change the building structure and the hardware configuration of the energy supply system. Therefore, there is a huge potential for building energy savings through efficient operation....

This study presents an InterNet-based power market simulator (NetPMS) that has been invented, designed and implemented by the authors to provide an applicable environment for university students, research centres, power market participants and electrical power agents in order to exchange and raise their knowledge about power market issues. NetPMS i...

In this paper, planning of a grid-connected smart micro-power system is investigated. At first, its Advanced Metering Infrastructure (AMI) is designed to record, process and communicate the micro-grid energy, electrical data (e.g., active and reactive power flow data, voltage, frequency etc.), wind speed, solar radiation and so on, which are sent t...

Traffic speed prediction is an important problem in the research area of intelligent transportation system (ITS). Recently, artificial neural networks models, such as MLP, have been used in various applications over nonlinear time series prediction such as traffic control. In modeling, irrelevant inputs cause the deterioration of performance and an...

Short-term traffic flow forecasting is an important problem in the research area of intelligent transportation system (ITS). Recently, artificial neural networks modeling, such as MLP, have been used in various applications over nonlinear time series forecasting such as traffic control. In modeling, irrelevant inputs cause the deterioration of perf...

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm i...

In the evolving smart power systems (or smart grids), distributed generators (DG) and virtual power plants (VPP) have major roles in providing electric energy for microgrids. This paper studies the optimal operation of a VPP in a microgrid considering the uncertainties of the energy and fuel prices and managing the variance/risk of the VPP's profit...

Intermittence is one the main obstacles in wind power penetration, due to imbalance charges set by market prices. To cope with this drawback, demand-side participation has been proposed as a good complement that can handle positive and negative imbalances. This study suggests an offering optimisation model for aggregated wind power and flexible loa...

In this paper, a new method for market-based transmission planning is proposed. This method covers the main objectives of transmission planning in deregulated environment such as facilitating competition among market participants, providing non-discriminate electricity market, improving the reliability of power system, increasing the flexibility of...

This paper presents a multi-stage stochastic model for short-term transmission expansion planning considering the available transfer capability (ATC). The ATC can have a huge impact on the power market outcomes and the power system reliability. The transmission expansion planning (TEP) studies deal with many uncertainties, such as system load uncer...

This article presents a multi-objective framework for transmission expansion planning (TEP) with steady state voltage security consideration using AC optimal power flow (AC-OPF) within a market environment. The objectives are to minimize the investment costs (IC), operation costs (OC), load shedding cost (LSC) and also to maximize the voltage stabi...

Due to the increase in electricity energy consumption and the fact that about 90 % of fuels being used now are co2 pollutant and the crisis has been caused by greenhouse gases have made moving toward renewable energies unavoidable. Fortunately, with the cooperation and control of DG units, we can fortify the distribution networks that will finally...

To determine the optimal size, location and also the proper technology of distributed generation (DG) units in distribution systems, a static fuzzy multiobjective model is proposed in this paper. The proposed model can concurrently optimize a number of conflicting and competing objective functions including economic, technical and environmental att...