Sharif Digital Repository

Nowadays, the increasing integration of variable renewable energies (VREs) in power systems have resulted in operational transformations of energy systems. Respectively, the high-amount of integrated VREs could cause severe-ramping in the net-load of energy systems due to abrupt changes in their power production. Accordingly, based on the limited flexibility capacity in transmission systems, severe ramping-up/down (RU/RD) in distribution systems should be addressed by employing local flexible resources (LFRs). Nevertheless, evolution of multi-agent structured distribution systems has limited the direct access of distribution system operators (DSOs) in scheduling of LFRs. Consequently, this... 

The development of emerging smart grid technologies has led to more and more penetration of renewable energy resources and electric energy storage in the residential sectors. Besides, owing to the significant evolution of power electronic devices, there is a rapid growth in penetration of DC loads and generations, such as PV and electric vehicles (EVs), into the buildings and homes as a building block of the future smart cities. This is despite the fact that the electricity infrastructure of the conventional buildings is designed based on AC electricity and as a result, there would be a lot of losses due to the frequent power conversion from AC to DC and vice versa. Besides, according to a... 

In the energy system, various sources are used to fulfill the energy demand of large buildings. The energy management of large-scale buildings is very important. The proposed system comprises solar PVs, energy storage systems, and electric vehicles. Demand response (DR) schemes are considered in various studies, but the analysis of the impact of dynamic DR on operational cost has been ignored. So, in this paper, renewable energy resources and storages are integrated considering the demand response strategies such as real-time pricing (RTP), critical peak pricing (CPP), and time of use (ToU). The proposed system is mapped in a linear model and simulated in MATLAB using linear programming... 

Transmission lines congestion has recently been a vital challenge in power systems operation due to the intermittent outputs of renewable energy sources (RES). Therefore, an efficient transmission congestion management (TCM) method should be defined to deal with the congestion issue. This paper aims to propose a simultaneous linearized two-stage TEP-BESS co-planning optimization model to relieve transmission lines congestion. In doing so, a novel TCM structure is suggested in a pool-based deregulated data-driven optimal power flows (D-OPF) by the computationally effective min-max regret method to consider future scenarios of generating units and demanded loads. To improve the efficiency of... 

The introduction of cryptocurrencies as a new form of money has attracted a tremendous amount of attention in recent years. This new financial paradigm relies on miners to validate transactions by running their cryptocurrency mining devices (CMDs). Nowadays, the significant profitability of the mining business has tempted a large number of private players in the electrical industry to employ their renewable energy resources to mine digital currency. Here, microgrid (MG) owners may use their excessive generated power to mine digital money instead of exporting it to the main grid. This paper is devoted to investigate the influential potentials of this trending business on distribution networks... 

This paper presents a novel stochastic planning framework for the integration of renewable distributed energy resources (DERs) into existing power systems without relying on new investments in the transmission networks. The upper-level problem of the proposed model aims at minimizing the total expected social cost of supplying demand that includes the expected cost of getting energy from conventional generating units and DERs, the congestion cost of transmission networks, and the greenhouse gas (GHG) emission cost, while each of the privately invested DER satisfies a specified rate of return. The lower-level problem clears the electricity market to find locational marginal prices (LMPs) and... 

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 co-planning 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... 

This paper presents a new framework for multistage expansion planning in active power distribution networks, in which the distribution system operator (DSO) considers active network management by clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the net present value of the total costs imposed to DSO associated with the investment and maintenance of the network assets as well as the network operation, while the lower level on clearing the local energy market captures the participation of distributed energy resource (DER) owners and demand aggregators to maximize the social welfare.... 

Current energy systems face multiple problems related to inflation in energy prices, reduction of fossil fuels, and greenhouse gas emissions which are disturbing the comfort zone of energy consumers and the affordability of power for large commercial customers. These kinds of problems can be alleviated with the help of optimal planning of demand response policies and with distributed generators in the distribution system. The objective of this article is to give a strategic proposition of an energy management system for a campus microgrid (µG) to minimize the operating costs and to increase the self-consuming energy of the green distributed generators (DGs). To this end, a real-time based... 

Recently, many investigations have been studied on the effects of the uncommon extreme events like hurricanes in electrical distribution grids. These events leads to damage to distribution grid equipments, and they are cause widespread blackouts. This paper presents short-term resilience enhancement of the residential sections against hurricane at day-ahead. The lines outage in the electrical distribution grid is implemented as stochastic modeling by hurricane. The resilience enhancement is done in the multiple energy systems such as integrated gas, heat and electrical. The three-stage multi-objective functions optimization is proposed for resilience-oriented enhancement. The proposed... 

Distributed generation connected with AC, DC, or hybrid loads and energy storage systems is known as a microgrid. Campus microgrids are an important load type. A university campus microgrids, usually, contains distributed generation resources, energy storage, and electric vehicles. The main aim of the microgrid is to provide sustainable, economical energy, and a reliable system. The advanced energy management system (AEMS) provides a smooth energy flow to the microgrid. Over the last few years, many studies were carried out to review various aspects such as energy sustainability, demand response strategies, control systems, energy management systems with different types of optimization... 

Reinforcement learning methods such as Q-learning have shown promising results in the model-free design of linear quadratic regulator (LQR) controllers for linear time-invariant (LTI) systems. However, challenges such as sample-efficiency, sensitivity to hyper-parameters, and compatibility with classical control paradigms limit the integration of such algorithms in critical control applications. This paper aims to take some steps towards bridging the well-known classical control requirements and learning algorithms by using optimization frameworks and properties of conic constraints. Accordingly, a new off-policy model-free approach is proposed for learning the Q-function and designing the... 

This paper presents a new model to maximize the utilization of existing transmission system infrastructure by optimally sizing and siting the future developments of variable renewable energy sources (VRES). The model tries to maximize the integration of VRES in power systems with minimum expected energy curtailment without relying on new investments in the transmission systems. The proposed model is formulated as a linear stochastic programming optimization problem where VRES output scenarios are generated such that their spatio-temporal correlations are maintained. The Progressive Hedging Algorithm (PHA) with bundled scenarios is utilized to solve the proposed model for large-scale cases.... 

In this paper, the vulnerability of large-dimensional dynamic networks to false data injections is analysed. The malicious data can manipulate input injection at the control nodes and affect the outputs of the network. The objective is to analyse and quantify the potential vulnerability of the dynamics by such adversarial inputs when the opponents try to avoid being detected as much as possible. A joint set of most effective actuation nodes and most vulnerable target nodes are introduced with minimal detectability by the monitoring system. Detection of this joint set of actuation-target nodes is carried out by introducing a Gramian-based measure and reformulating the vulnerability problem as... 

By increasing the penetration level of the combined heat and power systems and demand response programs between energy consumers in the distribution network, the interaction between electricity and the natural gas network becomes more complicated. This paper proposes a peer-to-peer (P2P) energy sharing scheme for energy trading among Smart Energy Hubs (S.E. Hubs) which can trade both electrical and thermal energy with each other to reduce their cost and, reduce their dependency to gas and electricity utility companies. A two-stage energy strategy is presented. In the first stage, the S.E. Hubs total social cost is reduced by finding the optimal energy sharing profiles. And, in the second... 

The purpose of this research is to provide power grid energy efficiency solutions. In this paper, a comprehensive review and its optimal solution is proposed considering the various challenges of smart grid demand-side management. The main technique is based on a novel idea in the Smart Grid—demand response optimization which enables autonomous energy management on the demand side for a wide variety of customers. The first section of this research examines the smart grid issue and evaluates the state-of-the-art load management techniques in terms of the work’s scope. The demand-side load management architecture consists of three primary levels, two of them in line planning and low-cost... 

The widespread presence of contingent generation, when coupled with the resulting volatility of the chronological net-load (i.e., the difference between stochastic generation and uncertain load) in today's modern electricity markets, engender the significant operational risks of an uncertain sufficiency of flexible energy capacity. In this article, we address several operational flexibility concerns that originate from the increase in generation variability captured within a security-constrained unit commitment (SCUC) formulation in smart grids. To quantitatively assess the power grid operational flexibility capacity, we first introduce two reference operation strategies based on a two-stage... 

High penetration of Power Electronic (PE) converters in DC power grids causes new stability challenges due to dynamic interactions among the subsystems of a network. Such dynamic interactions can be avoided by the impedance coordination among the subsystems through the modification of control loops or passive elements inside a grid. Impedance coordination is a very complex and time-consuming task with no adaptations to dynamic changes in a power grid. The current study delved into the concepts of dynamic interaction and passivity and they were combined to provide an online stability measure concerning the DC bus impedance characteristics. In this regard, a novel DC Power System Stabilizer... 

Due to the acceleration of energy transition from fossil fuels to Distributed Energy Resources (DERs), the structure of the power industry (mainly generation and distribution) is changing. The emergence of the smart grid concept and Peer-to-Peer (P2P) electricity markets make local producers and consumers face new challenges and risks. Managing the risks that the participants in P2P markets are encountered is necessary to guarantee a sustainable penetration of such markets. This article provides a comprehensive risk analysis by implementing a proposed risk management framework to address the identification, classification, assessment, and mitigation of all risks that prosumers will face when... 

The Class-E power amplifier has been widely studied and formulated in the literature. Although the majority of reported inductive coupling wireless power transfer (WPT) systems use a class-E power amplifier for driving the primary coil, still there is a lack of a comprehensive study on class-E circuit dedicated to WPT, providing a set of closed form design equations for proper class-E operation. This paper presents the required design equations needed to design a 'true' class-E circuit for WPT applications. Equations for the series-tuned secondary coil WPT system are presented, as well as two different design procedures for the parallel-tuned secondary coil. The derived equations have been...