Mohammad Chehreghani Bozchalui

Optimal operation of commercial building microgrids using multi-objective optimization to achieve emissions and efficiency targets

This paper presents an optimization model for optimal energy management of commercial building microgrid (μG) systems. The objectives are to increase efficiency of energy utilization, minimize operational costs and reduce environmental impacts of energy utilization in commercial buildings. Thus, mathematical models of a Combined Cooling, Heating, and Power (CCHP) μG including gas-fired Internal Combustion Engines (ICEs), Gas Boilers (GB), Micro Turbines (MTs), Fuel Cells (FCs), Heat Exchanger (HE), and Absorption Refrigeration (AR) are developed. Also, mathematical models for solar PhotoVoltaic (PV) generation, thermal energy storage, and battery storage devices are formulated. Based on the developed models, a multi-objective optimization problem is formulated to optimally operate these multi-carrier hybrid AC/DC μGs, minimizing their energy costs and Greenhouse Gas (GHG) emissions. The proposed method is applied to a commercial building μG to investigate the best strategies to operate the μG to achieve Department of Energys (DOEs) 2020 emissions and efficiency targets for μGs. The presented simulation case studies show promising results by reducing total costs and attaining the efficiency and emissions reductions targets.

Microgrids availability evaluation using a Markov chain energy storage model: a comparison study in system architectures

This paper investigates the effect of energy storage systems on the availability of microgrids with different architectures in the presence of renewable energy sources (RESs). When RESs are used for power generation within a microgrid, its availability may be reduced due to the intermittent nature of RESs. Thus, energy storage systems may be used as a solution to improve microgrids availability. Therefore, it is important to have a realistic evaluation of microgrids availability and to determine how added energy storage affects microgrids. Since energy storage system is not just a one-time-use reserve, charging and discharging processes in energy storage need to be considered when their availability is evaluated. Thus, a Markov chain model is used in this paper to properly represent the charging and discharging processes of energy storage systems, and minimal cut sets method is used in order to evaluate the availability of different microgrid architectures. Using the proposed method, availabilities of radial, ring, and ladder type microgrid architectures are evaluated in the presence of RESs and energy storage systems, and results are discussed.

Coordinated clustering algorithms to support charging infrastructure design for electric vehicles

The confluence of several developments has created an opportune moment for energy system modernization. In the past decade, smart grids have attracted many research activities in different domains. To realize the next generation of smart grids, we must have a comprehensive understanding of interdependent networks and processes. Next-generation energy systems networks cannot be effectively designed, analyzed, and controlled in isolation from the social, economic, sensing, and control contexts in which they operate. In this paper, we develop coordinated clustering techniques to work with network models of urban environments to aid in placement of charging stations for an electrical vehicle deployment scenario. We demonstrate the multiple factors that can be simultaneously leveraged in our framework in order to achieve practical urban deployment. Our ultimate goal is to help realize sustainable energy system management in urban electrical infrastructure by modeling and analyzing networks of interactions between electric systems and urban populations.

Analysis of Electric Vehicles as Mobile Energy Storage in commercial buildings: Economic and environmental impacts

This paper investigates the application of Electric Vehicles (EVs) as Mobile Energy Storage (MES) in commercial buildings. Thus, energy systems of a commercial building including its grid connection, Distributed Energy Resources (DERs), Energy Storage (ES), and demand profile are modeled. Based on the developed models, a Mixed Integer Linear Programming (MILP) problem is formulated to optimize the operation of a commercial building microgrid (μθ) minimizing its daily energy costs and greenhouse gas emissions (GHG). Technical and operational constraints of DERs and ESS such as minimum up time and down time, load sharing characteristics of diesel generators, and charging and discharging constraints of ES devices are formulated to appropriately model the operation of a grid connected commercial μΘ. A realistic example with solar Photo-Voltaic (PV), Fuel Cell (FC), Micro-Turbine (MT), Stationary Energy Storage (SES), and MES is used to study effects of integrating EVs as MES on energy costs and GHG emissions of a commercial building. Simulation results that reveals potential economical and environmental impacts of EVs are presented and discussed.

Optimal operation of Energy Storage in distribution systems with Renewable Energy Resources

This paper presents a framework for optimal operation scheduling of Energy Storage Systems (ESSs) in coordination with Renewable Energy Resources (RERs) in distribution systems. The proposed framework is a multi-time interval optimization problem that includes an efficient three-phase unbalanced Distribution Optimal Power Flow (DOPF) model. Mathematical models for RERs and ESS are integrated into the problem, and multiple objective functions such as minimization of losses, imbalanced power at the substation, total energy costs, and peak demand are formulated to optimally operate distribution networks from the perspective of a local distribution company. The proposed framework generates optimal charge/discharge scheduling of ESSs, while meeting technical and operational requirements of distribution networks and ESSs. Relevant simulation results for a test system with multiple solar PVs and two ESSs are presented and discussed to highlight the effectiveness of the proposed method to optimally operate distribution systems with multiple ESSs and RERs.

Rolling Stochastic Optimization based operation of distribution systems with PVs and Energy Storages

This paper presents a novel framework for stochastic optimal operation of Energy Storage (ES) systems in coordination with Renewable Energy Resources (RERs) in three-phase unbalanced distribution systems. An efficient three-phase unbalanced Distribution Optimal Power Flow (DOPF) is formulated that can be used for both radial and meshed networks. Mathematical optimization models for ESs are developed and integrated in the DOPF formulation. Then, two stochastic operation methods, Fixed-Window Iterative and Rolling Stochastic Optimization methods, are employed to optimally schedule the operation of resources in distribution networks with uncertainties in demand and RER outputs. The proposed optimization model can also be employed to analyze the effects of integrating RERs and ESs into distribution systems. Some relevant simulation results are presented and discussed to highlight the effectiveness of the proposed method to optimally operate distribution systems with ES and RERs. Presented results show that considerable power loss reductions could be achieved with optimal operation of ESs even in the presence of uncertainties.

Smart operation of unbalanced distribution systems with PVs and Energy Storage

This paper presents a novel framework for optimal operation of Energy Storage Systems (ESSs) in coordination with Renewable Energy Resources (RERs) in a distribution system. The proposed model is a multi-period, three-phase, unbalanced Distribution Optimal Power Flow (DOPF) wherein mathematical models for solar photovoltaic (PV) generation and ESS are integrated. Two objectives are considered from the perspective of a Local Distribution Company (LDC): one objective seeks to minimize the LDCs energy procurement costs using a time-of-use rate, and the second objective minimizes total losses of the feeder. Multiple case studies are carried out to examine the operational scheduling of the ESS when placed nearby the substation and at the end of the feeder. Relevant simulation results are presented and discussed to highlight the effectiveness of the proposed method for optimal operation of distribution systems with ESS and RERs. Furthermore, the effect of increasing PV penetration on the operating schedule of the ESS is also examined.

Operation strategies for energy storage systems in distribution networks

This paper investigates various strategies for operation scheduling of Energy Storage Systems (ESS) in distribution systems, and proposes an optimization-based method to optimally operate ESS in coordination with Renewable Energy Resources (RERs) and load variations. Mathematical models for operation of ESS are developed and incorporated in a three-phase unbalanced Distribution Optimal Power Flow (DOPF) optimization model. The proposed model generates optimal charge/discharge schedules of ESS, while satisfying distribution network operational constraints such as voltage limits. Various simulations are carried out to analyze the impacts of different operation strategies on the performance of the system, and highlight the effectiveness of the proposed method in optimally operating distribution networks with ESS and RERs. Presented results show that considerable improvement in the efficiency of distribution system operation, e.g., reductions in losses, peak demand, and energy, could be achieved using the proposed optimal operation scheduling of ESS.

Charging and Storage Infrastructure Design for Electric Vehicles

Ushered by recent developments in various areas of science and technology, modern energy systems are going to be an inevitable part of our societies. Smart grids are one of these modern systems that have attracted many research activities in recent years. Before utilizing the next generation of smart grids, we should have a comprehensive understanding of the interdependent energy networks and processes. Next-generation energy systems networks cannot be effectively designed, analyzed, and controlled in isolation from the social, economic, sensing, and control contexts in which they operate. In this article, we present a novel framework to support charging and storage infrastructure design for electric vehicles. We develop coordinated clustering techniques to work with network models of urban environments to aid in placement of charging stations for an electrical vehicle deployment scenario. Furthermore, we evaluate the network before and after the deployment of charging stations, to recommend the installation of appropriate storage units to overcome the extra load imposed on the network by the charging stations. We demonstrate the multiple factors that can be simultaneously leveraged in our framework to achieve practical urban deployment. Our ultimate goal is to help realize sustainable energy system management in urban electrical infrastructure by modeling and analyzing networks of interactions between electric systems and urban populations.

Analysis of unbalanced distribution systems with solar PV penetration

This paper presents the modeling and analysis of solar photovoltaic (PV) generation systems penetrating into low voltage distribution feeders. The solar PV module is modeled as a constant PQ generation source and incorporated within an unbalanced distribution feeder. Furthermore, a distribution optimal power flow (DOPF) model is developed that includes the PV module and examines feeder operation from the perspective of the Local Distribution Company (LDC). Objective functions such as minimization of total energy drawn from the substation and minimization of total losses are considered. A realistic feeder system of Hydro One Inc. is used for the studies for various penetration levels of PV resources. Results show that total losses and total energy drawn from the substation is reduced with increased penetration of solar PV resources. However, this is accompanied with an increase in reactive power drawn from the external grid.