Saeed D. Manshadi

Resilient Operation of Multiple Energy Carrier Microgrids

This paper proposed a methodology to identify the vulnerable components, and ensure the resilient operation of coordinated electricity and natural gas infrastructures considering multiple disruptions within the microgrid. The microgrid demands, which consist of electricity and heat demands, are served by the interdependent electricity and natural gas supplies. The proposed approach addressed the vulnerability of multiple energy carrier microgrids against various interdictions, which is used to apply preventive reinforcements to increase the resilience of energy supply and decrease the operation cost. The proposed methodology is formulated as a bi-level optimization problem to address the optimal and secure operation of multiple energy carrier microgrids. The interdependence between natural gas and electricity infrastructures is addressed to show the effectiveness of the presented methodology in improving the resilience of generation and demand scheduling against deliberate actions causing disruptions in the interdependent energy infrastructures in multiple energy carrier microgrids.

A Hierarchical Electricity Market Structure for the Smart Grid Paradigm

This paper proposed a hierarchical structure for the electricity market to facilitate the coordination of energy markets in distribution and transmission networks. The proposed market structure enables the integration of microgrids, which provide energy and ancillary services in distribution networks. In the proposed hierarchical structure, microgrids participate in the energy market at the distribution networks settled by the distribution network operator (DNO), and load aggregators (LAs) interact with microgrids and generation companies (GENCOs) to import/export energy to/from the distribution network electricity markets from/to the wholesale electricity market. The proposed approach addressed the synergy of energy markets by introducing dynamic game with complete information for GENCOs, microgrids, and LAs. The proposed hierarchical competition is composed of bi-level optimization problems in which the respective upper-level problems maximize the individual market participants’ payoff, and the lower-level problems represent the market settlement accomplished by the DNO or the independent system operator. The bi-level problems are solved by developing sensitivity functions for market participants’ payoff with respect to their bidding strategies. A case study is employed to illustrate the effectiveness of the proposed approach.

Multiple Period Ramping Processes in Day-Ahead Electricity Markets

This paper proposes an approach to formulate the multiple-period ramping capability of dispatchable generation resources and evaluates the impact of this service on the generation scheduling in day-ahead electricity market. It is discussed that the multiple-period ramping enhances the load following capability of dispatchable generation resources and improves the dispatchability of renewable energy resources in power systems. The presented approach encompasses the uncertainties in the operation scheduling of power systems, using scenario based stochastic security-constrained unit commitment. The presented case studies also highlight the merits of integrating energy storage facilities to reduce the ramping services provided by dispatchable generation resources with respective costs.

Expansion of Autonomous Microgrids in Active Distribution Networks

This paper presents an approach to transform the active distribution network with distributed energy resources into multiple autonomous microgrids. The distribution network consists of several generation resources and demand entities, that are clustered into autonomous microgrids. The proposed problem is formulated as a bi-level optimization problem that leverages the Eigen decomposition in the graph spectra of the distribution network to determine the boundaries for microgrids and a mixed-integer programming problem that minimizes the expansion cost within microgrids. The presented approach is evaluated in a case study for a distribution network considering the imposed reliability constraints. The outcomes indicate the effectiveness of the proposed algorithm to determine the expansion strategies to form autonomous microgrids in active distribution networks.

A Framework for Expansion Planning of Data Centers in Electricity and Data Networks under Uncertainty

This paper presents the expansion planning for data centers and data routes in the data and electricity networks considering the uncertainties in the planning horizon to ensure an acceptable rate of service to the requests received from the end-users in the data network. The objective is to determine the location and capacity of the data centers as well as the required data routes while considering the imposed constraints in the electricity and data networks. The installation cost of data centers and data routes, as well as the expected operation cost of the data centers, are minimized. The proposed problem addressed the uncertainties in the expansion planning of the electricity networks including the availability of renewable generation resources, the variations in electricity demand, the availability of generation and transmission components in the electricity network, and the uncertainties in the number of requests received by the user groups in the data network. The problem is formulated as a mixed integer linear programming problem and Bender decomposition and electricity price signals are used to capture the interaction among the data and electricity networks. The presented case study shows the effectiveness of the proposed approach.

Risk Averse Generation Maintenance Scheduling with Microgrid Aggregators

This paper presents risk-averse long-term generation maintenance scheduling in the power systems with a considerable installed capacity of microgrids. Microgrid aggregators facilitate the participation of microgrids in the wholesale market. In this paper, the effect of microgrids as controllable demand entities on the generation maintenance scheduling practices in the power system is investigated. The uncertainties in the marginal cost of generation in microgrids, the generation capacity installed within the microgrids, and the system electricity demand are captured using respective nominal values and uncertainty intervals. Moreover, the contingencies in transmission network are addressed by introducing additional variables. A two-stage robust optimization problem is formulated to determine a trade-off among the performance and conservativeness of the procured solution in the long-term operation horizon. The problem is formulated as a mixed integer linear programming problem and column-and-constraint generation procedure is used to solve the problem. The master problem minimizes the maintenance cost of the generation units subjected to generation units’ constraints in the long-term operation horizon and the sub-problems determine the worst realization of the uncertainties and generate additional constraints in the master problem. The proposed methodology is applied to two case studies for a 6-bus and IEEE 118-bus power systems.

Decentralized operation framework for hybrid AC/DC microgrid

This paper proposes a methodology to attain the optimal generation scheduling of hybrid AC/DC microgrids. The hybrid microgrid consists of AC and DC networks with respective generation and demand resources that are connected by bi-directional AC/DC converters. The proposed methodology leverages decentralized optimization framework that uses the dispatch of the AC/DC converter to facilitate the coordinated operation of AC and DC networks. The presented framework utilizes an iterative approach to determine the optimal operation schedule for the hybrid AC/DC microgrid using distinct optimization problems. The results illustrate the effectiveness of the presented approach for operation planning of hybrid AC/DC microgrids.

Wireless Charging of Electric Vehicles in Electricity and Transportation Networks

Wireless charging station (WCS) enables in-motion charging of the electric vehicles (EVs). This paper presents the short-term operation of WCS by capturing the interdependence among the electricity and transportation networks. In the transportation network, the total travel cost consists of the cost associated with the travel time and the cost of utilized electricity along each path. Each EV takes the path that minimizes its total travel cost. In the electricity network, the changes in WCS demand as a result of changes in the traffic flow pattern impacts the price of electricity. The changes in the price of electricity further affect the charging strategy of the EVs and the associated traffic flow pattern. The coordination between electricity and transportation networks would help mitigate congestion in the electricity network by routing the traffic flow in the transportation network. The presented formulation leverages decentralized optimization to address the economic dispatch in the electricity network as well as the traffic assignment in the transportation network. The presented case studies highlight the merit of the presented model and the developed algorithms for the coordinated operation of WCS in electricity and transportation networks.

Resilient operation of multiple energy carrier microgrids

This paper proposed a methodology to identify the vulnerable components, and ensure the resilient operation of coordinated electricity and natural gas infrastructures considering multiple disruptions within the microgrid. The microgrid demands, which consist of electricity and heat demands, are served by the interdependent electricity and natural gas supplies. The proposed approach addressed the vulnerability of multiple energy carrier microgrids against various interdictions, which is used to apply preventive reinforcements to increase the resilience of energy supply and decrease the operation cost. The proposed methodology is formulated as a bi-level optimization problem to address the optimal and secure operation of multiple energy carrier microgrids. The interdependence between natural gas and electricity infrastructures is addressed to show the effectiveness of the presented methodology in improving the resilience of generation and demand scheduling against deliberate actions causing disruptions in the interdependent energy infrastructures in multiple energy carrier microgrids.