Maziar Yazdani Damavandi

Modeling the PEV traffic pattern in an urban environment with parking lots and charging stations

In this paper, a mixed-integer linear programing (MILP) model for the traffic behavior of plug-in electric vehicles (PEVs) in an urban environment is proposed. It is assumed that any environment can be categorized into different zones based on their urban functions (e.g. industrial, residential, and commercial). Therefore, the interaction of PEVs that travel between these zones has to be modeled. Besides, it is assumed that in each zone a parking lot (PL) and individual charging stations exist to provide the required state of charge (SOC) for PEVs during their daily travel. As a result, the amount of power that these PEVs consume (rather in PL or charging stations) and the amount of SOC that PEVs carry with them should be precisely computed. The proposed MILP model is applied on two zones urban area with residential and industrial districts and the numerical results prove the proficiency of the model.

Bi-level approach for modeling multi-energy players' behavior in a multi-energy system

In this paper a bi-level approach is presented to model the behavior of multi-energy players (MEP) who are coupled based on signal price in a multi-energy system (MES). The MEPs are defined as energy players who can trade more than one energy carrier and have energy facilities (e.g. energy storages and converters) to convert and store various energy carriers. In this approach, MEPs trade various energy carriers in the upper level problem and the coupled energy price will be deduced. In the lower level problem MEPs schedule their energy balance based on the upper level signal price. By implementing dual theorem, the bi-level problem is transformed into a single level optimization problem that can be solved with CPLEX optimizer. The proposed model has been applied in an MES with four MEPs and the numerical results demonstrate the proficiency of the modeling framework.

Distribution company and microgrids behaviour in energy and reserve equilibirum

In this paper, the cooperation of distribution company (Disco) and microgrids (MGs) in a local energy and reserve markets is addressed. To investigate the behavior of these decision makers in local energy and reserve equilibrium, a bilevel optimization model is presented. In the proposed bi-level model, Disco and MGs are considered as the leader and the followers, respectively. Disco decides about energy and reserve price in local markets. In addition, MGs decides about optimal scheduling of their resources and energy and reserve interactions with Disco in local markets. In energy and reserve equilibrium point, the local energy and reserve prices and the amount of energy and reserve interactions between Disco and MGs are determined. Duality theory is employed to solve the proposed bi-level model. The proposed model has been applied on a distribution grid with four MGs and the numerical results demonstrate the effectiveness of the proposed modeling framework.

Modeling strategic behavior of distribution company in wholesale energy and reserve markets

The decision making framework in power system has changed due to presence of distributed energy resources (DERs). These resources are installed in distribution networks to meet demand locally. Therefore, distribution companies (Discos) are enabled to supply energy through these resources to meet their demand at a minimum operation cost. Moreover, in this framework, the Disco will change its role in the wholesale energy market from price taker to price maker as a decision maker. Moreover, DERs can serve reserve in their normal operation. This opportunity facilitates Disco to provide reserve to the wholesale reserve market. The strategic behavior of a Disco in wholesale energy and reserve markets is modeled in this paper as a bi-level optimization problem. The operation problem of the Disco and the Independent System Operator (ISO) are modeled in the upper- and lower-level problems, respectively. Karush-Kuhn-Tucker (KKT) dualilty theory conditions are employed to transform the proposed nonlinear bi-level problem to a linear single level one. Numerical studies demonstrate the proficiency of the proposed model and the solution methodology.

Comparison of various operational statuses of PIEV aggregators with home-charged EVs and parking lots

Emerging technologies arising in modern power systems have propelled the presence of new agents to manipulate these facilities. Participation of plug-in electric vehicles (PIEVs) in the electricity market is one of the main issues in this environment. PIEV participation in market place can affect the agents strategy. Therefore, this paper investigates two states of power system where individual aggregators participate in the power market on behalf of home-charged PIEVs and parking lots (PLs) separately, as well as the coordinated version of the problem. Several scenarios are developed for deriving specific characteristics of PIEVs in home levels and in PLs. An optimization model is built and solved using mixed integer linear programming. The results are produced to suggest the optimum procedure for an aggregator to whether take the authority of home-charging PIEVs and PLs individually or coordinately.

Modeling Energy Demand Dependency in Smart Multi-Energy Systems

Smart local energy networks provide an opportunity for more penetration of distributed energy resources. However, these resources cause an extra dependency in both time and carrier domains that should be considered through a comprehensive model. Hence, this paper introduces a new concept for internal and external dependencies in Smart Multi-Energy Systems (SMES). Internal dependencies are caused by converters and storages existing in operation centers and modeled by coupling matrix. On the other hand, external dependencies are defined as the behavior of multi-energy demand in shifting among carriers or time periods. In this paper, system dependency is modeled based on energy hub approach through adding virtual ports and making new coupling matrix. Being achieved by SMESs, the dependencies release demand-side flexibility and subsequently enhance system efficiency. Moreover, a test SMES that includes several elements and multi-energy demand in output is applied to show the effectiveness of the model.

Effects of PEV Traffic Flows on the Operation of Parking Lots and Charging Stations

The introduction of plug-in electric vehicles (PEVs) in the electrical system is bringing various challenges. The main issue is incorporating the PEV owner’s preferences in the models. One of the main attributes representing the preference of the owners is their travel purposes, impacting on the traffic flow pattern. The PEVs’ traffic pattern defines the required charging schedule of the PEVs, and consequently, characterizes the operation of the charging facilities such as PEV parking lots (PLs). The deployment of resources such as PEV PL requires a detailed modeling of the factors affecting their operation. In this regard, this paper aims to model the power flow of the PEVs based on their traffic flow. Different travel types and purposes are considered for the PEVs traffic modeling. Two types of charging infrastructure (i.e., PLs and individual charging stations) are considered. The study is performed on a distribution network categorized based on the consumption patterns of the zones.

Location of parking lots for plug-in electric vehicles considering traffic model and market participation

This paper addresses the location of parking lots (PLs) to be used for plug-in electric vehicles (PEVs) by using a probabilistic traffic model and taking into account the PL participation in electricity markets. The PLs are used both for grid-to-vehicle and vehicle-to-grid. The system includes private or public charging stations only used for PEV charging. The traffic model considers the partitioning of the territory into areas. The case study is based on traffic and market data referring to Italy.

Modeling the cross impact of multi-energy player's price equilibrium in retail and wholesale markets

Integration of emerging energy resources in distribution level reveals new opportunities for decision makers to coordinate various energy vectors under the concept of multi-energy system (MES). In this paper, the behavior of a multi-energy player (MEP) who can trade more than one energy carrier to enhance operational flexibility of MES has been investigated. MEP participates in retail and wholesale energy markets to maximize its profit. The strategic behavior of MEP in these two markets is modeled as two synchronized bi-level problems. The problem is linearized and solved through CPLEX 12 solver. Numerical results show the behavior of MEP as a prosumer in the electricity market to make a smother demand and price profile. Moreover, the results reveal a mutual effect of local and wholesale equilibrium prices by increasing the market share of MEP.

Pricing G2V/V2G modes through characterizing the PEVs traffic behavior

In this paper, a mixed-integer linear programing (MILP) model for characterizing the traffic behavior of plug-in electric vehicles (PEVs) in an urban environment is proposed. The paper proposes the procedure to mathematically model the uncertain behavior of the PEVS. As the PEVs traffic pattern affects the potential of PEV parking lot (PL) in terms of available capacity and state of charge, the characterized PEVs are employed to provide the proper pricing schemes for the PEVs in PL. The results discuss the mutual effect of PEVs behavior on the profit of PL, as well as the effects of PLs tariffs on motivating PEVs to provide more flexibility for the PL. The results show that with a proper pricing scheme both parties (i.e., PEV owners and PL) can earn higher profits, while the charging requirements are met based on the preferences of the owners.