Modeling a cooperation environment for flexibility enhancement in smart multi-energy industrial systems

Environmental aspects have been highlighted in architecting future energy systems where sustainable development plays a key role. Sustainable development in the energy sector has been defined as a potential solution for enhancing the energy system to meet the future energy requirements without interfering with the environment and energy provision. In this regard, studying the cross-impact of various energy vectors and releasing their inherent operational flexibility is main topic. Thecoordinationofvariousenergyvectorsundertheconceptofmulti-energysystem (MES)hasintroducednewsourcesofoperationalflexibilitytothesystemmanagers. MES considers both interactions among the energy carriers and the decision makers in an interdependent environment to increase the total efficiency of the system and reveal the hidden synergy among energy carriers. This thesis addresses a framework for modeling multi-energy players (MEP) that are coupled based on price signal in multi-energy system (MES) in a competitive environment. MEP is defined as an energy player who can consume or deliver more than one type of energy carriers. At first, the course of evolution for the energy system from today independent energy systems to a fully integrated MES is presented and the fractal structure is described for of MES architecture. Moreover, the operational behavior of plug-in electric vehicles’ parking lots and multi-energy demands’ external dependency are modeled in MES framework to enhance the operational flexibility of local energy systems (LES). In the fractal environment, there exist conflicts among MEPs’ decision making in a same layer and other layers. Realizing the inherent flexibility of MES is the main key for modeling the conflicts in this multi-layer structure. The conflict between two layers of players is modeled based on a bi-level approach. In this problem, the first level is the MEP level where the player maximizes its profit while satisfying LES energy exchange. The LES’s exchange energy price is the output of this level. In the lower level, the LESs schedule their energy balance, based on the upper level input price signal. The problem is transformed into a mathematical program with equilibrium constraint (MPEC) through duality theory. In the next step, high penetration of multi-energy players in the electricity market is modeled and their impacts on electricity market equilibrium are investigated. In such a model, MEP participates in the local energy and wholesale electricity markets simultaneously. MEP and the other players’ objectives in these two markets conflict with each other. Each of these conflicts is modeled based on bi-level programming. The bi-level problems are transformed into a single level mixed-integer linear problem by applying duality theory

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

Assessing the effectiveness of decision making frameworks in local energy systems

This paper investigates the effectiveness of using different decision-making frameworks in local energy systems (LES) through the assessment of the long-term equilibrium of energy players. For this purpose, the energy system is modelled through two levels of multi-energy player (MEP) and LES, coupled by energy price signals. The conflict between the decision-making of these two levels of players is modelled through a bi-level approach. A mathematical problem with equilibrium constraint is formulated by applying the duality theory, resorting to a linear representation of the constraints. The solution is found by using the CPLEX12 solver. The numerical results show the characteristics of the MEP behaviour in different energy aggregation modes for the LES, with centralised management or uniform pricing. The MEP may find benefits from possible synergies among the LES due to availability of energy carriers with complementary characteristics

Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs

The operation problem of a micro-grid (MG) in grid-connected mode is an optimization one in which the main objective of the MG operator (MGO) is to minimize the operation cost with optimal scheduling of resources and optimal trading energy with the main grid. The MGO can use incentive-based demand response programs (DRPs) to pay an incentive to the consumers to change their demands in the peak hours. Moreover, the MGO forecasts the output power of renewable energy resources (RERs) and models their uncertainties in its problem. In this paper, the operation problem of an MGO is modeled as a risk-based two-stage stochastic optimization problem. To model the uncertainties of RERs, two-stage stochastic programming is considered and conditional value at risk (CVaR) index is used to manage the MGO’s risk-level. Moreover, the non-linear economic models of incentive-based DRPs are used by the MGO to change the peak load. The numerical studies are done to investigate the effect of incentive-based DRPs on the operation problem of the MGO. Moreover, to show the effect of the risk-averse parameter on MGO decisions, a sensitivity analysis is carried out

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

Aggregation of Distributed Energy Resources Under the Concept of Multienergy Players in Local Energy Systems

In recent years, in addition to the traditional aspects concerning efficiency and profitability, the energy sector is facing new challenges given by environmental issues, security of supply, and the increasing role of the local demand. Therefore, the researchers have developed new decision-making frameworks enabling higher local integration of distributed energy resources (DER). In this context, new energy players appeared in the retail markets, increasing the level of competition on the demand side. In this paper, a multi-energy player (MEP) is defined, which behaves as a DER aggregator between the wholesale energy market and a number of local energy systems (LES). The MEP and the LES have to find a long-term equilibrium in the multienergy retail market, in which they are interrelated through the price signals. To achieve this goal, in this paper the decisionmaking conflict between the market players is represented through a bi-level model, in which the decision variables of the MEP at the upper level are parameters for the decision-making problem at the lower level (for the individual LES). The problem is transformed into a mathematical program with equilibrium constraints by implementing duality theory, which is solved with the CPLEX 12 solver. The numerical results show the different MEP behavior in various conditions that impact on the total flexibility of the energy system

Modeling the carrier dependencies on demand-side in a smart multi-energy local network

Smart local energy networks represent a key option for more penetration of sustainably developed facilities. These facilities can cause an extended dependency in both time and carrier domains which should be considered through a comprehensive model. This paper introduces a new concept of internal and external dependencies. The concept is related to penetration of energy converters on demand side and the effects they bring to the system. Being achieved by implementation of smart grid, dependencies release operational flexibility and subsequently enhance the system efficiency. The model contains, carrier based demand response which preserves consumers satisfaction by utilizing the flexibility in exchanging the input energy carrier instead of changing end-usage pattern. The paper develops the coupling matrix model for smart multi-energy systems considering the external dependency as an added module to the overall model

Stochastic Modelling of Multi-Energy Carrier Dependencies in Smart Local Networks with Distributed Energy Resources

In a multi-energy system, there are different types of dependencies among the energy carriers. Internal dependencies refer to possible changes in the energy source in the presence of energy converters and storage and are managed by the system operator through the control strategies applied to the equipment. External dependencies are due to the choice of the energy supply according to customer preferences, when alternative solutions are available. This paper introduces a new model of the external dependencies within a multi-generation representation based on energy hubs. The external dependencies are addressed through a stochastic model, in order to take into account the possible uncertainty in the customers’ decisions. This model is then used to introduce carrier-based demand response, in which the user participates in demand response programmes aimed at promoting the shifting among different energy sources by preserving the service provided to the end users. The results obtained from the new model in deterministic and stochastic cases indicate the appropriateness and usefulness of the proposed approach