Operation Of Multi-carrier Energy Systems Research Articles

Electric vehicles and the operation of multi-carrier energy systems in the smart grid: a review study

Smart grids have been connected to energy hubs (EHs) with a range of energy carriers and storage capacity to increase the efficiency, flexibility, and dependability of the energy system. One of the most challenging problems in smart grids nowadays is the scheduling of EHs. Although the interaction of several devices, such as EHs and electric vehicle charging stations (EVCSs), can help improve their performance, developing such intricately interwoven systems is difficult. In this paper, with the help of several papers, the impact of EVCSs on the optimal operation of EHs is investigated, despite the uncertainty surrounding electric vehicle charging behaviours. Additionally, the formulation concerning the energy hub's component parts, electric vehicles (EVs) in a single hub, and interconnected hubs is investigated. In addition, some simulation results from reviewed papers are presented and analyzed in this paper. The main goal of this paper is to analyze the effects of EVCS on the optimal management of EHs. Furthermore, some models of energy hubs integrated by EVCS are presented, and a numerical analysis is conducted to examine the function of EVCS in conjunction with electrical and thermal storage systems.

Congestion management for coordinated electricity and gas grids in the presence of multi-energy hubs: A risk-based optimal scheduling

Due to the development of cost-effective and high-efficient infrastructures in electricity and natural gas carriers, the need for optimal operation of multi-carrier energy systems is essential. On the other side, with the increasing penetration of renewable energy resources (RERs), and power demand, the congestion management (CM) of power systems is turning out to be a significant challenge for system operators. Motivated by these, this paper focuses on the congestion management problem for a multi-energy hub (MEH) system incorporated by RERs, flexible energy resources (FERs), and different energy conversion technologies to supply electrical, heat, and cooling demands, aiming to minimize the total operating costs. In current practice, the steady-state Weymouth equation and AC-power flow method for natural gas and electricity networks are implemented to investigate the interdependency of power and gas networks. The renewable energy generation variations are mitigated by the scenario-based stochastic framework. Also, to manage the risk associated with random variables, the downside risk constraint (DRC) model is employed to analyze the changes in the expected cost per several values of the risk parameters. The numerical results demonstrate that the proposed model can significantly utilize the energy hub’s flexibility to alleviate gas and power congestion while decreasing the total operation cost.

A Novel Flexible Method for Optimal Operation Modeling of Multi-Carrier Energy Systems

This research suggests a new flexible method for the optimal operation of multi-carrier energy systems based on optimization techniques for different weather conditions and seasons. The results apply to different modes (a hot summer day, a cold winter day and a normal day). A new cost function from the operator’s point of view is suggested considering the constraints on consumable gas supply and electrical energy in the cold and hot seasons respectively. Furthermore, a novel algorithm is suggested that gives the economical values of energy carriers, final cost, and the percentage of the direct electrical energy supply and outside the hub. In this method, load data, related prices, constraints, and penalties are applied to the suggested model, and afterward hub optimization assists in finding the optimal operation and costs. MATLAB software is used to check the results and the simulation outputs confirming the effectiveness of the proposed method.

Smart energy hub optimization in presence of stochastically modeled renewables and loads

Integration of information technology with multi-carrier energy systems has paved the way for smart energy hubs (SEHs). Such energy hubs require stochastic modeling of intermittent renewable energy resources (RERs) and fluctuating demands to realize their optimal operation. Many excellent works are available related to their optimization but none of the existing works presents a comprehensive model which not only incorporates the stochastic nature of RERs and demands but also taps demand response potential in the presence of system storages. To fill this gap, this paper proposes a comprehensive model for an SEH which incorporates the stochastic nature of electrical, heating, and cooling demands in the presence of RERs, batteries, and thermal storages. In addition, optimal shifting of electrical, heating, and cooling loads are performed to further reduce the operational cost of SEH considering a price-based demand response program (DRP). The cost minimization objective is formulated as a mixed-integer linear programming (MILP) optimization problem. Five different cases are analyzed considering the inclusion and exclusion of storage and RERs with different percentages of shiftable loads for DRP. The proposed complex model is solved using CPLEX in GAMS environment. With RERs, cost reductions of 5.25% and 18.96% are observed in the operational cost of SEH without tapping demand response (DR) potential. When 10% and 20% loads are deemed to be shiftable for DR, operational costs reduce to 20.15% and 21.43% respectively with RERs and energy storages. Results of the study can support energy managers in the optimal operation of multi-carrier energy systems.

A Multi-objective Optimization Framework for Dynamic Planning of Energy Hub Considering Integrated Demand Response Program

The integrated operation of multi-carrier energy systems has attracted special attention due to its increased efficiency, improved flexibility and reduced pollution. It should be noted that accurate and optimal design of these systems will have a high impact on their optimal operation. Hence, this paper presents a multi-objective optimization framework for long-term planning of energy hub, in which equipment degradation and integrated demand response (IDR) programs are considered. The planning problem has been solved for 20 years and all short-term operation constraints have been taken into account. The problem is modeled using the fuzzy max-min method as a three-objective optimization problem, in which the objective functions include total cost, emission and hub losses. The simulation results demonstrate that the IDR program has reduced the total cost by about 9% by reducing equipment capacity and operating costs. In addition, the results illustrate that the reduction of 29% and 31% of losses and emission, led to a 49% increase in total costs. Overall, the results demonstrate that the proposed model, considering the equipment degradation and the annual load growth, leads to the optimal design of the hub structure and guarantees the supply of load until the end of the planning period.

Optimal resilient operation of multi-carrier energy systems in electricity markets considering distributed energy resource aggregators

This paper presents a novel iterative three-level optimization framework for the optimal resilient operational scheduling of active multi-carrier energy generation and distribution systems. The main contribution of this paper is that the proposed framework simulates the day-ahead and real-time pre-event preventive and post-event corrective actions for external shocks and explores the effectiveness of risk-averse operational strategies on the system’s costs. The solution methodology is another contribution of this paper that finds the optimal scheduling of distributed energy resources and switching of electrical switches and district heating and cooling control valves. At the first stage, the optimal day-ahead scheduling of distributed energy resources and the initial value of the risk control parameter are determined using robust optimization. At the second stage, the optimal real-time market scheduling of distributed energy resources is performed. Finally, at the third stage, different extreme shock scenarios are considered, the effectiveness of corrective actions are investigated, and the value of risk control parameter is modified. The proposed method was successfully applied to the modified 123-bus test system and 600 scenarios of external shocks were considered. The proposed process successfully reduced the expected cost of the.123-bus system by about 74.59% for the worst-case external shock. Further, the algorithm reduced the aggregated expected values of operational and interruption costs by about 57.73% for all of the 600 cases of the considered external shocks.

Optimal operation of multi-carrier energy networks with gas, power, heating, and water energy sources considering different energy storage technologies

Abstract The investigation of interdependency among energy carriers in different energy networks is beneficial for network operators in minimizing the operation cost of the whole networks and supplying the energy demands continuously. This study aims at evaluating the effectiveness of considering interconnections among energy sources, which is known as multi-carrier energy systems, on the operation of the energy networks. The proposed scheme aims to analyze the gas, power, heating, and water energy sources and their interdependencies in operation of multi-carrier energy networks considering the gas and power networks constraints and interdependent constraints of all the energy carriers. Accordingly, the role of combined heat and power technology, gas-fired power plants, pumped-storage systems, gas storage, heat buffer tank, and wind turbines as well as the power and gas network constraints are studied in the current work. The operation of multi-carrier energy systems in the presence of the above-mentioned technologies are studied to meet daily power, gas, heating and water loads. The proposed scheme is implemented in a case study to evaluate the practicality and performance of the scheme, which is analyzed by providing two cases for the selected multi-carrier energy network.

Dynamic long-term expansion planning of generation resources and electric transmission network in multi-carrier energy systems

In this paper, a new framework is proposed for long-term generation and transmission expansion planning in multi-carrier energy systems (MCES). The MCES considered here consists of combined heat and power (CHP), gas furnace, power generation unit and transmission lines associated to natural gas and electrical networks. In the proposed framework, by minimizing the total investment and operation costs, optimal capacity, location and time of installing of new heat and electrical generation resources and also electric transmission lines are determined in a multi-year horizon. A linearized AC load flow equations is used for modeling effects of electric transmission network and is compared with DC load flow model. Also, a linearized model of accurate gas flow equations in natural gas transmission pipelines is used and is compared with a simple model. By using linear models for energy transmission network, the expansion problem is converted to a mixed integer linear programming (MILP) problem. By solving the MILP model by GAMS in which mathematical algorithm is used, optimal operation and expansion strategies on heat and power generation resources as well as electric transmission lines are obtained over the planning horizon. Performance of the proposed model is evaluated through two system tests, where transmission losses, overall system efficiency, reliability of supply and emissions are considered as metrics. Simulation results show importance of energy transmission network modeling in investment and operation of MCES in the long-term.