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This guest editorial summarizes the topics and the papers selected for the Special Issue on Flexible and Resilient Urban Energy Systems. After rigorous reviewing process, 21 papers are accepted for publication. These 21 accepted papers cover various aspects of urban energy systems and are distributed as following: situational awareness of urban energy systems (2 papers), quantification metrics of flexibility and resilience of urban energy systems (3 papers), vulnerability modeling of urban energy systems under various extreme events (3 papers), planning of flexible and resilient urban energy systems (4 papers), robust and resilient operation and control of urban energy systems (4 papers), recovery and restoration strategy of urban energy systems (2 papers), and coordination and interoperability of interconnected energy systems (3 papers). The Guest Editorial Board hopes this Special Issue can provide a valuable information for future research and advancements in the field of flexible and resilient urban energy systems., QC 20230920

Currently, fuel cell and hydrogen technology are attracting more and more attention as a kind of green and clean energy technology in the context of the increasingly stringent carbon emission requirements of the shipping industry. However, there are still many obstacles to their maritime application due to high costs and a lack of infrastructure. This paper conducts a literature survey of fuel cell maritime applications from four aspects: key technologies of fuel cell and hydrogen maritime applications, cost and standards. It can be concluded that ships powered by hydrogen fuel cells will have a broad application prospect with the maturity of the hydrogen industry chain and the improvement of standards and regulations. Two main contributions of this paper are to fully understand a whole-process perspective of hydrogen and fuel cell maritime application, and to provide the problems and future direction in this field, which can help relevant research institutions and scholars evaluate the development status of the industrial chain and find new valuable research topics., QC 20230704

Alongside the concern for environmental sustainability, the concept of Circular Economy, a term for an economic system designed to regenerate itself, has gained momentum. Circularity finds full expression in Local Energy Communities (LEC), a newly emerging setup wherein the local energy needs of a community are met independently, through the choice of shared solutions for energy production from renewable sources. Erstwhile the use of stationary energy storage systems for self-consumption optimization, load management, peak shaving, backup power and ancillary services, would foster the value of these Local Energy Communities. In this paper, we design a techno-economic analysis to assess the impact of the usage of Second-life Batteries for increasing the energy self-independence of those communities. A cost-minimization approach with technical and economic constraints is used for the analysis and is applied to a use case of Italy. This paper assesses the benefits that a Local Energy Community can entail while considering self-consumption maximization of PV generation, load shifting and grid balancing needs, while addressing the problem of high storage costs through the exploitation of second-life electric vehicles (EV) batteries, adding an extra layer for circularity. Scenarios related to maximizing the selfconsumption of photovoltaic generation and demand side management are designed considering four different LEC technology configurations. The results confirm LEC viability, showing lower energy bills for each scenario and greater benefits coupling a solar generation system with a storage solution., QC 20221021

This paper presents ODIN, an open dispatch model for the Nordic power system. We begin by performing a survey of existing models, and conclude that no model which simulates the different price areas in the Nordic power system and is truly open exists. Existing models either lack data to do an out-of-the-box simulation which accurately represents the Nordic power system, rely on proprietary software, or have a more coarse representation of the Nordic region. In contrast, ODIN has the following properties: (1) It is developed completely in Python and can be solved with open-source optimization tools, thus using no proprietary software. (2) It includes all data needed to do yearly simulations for the Nordic power system, with 35 years of data for weather-dependent production such as hydro power and wind power. (3) It represents all Nordic price areas and has been validated to reproduce historical production and transfer patterns. This paper describes the methodology and structure of the model and illustrates its features with examples and a case study., QC 20220214

The exchange of reactive power at the interface between distribution and transmission systems gains significant importance with ongoing relocation of generators to lower voltage levels. To keep transmission systems operation secure and stable, distribution systems may need to be more flexible when exchanging power at the interface with the overlaying grid. A flexibility measure of this interface is proposed by this paper through introduction of flexibility coefficients. These coefficients are calculated by comparing DSO capability and TSO desirability surfaces. These surfaces describe the distribution system’s capability to provide flexible reactive power exchange and the transmission system’s needs to use these flexibilities. Since the surfaces can be calculated independently, the newly proposed method of flexibility assessment can be applied without substantial exchange of system information between DSO and TSO. The proposed concept is illustrated on the Nordic 32 system for a case of the connection of two differently behaving distribution systems., QC 20200819

The exchange of reactive power at the interface between distribution and transmission systems gains significant importance with ongoing relocation of generators to lower voltage levels. To keep transmission systems operation secure and stable, distribution systems may need to be more flexible when exchanging power at the interface with the overlaying grid. A flexibility measure of this interface is proposed by this paper through introduction of flexibility coefficients. These coefficients are calculated by comparing DSO capability and TSO desirability surfaces. These surfaces describe the distribution system’s capability to provide flexible reactive power exchange and the transmission system’s needs to use these flexibilities. Since the surfaces can be calculated independently, the newly proposed method of flexibility assessment can be applied without substantial exchange of system information between DSO and TSO. The proposed concept is illustrated on the Nordic 32 system for a case of the connection of two differently behaving distribution systems., QC 20200819

The exchange of reactive power at the interface between distribution and transmission systems gains significant importance with ongoing relocation of generators to lower voltage levels. To keep transmission systems operation secure and stable, distribution systems may need to be more flexible when exchanging power at the interface with the overlaying grid. A flexibility measure of this interface is proposed by this paper through introduction of flexibility coefficients. These coefficients are calculated by comparing DSO capability and TSO desirability surfaces. These surfaces describe the distribution system’s capability to provide flexible reactive power exchange and the transmission system’s needs to use these flexibilities. Since the surfaces can be calculated independently, the newly proposed method of flexibility assessment can be applied without substantial exchange of system information between DSO and TSO. The proposed concept is illustrated on the Nordic 32 system for a case of the connection of two differently behaving distribution systems., QC 20200819

The exchange of reactive power at the interface between distribution and transmission systems gains significant importance with ongoing relocation of generators to lower voltage levels. To keep transmission systems operation secure and stable, distribution systems may need to be more flexible when exchanging power at the interface with the overlaying grid. A flexibility measure of this interface is proposed by this paper through introduction of flexibility coefficients. These coefficients are calculated by comparing DSO capability and TSO desirability surfaces. These surfaces describe the distribution system’s capability to provide flexible reactive power exchange and the transmission system’s needs to use these flexibilities. Since the surfaces can be calculated independently, the newly proposed method of flexibility assessment can be applied without substantial exchange of system information between DSO and TSO. The proposed concept is illustrated on the Nordic 32 system for a case of the connection of two differently behaving distribution systems., QC 20200819

The exchange of reactive power at the interface between distribution and transmission systems gains significant importance with ongoing relocation of generators to lower voltage levels. To keep transmission systems operation secure and stable, distribution systems may need to be more flexible when exchanging power at the interface with the overlaying grid. A flexibility measure of this interface is proposed by this paper through introduction of flexibility coefficients. These coefficients are calculated by comparing DSO capability and TSO desirability surfaces. These surfaces describe the distribution system’s capability to provide flexible reactive power exchange and the transmission system’s needs to use these flexibilities. Since the surfaces can be calculated independently, the newly proposed method of flexibility assessment can be applied without substantial exchange of system information between DSO and TSO. The proposed concept is illustrated on the Nordic 32 system for a case of the connection of two differently behaving distribution systems., QC 20200819

This paper describes new additions to the Rapid Parameter Identification Toolbox (RaPId), which is an open-source MATLAB toolbox for parameter estimation using models developed with the Modelica language and exported with the functional mock-up interface (FMI) Standard. These additions include an updated graphical user interface (GUI), an optimization method utilizing multiple starting points for a gradient descent optimization, and examples for different cyber-physical system applications such as the Duffing-Holmes equation modeling in a form of electrical circuit and a hydroelectric power plant modeling., QC 20211022

To lower CO2 emissions, policy makers want to integrate as much variable renewable energy (VRE) as possible into power systems. This has been translated into targets for VRE as a share of total electricity generation and policies that aim to maximize the use of electricity available from VRE sources. However, in this paper we demonstrate that it is a misconception that maximizing VRE production always lowers CO2 emissions. In fact there are many constraints in power system operation that can lead to situations when curtailing VRE reduces both costs and CO2 emissions. In this paper we identify these situations and constraints, and illustrate them with several examples. The examples show how different constraints from optimal power system operation, using economic dispatch (ED) and unit commitment (UC), can combine to create the seemingly paradoxical result that curtailing VRE reduces both costs and CO2 emissions. Broadly defined these situations can occur 1) due to network constraints which create the need for inefficient redispatch actions if VRE is not curtailed, 2) due to increased need for ramp capability and cycling from other units, and 3) due to reserve/security requirements which can be satisfied more efficiently by allowing VRE curtailment. To achieve the most economical and efficient operation of power systems, instead of VRE curtailment being seen as a measure of last resort to preserve system security, VRE should always be optimally dispatched through markets based on its true cost, thus maximizing the value of VRE to the system rather than its output., QC 20210628

The increasing penetration of distributed renewable energy resources brings a great challenge for real-time voltage security of distribution grids. The paper proposes a safe multi-agent deep reinforcement learning (MADRL) algorithm for real-time control of inverter-based Volt-Var control (VVC) in distribution grids considering communication delay to minimize the network power loss, while maintaining the nodal voltages in a safe range. The multi-agent VVC is modeled as a constrained Markov game, which is solved by the MADRL algorithm. In the training stage, the safety projection is added to the combined policy to analytically solve an action correction formulation to promote more efficient and safe exploration. In the real-time decision-making stage, a state synchronization block is designed to impute the data under the latest timestamp as the input of the agents deployed in a distributed manner, to avoid instability caused by communication delay. The simulation results show that the proposed algorithm performs well in safe exploration, and also achieves better performance under communication delay., QC 20230905

The demand for larger power density and torque for the power traction motors used in electrified transportation puts forward a requirement for better thermal management methods. Spray cooling is a promising direct liquid cooling technique that has been proved to possess high heat removal capability in previous research. This paper investigates the heat transfer characteristics of spray cooling on endwindings of electric machines via numerical simulation through an Eulerian–Lagrangian approach. The utilized numerical models and calculated results are validated with experimentally measured data. The influence of different parameters and options involved in the simulation settings on the final results, like the stream numbers for the spray injector, the constant heat flux versus constant temperature thermal boundary condition, the influence of splashing, the effect of heat conduction in the endwindings and the Saffman lift force, only solving the energy equation for the air after its flow field reaches a steady-state, are evaluated. Parameter analyses are also conducted for operation conditions, configuration of the spray nozzles, and material properties of the coolant liquid. It is found that larger flow rate, smaller droplet size, lower spray height, more nozzle numbers, larger thermal conductivity and smaller viscosity of the coolant liquid tend to increase the overall heat transfer performance., QC 20230830

Grid-forming converters operate as voltage sources behind impedance. This property makes them robust against Short-Circuit Ratio (SCR) variation, but vulnerable against large grid disturbances. As a precaution, grid forming converters have to embed adequate control algorithms to ensure a stable system operation under various grid conditions, to deal with excessive overloadings mainly caused by faults, and to guarantee a stable re-synchronization after fault clearance. These expectations have been met in previous works considering balanced conditions. Nevertheless, the extension of the grid-forming control to deal with unbalanced grid conditions considering current limitation and angular stability is a point rarely discussed in the literature. To fill this research gap, this paper proposes an Extended Power Synchronization Method (EPSM) that allows the system to operate under balanced and unbalanced grid conditions while meeting the Fault Ride-Through requirements (FRT). The proposed method is a direct voltage control-based, which embeds a threshold current control loop, which is enabled only when a fault is detected. Additionally, the control is equipped with an algorithm that modifies the active power control during faults to aid the power converter to remain synchronized after fault clearance. The effectiveness of the proposed control has been demonstrated through time-domain simulations., QC 20230810

This paper first proposes an optimization model for Multi-Objective Optimal Power Flow (MO-OPF) problem in AC–DC networks. The considered objective functions are the fuel cost, active power losses, and environmental emission. The AC and DC power flow equations, the converter operating limits, the voltage magnitude limits, and line capacity limits are considered in the proposed AC–DC MO-OPF model. Then an equivalent Gradient Dynamical System (GDS) for the AC–DC MO-OPF model is derived. Each equilibrium point of this GDS is a Karush–Kuhn–Tucker (KKT) point of the original AC–DC MO-OPF model. In Theorem 1, we derive condition under which this KKT point is a saddle point of the original AC–DC MO-OPF problem. The equivalent GDS has the property that it can be solved using a distributed solution algorithm. Every bus in the AC–DC power grid is considered as a local agent in the proposed distributed GDS algorithm, which only obtains information only from its neighbors. In Theorem 2, we prove that proposed distributed approach is locally convergent to the saddle point of the original AC–DC MO-OPF problem. To show the performance of our distributed approach to solve our developed AC–DC MO-OPF model, the simulation results based on several test systems are provided., QC 20230707

The increasing importance of cross-border trade has brought the topic of allocating cross-border transmission capacity under the limelight. In this paper, we focus on two different transmission capacity calculation methods, namely, Available Transfer Capacity and Flow-based Capacity allocation, in the continuous intraday electricity market. The effect of these two methods is studied on the continuous intraday electricity market through an agent-based model comprising various types of trading agents. It also models market operator agent and transmission system operator agent inspired by the Single Intraday Coupling project in Europe. The price-volume decisions for the orders posted by the market participants are determined by two different strategies where one of them adapts to changing market conditions and new information while the other is naive. The model accounts for ramping constraints which enables the analysis of the trading behavior and interaction of agents across multiple delivery products simultaneously. A switch parameter is availed in the trading timeline for the thermal and storage agents to change from a less conservative approach of ignoring the ramping and charging/discharging rate constraints respectively to considering them. An interplay between different switch parameters and cross-border transmission capacity calculation methods is studied., Not duplicate with DiVA 1690946QC 20230706

Combined heat and power (CHP) plants are main generation units in district heating systems that produce both heat and electric power simultaneously. Moreover, CHP plants can participate in electricity markets, selling and buying the extra power when profitable. However, operational decisions have to be made with unknown electricity prices. The distribution of unknown electricity prices is also not known exactly and uncertain in practice. Therefore, the need of tools to schedule CHP units' production under distributional uncertainty is necessary for CHP producers. On top of that, a heating network could serve as a heat storage and an additional source of flexibility for CHP plants. In this paper, a distributionally robust short-term operational model of CHP plants in the day-ahead electricity market is developed. The model accounts for the heating network and considers temperature dynamics in the pipes. The problem is formulated in a data-driven manner, where the production decisions explicitly depend on the historical data for the uncertain day-ahead electricity prices. A case study is performed, and the resulting profit of the CHP producer is analyzed. The proposed operational strategy shows high reliability in the out-of-sample performance and a profit gain of the CHP producer, who is aware of the temperature dynamics in the heating network., QC 20230503

The modular multilevel converter (MMC) based high-voltage dc (HVDC)-connected offshore wind farm (OWF) is power electronic converter dominated power system, where the conventional current differential protection may not operate effectively. Based on the basic operation principle of the current differential relay, this paper points out that the phase difference ((fidiff) of fault currents from MMC and OWF should be limited within a specific range, i.e. (-(fidiffmax, (fidiffmax), to guarantee the reliable tripping of the current differential relay. Yet, the highly control-dependent fault currents from the MMC and OWF could yield an arbitrary (fidiff that might beyond (-(fidiffmax, (fidiffmax), which leads to the possible malfunction of the current differential relay. To tackle this challenge, the coordinated control method of MMC is proposed to align the phase angle of its fault current with that of the OWF, such that (fidiff is an element of (-(fidiffmax, (fidiffmax) can be always guaranteed, so as the reliable operation of the current differential relay. Finally, the proposed coordinated control is verified by the electromagnetic transient (EMT) simulations in PSCAD and the real-time digital simulator (RTDS)., QC 20230227

This paper deals with general bilinear feasibility problems. A nonlinear transformation is introduced that reformulates a general bilinear feasibility problem as a Linear Matrix Inequality (LMI) problem augmented with a single non-convex quadratic constraint. The single non-convex quadratic constraint has a regular concave constraint function. Due to the LMI part of this formulation, it is easier to analyze, and we prove that the solution space of this formulation is located inside several ellipsoids and outside a sphere. This leads to our proposed Inside-Ellipsoid and Outside-Sphere (IEOS) model for general bilinear feasibility problems. Then, the feasibility analysis of our proposed IEOS model is performed. The related necessary feasibility conditions and sufficient feasibility conditions are theoretically developed. Moreover, an iterative algorithm for solving our IEOS model is also proposed.Two applications including matrix-factorization problem in control systems and power-flow prob-lem in power systems are considered to evaluate the practicality of our proposed approach. Both problems are formulated as IEOS models. It is shown that our proposed model can provide more accurate solutions to these problems as compared to previous competing approaches in the relevant literature., QC 20230227

Recently, there has been an urgent tendency to steer the transport system towards zero-emission. Along natural gas vehicles, electric and hydrogen vehicles represent a promising way to a low-carbon system. Since the development of these vehicles relies on advances of refueling stations, their economic and operational aspects need to be considered. Therefore, this paper addresses a multi-product charging station for refilling electric, hydrogen and natural gas vehicles. The station participates in day-ahead and intra-day markets where the market price is subject to the uncertainty. For charging station participating in sequential markets with different prices, it is necessary to consider the coordinated bidding. Taking into account the sequential clearing of these markets and the gradual realization of market prices, the bidding problem is formulated as a two-stage stochastic program. In order to solve this large-scale stochastic program with a huge number of scenarios, the rolling planning method in combination with sample average approximation and SCENRED tool are applied. The study aims to attain the optimal operation of devices and bidding curves of the charging station in order to maximize its profit. The obtained average optimality gap based on Monte Carlo sampling approach, which is less than 1%, proves the effectiveness of our proposed algorithm in solving this large scale stochastic optimization. The submitted bidding curves to the intra-day market are found to be dependent on changes in the day-ahead market prices. Tornado diagrams indicate that the selling price and demand of electricity are ranked as the most effective factors on profit., QC 20230127

The growing prominence of electric vehicle (EV) aggregators in the modern power system is drawing more attention towards modeling their behavior in the short-term electricity markets. The demand-side flexibility offered by the EVs can be leveraged to reduce their charging costs. In this paper, the participation of an EV aggregator in the intraday and balancing market is modeled as a multistage stochastic programming problem. The computational complexity introduced by the peculiarities of the intraday market is solved by a progressive hedging algorithm (PHA), a scenario-based decomposition technique. A randomized scenario sampling approach is implemented to accelerate the PHA which is further improved with a parallel randomized PHA. Finally, an asynchronous version of the parallel randomized PHA is leveraged to speed up the multistage model of EV aggregator trading. We compare the computation time of the modified versions of the PHA algorithm with the conventional PHA for the proposed EV aggregator model. Furthermore, we also show the value of EV aggregator trading in the intraday and balancing markets by comparing its cost to baseline models., QC 20221024

This paper presents a novel methodological approach for the optimal day-ahead energy market bidding behavior of a cascaded hydropower plants (HPPs) portfolio in the sequential electricity markets. The understudy markets are day-ahead energy market and manual frequency restoration reserve (mFRR) markets in both capacity and energy setups. The introduction of the mFRR capacity market ensures transmission system operators (TSOs) about the availability of energy bids in the real-time market, which acts as binding constraints in the mFRR energy markets. As a determining factor, the active-time duration of mFRR energy bids is uncertain at the time of day-ahead bidding, which is modeled as the intervals in our robust optimization, while the electricity prices are considered as the scenarios in the stochastic optimization. Hence, we have proposed a novel stochastic adaptive robust optimization to address the bidding problem in the face of uncertainties accurately. The results show a considerable improvement compared to the conventional fully-stochastic approach in the case study of Swedish cascaded hydropower plants., QC 20220809

This paper proposes a distributed gradient dynamics approach for solving Multi-Objective AC Optimal Power Flow (MO-ACOPF) problem. The fuel cost, environmental pollution, and network loss are considered as objective functions. The non-convex MO-ACOPF problem is reformulated as a gradient dynamical system. We derive condition under which the equilibrium point of the proposed gradient dynamical system is the saddle point of the MO-ACOPF Lagrangian function. We propose a distributed solution algorithm for derived MO-ACOPF gradient dynamical system. In the distributed solution algorithm, each bus in the power network is assumed as a local agent, which only uses information from its neighbor agents to compute optimal operating points. We prove convergence of our distributed algorithm to the equilibrium point of the MO-ACOPF gradient dynamical system (and accordingly to the primal and dual optimum of original MO-ACOPF). Accordingly, our proposed approach has the following main advantages: (a) it is a distributed and decentralized algorithm and accordingly it needs less computational time as compared to the centralized model, (b) it has the proof of convergence to the global optimal solution, and (c) it is suitable for varying loads in power networks. The simulation results based on standard IEEE 14-, 30-, 39-, 57-, 118- and 300-bus test systems in different scenarios are carefully studied. The proposed distributed gradient dynamics provides the best results compared to the relevant literature as illustrated by simulation results., QC 20220617

Parameter estimation of power plants is one of the main challenges of power system studies. Among different components of a power plant, excitation system (EXS) has great importance because of its effect on dynamic stability of power systems. Thus, it is vital to have accurate models of EXSs for power system dynamic studies. Since the field voltage and current are not accessible in brushless EXSs, parameter estimation of them is more difficult and challenging. Therefore, a new method is proposed in this paper to estimate field voltage signal using other measurements of the synchronous generator (SG). The proposed method is carried out through three stages; 1) parameter estimation of the SG using load rejection tests, 2) field voltage estimation, and 3) parameter estimation of EXS. The proposed method is applied to a 147 MVA industrial gas unit. The estimated model outputs are compared to the experimental results to show the accuracy and effectiveness of the proposed method., QC 20220531

With increasing scarcity in water resources around the world, policy-makers are increasingly looking to water trading arrangements to ensure that available surface water is used as efficiently as possible. However, traded water must be able to be transported from its source to its point of use. In many real-world applications this transportation occurs over a gravity-fed river network. The physical characteristics of this network (such as the shape of weirs) determines how quickly water flows from point to point, as well as setting upper and lower limits on the rate of flow. The choice of the path of injections and extractions which maximises overall welfare must take into account these physical characteristics. This paper characterises the profile of water injections and extractions, and the corresponding path of prices, that maximises overall economic welfare, subject to the hydrology of a stylised river network. We illustrate the outcomes of the model in simple water networks, and show how even relatively simple changes in supply and demand conditions can lead to dynamic variation in the profile of prices and injection/extraction across the river system. We show how this model can act as the foundation for a smart market for water trading arrangements., QC 20220322

With the growing level of uncertainties in today's power systems, the vulnerability analysis of a power system with uncertain parameters becomes a must. This paper proposes a two-stage adaptive robust optimization (ARO) model for the vulnerability analysis of power systems. The main goal is to immunize the solutions against all possible realizations of the modeled uncertainty. In doing so, the uncertainties are defined by some predetermined intervals defined around the expected values of uncertain parameters. In our model, there are a set of first-stage decisions made before the uncertainty is revealed (attacker decision) and a set of second-stage decisions made after the realization of uncertainties (defender decision). This setup is formulated as a mixedinteger trilevel nonlinear program (MITNLP). Then, we recast the proposed trilevel program to a single-level mixed-integer linear program (MILP), applying the strong duality theorem (SDT) and appropriate linearization approaches. The efficient off-the-shelf solvers can guarantee the global optimum of our final MILP model. We also prove a lemma which makes our model much easier to solve. The results carried out on the IEEE RTS and modified Iran's power system show the performance of our model to assess the power system vulnerability under uncertainty., QC 20220309

The planning of future power systems with high shares of renewable generation requires modelling large and complex systems over long time periods, resulting in models which are computationally heavy to solve. For this reason methods that can be used to decrease the size of power system dispatch models are needed. A common method in large scale planning models is to decrease the model size by increasing the size of the time steps. However, using larger time steps makes the representation of variability of renewable generation and load less accurate, which can affect the results from the model. In this paper, we investigate the possibility to use a power-based version of an economic dispatch model to decrease the model time resolution while getting results which are close to the original high-resolution model. We implement both power-based and the conventional, energy-based, versions of a dispatch model with different time resolutions, and show that the power-based model has better agreement with the high-resolution model, especially as the model time step increases. For example, using the power-based model gives more accurate results for wind power curtailment in a high-renewable scenario., QC 20220202

An appropriate battery thermal management system is essential for electric vehicles to keep an optimal working temperature range with minimal temperature difference, and meanwhile to ensure the battery is more efficient and safe. In this paper, the liquid cold plate thermal management system with heat pipes is proposed to investigate the thermal characteristic of LiFePO4 battery pack during various discharge rate operations. A three-dimensional numerical model based on standard k-epsilon turbulent model is developed to realize the visible analysis of fluid flow and heat transfer for the proposed thermal management system. The 50 Ah battery module is used in the experiment to validate the cooling effects of proposed thermal management system relied on heat pipes, and its performance is compared with liquid cold plate without heat pipes. Furthermore, the cooling performance of the cold plate with heat pipes could be further improved through the orthogonal experiment design, the maximum temperature of battery cell and temperature difference of battery module could be dropped by 6.95% and 11.08%, as compared with the original design. What's more, the channel height of cold plate with heat pipes has the greatest effect on the maximum temperature of battery cells and temperature difference of battery modules., QC 20210217

Protection system design for high-voltage direct-current (HVDC) grids using DC circuit breakers (DCCBs) is not straightforward. Both hardware parameters, such as line inductors and DCCBs, as well as software parameters, such as protection threshold settings and protection margins, have to be taken into account and interact. Previous studies focused on the impact of specific parameters (e.g., line inductors) while other parameters (e.g., maximum DCCB currents) were checked manually for compliance with constraints. This paper presents a new holistic method for HVDC grid protection design. The approach is no longer exclusively based on parameter sweeps but solves HVDC grid protection as a classic optimization problem with an optimization goal and constraints. Electromagnetic transient (EMT) simulations are embedded into the optimization tool such that the system dynamic response is taken into account. Results for two example test cases and two example optimization goals are provided. For instance, the method can achieve a reduced sum of line inductors compared to an initial guess. The proposed method is useful to find a more optimally designed HVDC protection system, and practical because it makes sure that the constraints (e.g., maximum DCCB current, no converter blocking and large protection margins) are fulfilled., QC 20210720

This paper presents a security constrained unit commitment (SCUC) with continuous intra-hour time-varying reserves. The hourly formulation extends the power-based UC formulation and has reserves which vary continuously within the hour, as opposed to the traditional hourly energy-based SCUC that uses constant reserves within the hour. We show that the traditional hourly energy-based formulation cannot ensure N-1 security at all times, since this formulation is not able to take the power trajectories of units within the hour into account. This is remedied by an hourly power-based version which allows the formulation of contingency constraints to guarantee N-1 security at all times within the hour. The proposed formulation uses continuous time-varying reserves which lowers the cost for providing reserves and makes better use of units’ flexibility while still ensuring N-1 security. The energy-based and power-based formulations are evaluated using different versions of a 5-min security-constrained economic dispatch (SCED) based on real load data, thus simulating the real time operation of the system under different assumptions for reserve procurement. The results show that the power-based formulation increases security compared to the energy-based formulation, both if reserves are fixed to the values from the SCUC or co-optimized in real time by the SCED.Previous article in issue., QC 20210903

The power system operators are facing significant challenges in the operation due to the increasing penetration level of renewable energy sources (RESs). The flexibility from the district heating system (DHS) is attracting considerable interest to deal with RES uncertainty. This paper formulates a distributionally robust chance-constrained (DRCC) optimization model of the integrated electricity and heating system (IEHS) dispatch to hedge the uncertainty of RES and exploit the flexibility of the DHS. In particular, the uncertainty from the electrical power system (EPS) is propagated to the DHS so that both systems can respond to the uncertainty of RES. The uncertainty of the wind power is modeled by an ambiguity set, which defines a family of probability distributions with the same first and second moment property. Real-time regulation actions of both the EPS and DHS to respond to the wind power forecast errors are modeled through the data-driven affine control policies. To achieve computational tractability, the proposed DRCC model is reformulated as a second-order cone program (SOCP). The simulation results tested on the integrated six-bus and seven-node system demonstrate that the proposed DRCC model outperforms the chance-constraints dispatch based on Gaussian distribution for the secure operation of the IEHS. (c) 2021 Elsevier Ltd. All rights reserved., QC 20210524

Simulations and analysis of large hydro-thermal power systems easily become computationally heavy without simplifications of the system at hand. Hydropower, in particular, presents a challenge as complex river systems add a large amount of variables and linked constraints to the analysis. A possible simplification is to use aggregated Equivalent models for different parts of the hydrosystem which give similar results, with respect to e.g. power production, as a more detailed description of the Original system. In this paper, novel linear multi-scenario Equivalent models for hourly simulations of nonlinear hydropower systems are developed and their performance investigated. The new models consider multiple scenarios for inflow, price and start resp. end content in the reservoirs as well as reserves for balancing capacity. The performance analysis is based on case studies over Swedish hydropower systems located in the electricity trading area SE1. The average relative error in power production is 9-15% and the computation time is reduced from 9 hours to between 0.4 and 36 seconds., QC 20200915

With renewable energy sources becoming an ever-increasing share of the generation mix of modern power systems, having the proper amount of reserve becomes of utmost importance to ensure the short-term as well as the long-term adequacy level in the system. This reserve can be in the form of generation assets or it can be provided from assets on the demand side. The contribution that these resources make to the adequacy of the system is referred to as their capacity credit. This paper derives a methodology for calculating the capacity credit of a resource in a multi-area system. Based on that, an approach is developed that quantifies how strategic demand reserve should be distributed between power system areas in a multi-area system in order to reach individual long-term reliability targets in all areas. Lastly, an algorithm is derived that optimizes the coordinated procurement of multi-area strategic demand reserve by counterbalancing the value of lost load against the costs related to maintaining generation adequacy. A combination of an iterative multi-variate gradient approach and a Monte Carlo simulation with an efficient sensitivity analysis allows this to be achieved in a computationally economical way. An illustrative example and numerical simulations of test systems using real data from the Nordic power system demonstrate the effectiveness of the proposed approach., QC 20200714