Jiarui Zhang, Yunfei Mu, Zeqing Wu, Zhe Liu, Yi Gao, Hongjie Jia, Hairun Li
Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic-based model predictive control approach (AA-MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH-based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA-MPC approach that takes the thermal energy for emergency building heating as a time-varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic-based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.
{"title":"Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic-based model predictive control approach","authors":"Jiarui Zhang, Yunfei Mu, Zeqing Wu, Zhe Liu, Yi Gao, Hongjie Jia, Hairun Li","doi":"10.1049/esi2.12082","DOIUrl":"10.1049/esi2.12082","url":null,"abstract":"<p>Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic-based model predictive control approach (AA-MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH-based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA-MPC approach that takes the thermal energy for emergency building heating as a time-varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic-based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"5 1","pages":"40-53"},"PeriodicalIF":2.4,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44943080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Harold R. Chamorro, Edgar O. Gomez-Diaz, Mario R. A. Paternina, Manuel A. Andrade, Emilio Barocio, Jose L. Rueda, Francisco Gonzalez-Longatt, Vijay K. Sood
Electrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro-mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest data-analytic technologies.
{"title":"Power system coherency recognition and islanding: Practical limits and future perspectives","authors":"Harold R. Chamorro, Edgar O. Gomez-Diaz, Mario R. A. Paternina, Manuel A. Andrade, Emilio Barocio, Jose L. Rueda, Francisco Gonzalez-Longatt, Vijay K. Sood","doi":"10.1049/esi2.12081","DOIUrl":"10.1049/esi2.12081","url":null,"abstract":"<p>Electrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro-mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest data-analytic technologies.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"5 1","pages":"1-14"},"PeriodicalIF":2.4,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49243447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to meet the two global challenges of energy shortage and environmental pollution, various countries have begun to advocate the application of new energy equipment such as electric vehicles. This has also promoted the development of energy storage equipment and energy storage systems. With their high performance, lithium-ion batteries are used in a wide range of electrical equipment. But the safety of lithium-ion batteries depends on effective behaviour diagnosis. In order to better realise behaviour diagnosis, this paper combined the long and short-term memory network (LSTM) with the temporal convolution network (TCN) for the first time and established a synthetic thermal convolutional-memory network (STCMN) for lithium-ion battery behaviour diagnosis against noise interruptions. In addition, a TCN-LSTM alliance network structure is designed. The TCN-LSTM alliance network is an effective architecture applied not only to the temperature prediction of Li-ion batteries but also to the thermal diagnosis part. And these two parts finally constitute the thermal convolutional-memory network. The experimental results show the network designed in this paper was able to improve Li-ion battery behaviour detection.
{"title":"Synthetic thermal convolutional-memory network for the lithium-ion battery behaviour diagnosis against noise interruptions","authors":"Marui Li, Chaoyu Dong, Rui Wang, Xiaodan Yu, Qian Xiao, Hongjie Jia","doi":"10.1049/esi2.12080","DOIUrl":"10.1049/esi2.12080","url":null,"abstract":"<p>In order to meet the two global challenges of energy shortage and environmental pollution, various countries have begun to advocate the application of new energy equipment such as electric vehicles. This has also promoted the development of energy storage equipment and energy storage systems. With their high performance, lithium-ion batteries are used in a wide range of electrical equipment. But the safety of lithium-ion batteries depends on effective behaviour diagnosis. In order to better realise behaviour diagnosis, this paper combined the long and short-term memory network (LSTM) with the temporal convolution network (TCN) for the first time and established a synthetic thermal convolutional-memory network (STCMN) for lithium-ion battery behaviour diagnosis against noise interruptions. In addition, a TCN-LSTM alliance network structure is designed. The TCN-LSTM alliance network is an effective architecture applied not only to the temperature prediction of Li-ion batteries but also to the thermal diagnosis part. And these two parts finally constitute the thermal convolutional-memory network. The experimental results show the network designed in this paper was able to improve Li-ion battery behaviour detection.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"5 1","pages":"29-39"},"PeriodicalIF":2.4,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42238025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emerging innovation in smart charging for plug-in electric vehicles (EVs) has the potential to achieve significant economic benefits. In several works, smart charging encourages the use of EVs as a flexible resource by modifying their power consumption through a demand response (DR) program. However, it is promptly assumed that EVs are always responsive and accept the smart charging signals with no fault. In practice, due to uncertainties such as random EV mobility, volatile battery charging characteristics or charging component failures, some EVs would be unable to accept the assigned charging signals dispatched from a central server. Therefore, this article proposes a feedback loop to predict EV charging behaviours and thereby adaptively tune the time-based control signals dispatched to individual EVs. Moreover, a parallel-operating distributed DR algorithm is proposed which aims optimal EV scheduling under charging uncertainties while reducing the need of private information sharing. The proposed distributed algorithm allows increased EV user privacy, fast convergence properties and optimal operation under communication disruptions and delays. The effectiveness of the proposed methods are also numerically exhibited for varying penetration of EVs within a low-voltage (LV) distribution test network.
{"title":"A feedback-integrated framework for resilient and distributed scheduling of electric vehicles under uncertain charging characteristics","authors":"Bakul Kandpal, Ashu Verma","doi":"10.1049/esi2.12079","DOIUrl":"10.1049/esi2.12079","url":null,"abstract":"<p>Emerging innovation in smart charging for plug-in electric vehicles (EVs) has the potential to achieve significant economic benefits. In several works, smart charging encourages the use of EVs as a flexible resource by modifying their power consumption through a demand response (DR) program. However, it is promptly assumed that EVs are always responsive and accept the smart charging signals with no fault. In practice, due to uncertainties such as random EV mobility, volatile battery charging characteristics or charging component failures, some EVs would be unable to accept the assigned charging signals dispatched from a central server. Therefore, this article proposes a feedback loop to predict EV charging behaviours and thereby adaptively tune the time-based control signals dispatched to individual EVs. Moreover, a parallel-operating distributed DR algorithm is proposed which aims optimal EV scheduling under charging uncertainties while reducing the need of private information sharing. The proposed distributed algorithm allows increased EV user privacy, fast convergence properties and optimal operation under communication disruptions and delays. The effectiveness of the proposed methods are also numerically exhibited for varying penetration of EVs within a low-voltage (LV) distribution test network.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"4 4","pages":"532-545"},"PeriodicalIF":2.4,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12079","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47777574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article presents a generalised integrator with a band-pass filter frequency locked loop (GI-BPF-FLL) control algorithm for the solar photovoltaic (SPV)-integrated unified power quality conditioner (SPVUPQC) system. This control algorithm extracts fundamental components (FC) of the distorted and deformed input signals, and it has the competence of eliminating DC-offset. The key objective is to decrease the number of sensors used in the control algorithm of the SPVUPQC system while enabling the power quality enhancement features in the distribution grid. The effectiveness of the presented GI-BPF-FLL control algorithm and its performance comparison with the conventional control algorithm are discussed in both the time domain as well as frequency domain analysis. The SPVUPQC system consisting of a distribution static compensator (DSTATCOM) and a dynamic voltage restorer (DVR), to compensate simultaneously both the voltage distortions, sag/swell etc. as well as current harmonics, reactive power and load currents unbalances etc. The model of the SPVUPQC system is developed in the MATLAB/Simulink environment, and its results are presented to demonstrate its capabilities. The system's validation is also done on the hardware prototype, and it performs effectively for the voltage and current power quality enhancement simultaneously. The load side voltages magnitudes, grid side voltages and the grid currents total harmonic distortions are found within the boundaries specified in the IEEE standard 1159 and the IEEE standard 519.
{"title":"Multi-functional control strategy for power quality improvement of three-phase grid using solar PV fed unified power quality conditioner","authors":"Chandrakala Devi Sanjenbam, Priyank Shah, Bhim Singh","doi":"10.1049/esi2.12077","DOIUrl":"10.1049/esi2.12077","url":null,"abstract":"<p>This article presents a generalised integrator with a band-pass filter frequency locked loop (GI-BPF-FLL) control algorithm for the solar photovoltaic (SPV)-integrated unified power quality conditioner (SPVUPQC) system. This control algorithm extracts fundamental components (FC) of the distorted and deformed input signals, and it has the competence of eliminating DC-offset. The key objective is to decrease the number of sensors used in the control algorithm of the SPVUPQC system while enabling the power quality enhancement features in the distribution grid. The effectiveness of the presented GI-BPF-FLL control algorithm and its performance comparison with the conventional control algorithm are discussed in both the time domain as well as frequency domain analysis. The SPVUPQC system consisting of a distribution static compensator (DSTATCOM) and a dynamic voltage restorer (DVR), to compensate simultaneously both the voltage distortions, sag/swell etc. as well as current harmonics, reactive power and load currents unbalances etc. The model of the SPVUPQC system is developed in the MATLAB/Simulink environment, and its results are presented to demonstrate its capabilities. The system's validation is also done on the hardware prototype, and it performs effectively for the voltage and current power quality enhancement simultaneously. The load side voltages magnitudes, grid side voltages and the grid currents total harmonic distortions are found within the boundaries specified in the IEEE standard 1159 and the IEEE standard 519.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"4 4","pages":"518-531"},"PeriodicalIF":2.4,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57947755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jorge Zuluaga, Carlos E. Murillo-Sanchez, Ricardo Moreno-Chuquen, Harold R. Chamorro, Vijay K. Sood
The variability and uncertainty of renewable resources impose new challenges in the operational planning related to the unit commitment of generation units. The development of day-ahead multi-period optimal power flow, under integration of wind power, requires modelling of multiple scenarios in order to ensure an optimal power flow minimising the generation cost. A progressive hedging approach has been proposed and developed to solve efficiently the unit commitment problem as a two-stage stochastic programming problem to update each stage in parallel. The performance of progressive hedging is compared with a standard mixed-integer linear programming problem. The results indicate that the computation time is 50 times faster than standard mixed-integer linear programming. The test case system is based on a reduced version of the interconnected Colombian system. The comparative results indicate an important reduction in computational time.
{"title":"Day-ahead unit commitment for hydro-thermal coordination with high participation of wind power","authors":"Jorge Zuluaga, Carlos E. Murillo-Sanchez, Ricardo Moreno-Chuquen, Harold R. Chamorro, Vijay K. Sood","doi":"10.1049/esi2.12078","DOIUrl":"10.1049/esi2.12078","url":null,"abstract":"<p>The variability and uncertainty of renewable resources impose new challenges in the operational planning related to the unit commitment of generation units. The development of day-ahead multi-period optimal power flow, under integration of wind power, requires modelling of multiple scenarios in order to ensure an optimal power flow minimising the generation cost. A progressive hedging approach has been proposed and developed to solve efficiently the unit commitment problem as a two-stage stochastic programming problem to update each stage in parallel. The performance of progressive hedging is compared with a standard mixed-integer linear programming problem. The results indicate that the computation time is 50 times faster than standard mixed-integer linear programming. The test case system is based on a reduced version of the interconnected Colombian system. The comparative results indicate an important reduction in computational time.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"5 2","pages":"119-127"},"PeriodicalIF":2.4,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43613931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Moushumi Patowary, Hassan Haes Alhelou, Gayadhar Panda
A relative assessment on conventional and adaptive current controllers used in reduced sensor-maximum power point tracking (MPPT) based photovoltaic (PV)-grid tied inverter systems for the improvement of system power quality is suggested. The steady-state and transients errors produced in the conventional PI and proportional resonant controllers, which are used to generate the references, can be fixed by using an intelligent ADALINE-LMS adaptive controller; moreover, it helps in reducing the %THD (total harmonic distortion) level measured at different power zones. Also, to track the maximum PV power, which is further integrated to DC-bus, a reduced sensor-based technology is added into the circuit that sidesteps the problem of tracking local MPP instead of global MPP and the drawbacks of using current sensors. The use of a reduced sensor-based MPPT controller confirms extraction of maximum PV power and it guarantees a constant DC-link voltage under all the possible test conditions. The overall control architectures and system performances, which are tested under different system dynamics, are validated through MATLAB/Simulink as well as experimental findings obtained using the dSPACE RTI 1202 interfacing kit. These experimental results confirm that the adaptive control technique used in reduced sensor-MPPT based PV-grid tied inverter systems performs unbeatably with balanced load and grid voltages, less harmonics, quick response time etc. under the operation of linear, non-linear and transient loads, whereas, conventional controllers are best only for the linear loads.
{"title":"Performance assessment and validation of inverter control current controllers in reduced sensor maximum power point tracking based photovoltaic-grid tied system","authors":"Moushumi Patowary, Hassan Haes Alhelou, Gayadhar Panda","doi":"10.1049/esi2.12076","DOIUrl":"10.1049/esi2.12076","url":null,"abstract":"<p>A relative assessment on conventional and adaptive current controllers used in reduced sensor-maximum power point tracking (MPPT) based photovoltaic (PV)-grid tied inverter systems for the improvement of system power quality is suggested. The steady-state and transients errors produced in the conventional PI and proportional resonant controllers, which are used to generate the references, can be fixed by using an intelligent ADALINE-LMS adaptive controller; moreover, it helps in reducing the %THD (total harmonic distortion) level measured at different power zones. Also, to track the maximum PV power, which is further integrated to DC-bus, a reduced sensor-based technology is added into the circuit that sidesteps the problem of tracking local MPP instead of global MPP and the drawbacks of using current sensors. The use of a reduced sensor-based MPPT controller confirms extraction of maximum PV power and it guarantees a constant DC-link voltage under all the possible test conditions. The overall control architectures and system performances, which are tested under different system dynamics, are validated through MATLAB/Simulink as well as experimental findings obtained using the dSPACE RTI 1202 interfacing kit. These experimental results confirm that the adaptive control technique used in reduced sensor-MPPT based PV-grid tied inverter systems performs unbeatably with balanced load and grid voltages, less harmonics, quick response time etc. under the operation of linear, non-linear and transient loads, whereas, conventional controllers are best only for the linear loads.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"4 4","pages":"505-517"},"PeriodicalIF":2.4,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45693515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The distributed integrated multi-energy system (DIMS) has many advantages in terms of the utilisation of renewable energy sources and clean energy. Operation strategies for the DIMS based on a real-time profile have been extensively studied. In a DIMS online optimisation problem, besides fluctuations in the renewable energy output and load, inconsistent time scales of the transport dynamics of different energy flows and non-ideal communication (involving communication uncertainty and latency) result in suboptimal operation in dispatch scheduling. An online multi-time-scale optimal operation strategy is proposed for the DIMS to respond to the above challenges, using a hybrid algorithm comprising a model predictive control method and distributed collaborative consensus algorithm (CCA). The approach is based on a hierarchy, comprising rolling optimisation and adjustment. A rolling optimisation is established to schedule operations according to the latest forecast and status information. The rolling dispatch is then adjusted according to the ultrashort-term adjustment using the CCA. Meanwhile, the effect of the information transmission environment on real-time scheduling is considered, and the robust CCA is improved for the implementation of strategies under non-ideal communication conditions. Case studies and results are presented and discussed to show the effectiveness of the proposed approach with the better matching between demand and supply.
{"title":"An online dispatch approach for distributed integrated multi-energy system considering non-ideal communication conditions","authors":"Jiaqi Ju, Qi Wang, Ming Ni, Yunlong Hu, Xiao Li","doi":"10.1049/esi2.12075","DOIUrl":"10.1049/esi2.12075","url":null,"abstract":"<p>The distributed integrated multi-energy system (DIMS) has many advantages in terms of the utilisation of renewable energy sources and clean energy. Operation strategies for the DIMS based on a real-time profile have been extensively studied. In a DIMS online optimisation problem, besides fluctuations in the renewable energy output and load, inconsistent time scales of the transport dynamics of different energy flows and non-ideal communication (involving communication uncertainty and latency) result in suboptimal operation in dispatch scheduling. An online multi-time-scale optimal operation strategy is proposed for the DIMS to respond to the above challenges, using a hybrid algorithm comprising a model predictive control method and distributed collaborative consensus algorithm (CCA). The approach is based on a hierarchy, comprising rolling optimisation and adjustment. A rolling optimisation is established to schedule operations according to the latest forecast and status information. The rolling dispatch is then adjusted according to the ultrashort-term adjustment using the CCA. Meanwhile, the effect of the information transmission environment on real-time scheduling is considered, and the robust CCA is improved for the implementation of strategies under non-ideal communication conditions. Case studies and results are presented and discussed to show the effectiveness of the proposed approach with the better matching between demand and supply.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"4 4","pages":"488-504"},"PeriodicalIF":2.4,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47057859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Security and resilience of energy systems have become major concerns in energy engineering. Several recent power grid attacks, including the first known devastating cyber-attack in 2015 and the first US ‘denial of service’ attack to the western power grid in March 2019, remind us of the global challenge represented by energy system attacks launched through the cyber-communication network. Meanwhile, attacks on energy systems are growing in number, causing severe impacts on public health and national security.</p><p>Resilience is playing an essential role in operating a dynamic cyber-physical energy system, such as microgirid. Thus, it is necessary to systematically understand the operation mechanism of a dynamic energy system, to implement proper strategies to improve its resilience subject to disturbances or attacks. To advance those fields, scientific research is needed to study and develop novel technologies, including but not limited to resilience study, resilient control, attack detection, defense strategies, machine learning, and data analytics.</p><p>This Special Issue of IET Energy Systems Integration focuses on Secure and Resilient Operations of Cyber-Physical Urban Energy Systems. Brief descriptions of each of the three papers in the Special Issue are provided below. We encourage the readers to refer to the papers for more details.</p><p>In “Resilience Assessment Methodologies and Enhancement Strategies of Multi-Energy Cyber Physical Systems of the Distribution Network”, Yang et al. introduced an extensive review on the state-of-the-art-research of power systems resilience. They give a definition of the Multi-Energy Cyber Physical Systems resilience and summarise its related characteristics, and the models of extreme disasters and equipment vulnerability are analysed. The qualitative resilience assessment curve, indexes and process of the Multi-Energy Cyber Physical Systems are developed. They present the key improvement measures for the planning and operation of MECPSs resilience and the focus of future research.</p><p>In “Attack and Defence methods in cyber-physical power system (CPPS)”, Yang and Liu focus on dealing with the attacks against complex CPPS, by profiling the structure of CPPS and the potential threats, conducting an in-depth analysis of CPPS attack modes from the cyber and physical subsystems, and summarising the three-level security defense methods for CPPS in detail. The future technological development prospects of CPPS security research are explicitly addressed, which will provide technical support for building reliable, safe, and robust energy systems. Overall, this paper analyses and summarises the typical attack patterns and multi-dimensional defense methods of CPPS and presents four problems that need to be deeply studied and solved in CPPs defense, so as to provide a reference for the subsequent technical development. First, the existing research studies on CPPS security are based on the attacks that have bee
{"title":"Guest editorial: Secure and resilient operations of cyber-physical urban energy systems","authors":"Yan Li","doi":"10.1049/esi2.12074","DOIUrl":"10.1049/esi2.12074","url":null,"abstract":"<p>Security and resilience of energy systems have become major concerns in energy engineering. Several recent power grid attacks, including the first known devastating cyber-attack in 2015 and the first US ‘denial of service’ attack to the western power grid in March 2019, remind us of the global challenge represented by energy system attacks launched through the cyber-communication network. Meanwhile, attacks on energy systems are growing in number, causing severe impacts on public health and national security.</p><p>Resilience is playing an essential role in operating a dynamic cyber-physical energy system, such as microgirid. Thus, it is necessary to systematically understand the operation mechanism of a dynamic energy system, to implement proper strategies to improve its resilience subject to disturbances or attacks. To advance those fields, scientific research is needed to study and develop novel technologies, including but not limited to resilience study, resilient control, attack detection, defense strategies, machine learning, and data analytics.</p><p>This Special Issue of IET Energy Systems Integration focuses on Secure and Resilient Operations of Cyber-Physical Urban Energy Systems. Brief descriptions of each of the three papers in the Special Issue are provided below. We encourage the readers to refer to the papers for more details.</p><p>In “Resilience Assessment Methodologies and Enhancement Strategies of Multi-Energy Cyber Physical Systems of the Distribution Network”, Yang et al. introduced an extensive review on the state-of-the-art-research of power systems resilience. They give a definition of the Multi-Energy Cyber Physical Systems resilience and summarise its related characteristics, and the models of extreme disasters and equipment vulnerability are analysed. The qualitative resilience assessment curve, indexes and process of the Multi-Energy Cyber Physical Systems are developed. They present the key improvement measures for the planning and operation of MECPSs resilience and the focus of future research.</p><p>In “Attack and Defence methods in cyber-physical power system (CPPS)”, Yang and Liu focus on dealing with the attacks against complex CPPS, by profiling the structure of CPPS and the potential threats, conducting an in-depth analysis of CPPS attack modes from the cyber and physical subsystems, and summarising the three-level security defense methods for CPPS in detail. The future technological development prospects of CPPS security research are explicitly addressed, which will provide technical support for building reliable, safe, and robust energy systems. Overall, this paper analyses and summarises the typical attack patterns and multi-dimensional defense methods of CPPS and presents four problems that need to be deeply studied and solved in CPPs defense, so as to provide a reference for the subsequent technical development. First, the existing research studies on CPPS security are based on the attacks that have bee","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"4 2","pages":"157-158"},"PeriodicalIF":2.4,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43707861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In modern society, system integration that enables multiple subsystems to function as one is emerging in various fields like industry, commerce, and infrastructure. Although it has been proved that integration value could be tapped to the maximum with controllable cost by optimising the integration schemes in certain fields, there is still a lack of a general method for modelling and analysing the process of system integration. To address this need, this paper proposes an analysis framework of system integration. The concepts of integration object, integration strategy, integration time, integration cost and integration value are introduced to describe the integration process. Further, three optimisation models of the local optimisation (OPT1), phase optimisation (OPT2) and integration optimisation (OPT3) are constructed. The proposed framework can also supervise and compare the performance of intermediate processes of different integration schemes. Two case studies in the commerce and energy fields are analysed to illustrate the function of the proposed framework.
{"title":"A framework of system integration and integration value analysis: Concept and case studies","authors":"Hongjie Jia, Huiyuan Wang, Yan Cao, Yunfei Mu, Xiandong Xu, Xiaodan Yu","doi":"10.1049/esi2.12071","DOIUrl":"10.1049/esi2.12071","url":null,"abstract":"<p>In modern society, system integration that enables multiple subsystems to function as one is emerging in various fields like industry, commerce, and infrastructure. Although it has been proved that integration value could be tapped to the maximum with controllable cost by optimising the integration schemes in certain fields, there is still a lack of a general method for modelling and analysing the process of system integration. To address this need, this paper proposes an analysis framework of system integration. The concepts of integration object, integration strategy, integration time, integration cost and integration value are introduced to describe the integration process. Further, three optimisation models of the local optimisation (OPT1), phase optimisation (OPT2) and integration optimisation (OPT3) are constructed. The proposed framework can also supervise and compare the performance of intermediate processes of different integration schemes. Two case studies in the commerce and energy fields are analysed to illustrate the function of the proposed framework.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"4 3","pages":"297-316"},"PeriodicalIF":2.4,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41869014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}