Junjie Hu

Coordination strategies for distribution grid congestion management in a multi-actor, multi-objective setting

It is well understood that the electric vehicle as a distributed energy resource can provide valuable services to the power system. Such services, however, would have to co-exist with hard constraints imposed by EV user demands and distribution grid operation constraints. This paper aims to address the interactions between the stakeholders involved, mainly considering the distribution grid congestion problem, and conceptualize several approaches by which their diverse, potentially conflicting, objectives can be coordinated. A key aspect to be considered is the relationship between the operational planning and the handling of real-time events for reliable grid operation. This paper presents an analysis of key stakeholders in terms of their objectives and key operations. Three potential strategies for congestion management are presented and evaluated based on their complexity of implementation, the value and benefits they can offer as well as possible drawbacks and risks.

A multi-agent system for distribution grid congestion management with electric vehicles

Abstract Electric vehicles (EVs) are widely regarded as valuable assets in the smart grid as distributed energy resources in addition to their primary transportation function. However, connecting EVs to the distribution network and recharging the EV batteries without any control may overload the transformers and cables during peak hours when the penetration of EVs is relatively high. In this study, a two level hierarchical control method for integrating EVs into the distribution network is proposed to coordinate the self-interests and operational constraints of two actors, the EV owner and Distribution system operator (DSO), facilitated by the introduction of the fleet operator (FO) and the grid capacity market operator (CMO). Unlike the typical hierarchical control system where the upper level controller commands the low level unit to execute the actions, in this study, market based control are applied both in the upper and low level of the hierarchical system. Specifically, in the upper level of the hierarchy, distribution system operator uses market based control to coordinate the fleet operator׳s power schedule. In the low level of the hierarchy, the fleet operator use market based control to allocate the charging power to the individual EVs, by using market based control, the proposed method considers the flexibility of EVs through the presence of the response-weighting factor to the shadow price sent out by the FO. Furthermore, to fully demonstrate the coordination behavior of the proposed control strategy, we built a multi-agent system (MAS) that is based on the co-simulation environment of JACK, Matlab and Simulink. A use case of the MAS and the results of running the system are presented to intuitively illustrate the effectiveness of the proposed solutions.

Optimal control of an electric vehicle’s charging schedule under electricity markets

As increasing numbers of electric vehicles (EVs) enter into the society, the charging behavior of EVs has got lots of attention due to its economical difference within the electricity market. The charging cost for EVs generally differ from each other in choosing the charging time interval (hourly), since the hourly electricity prices are different in the market. In this paper, the problem is formulated into an optimal control one and solved by dynamic programming. Optimization aims to find the economically optimal charging solution for each vehicle. In this paper, a nonlinear battery model is characterized and presented, and a given future electricity prices is assumed and utilized. Simulation results indicate that daily charing cost is reduced by smart charing.

An overview of trends in distribution network planning: A movement towards smart planning

Distribution network planning, historically known as a ‘predict and provide’ process, seeks to determine a set of optimal network solutions for supplying electric demands spatially distributed over a geographic area. Today, the rapid development and deployment of distributed generation and smart grid products (e.g., control, communication, and new economic measures) call for urgent improvements in distribution network planning to allow the utilities to proactively modernize their existing distribution grids. This paper reviews the current practices in this area and the emerging trends towards smart planning. Some challenges with smart planning are identified and briefly discussed.

A clearinghouse concept for distribution-level flexibility services

Flexibility resources on the demand side are anticipated to become a valuable asset for balancing renewable energy fluctuation as well as for reducing investment needs in distribution grids. To harvest this flexibility for distribution grids, flexibility services need to be defined that can be integrated with distribution grid operation and that provide a benefit that can be traded off against other grid investments. Two key challenges are here that the identification of useful services is still ongoing and that the transaction cost for the individually small contributions from the demand side could be prohibitive. This paper introduces a flexibility clearinghouse (FLECH) concept and isolates FLECH key functionality: to facilitate flexibility services in distribution grids by streamlining the relevant business interactions while keeping technical specifications open.

Application of Network-Constrained Transactive Control to Electric Vehicle Charging for Secure Grid Operation

This paper develops a network-constrained transactive control method to integrate distributed energy resources (DERs) into a power distribution system with the purpose of optimizing the operational cost of DERs and power losses of the distribution network, as well as preventing grid problems including power transformer congestion and voltage violations. In this method, a price coordinator is introduced to facilitate the interaction between the distribution system operator and the aggregators in the smart grid. Electric vehicles are used to illustrate the proposed network-constrained transactive control method. Mathematical models are presented to describe the operation of the control method. Finally, simulations are presented to show the effectiveness of the proposed method. To guarantee its optimality, we also checked the numerical results obtained with the network-constrained transactive control method and compared them with the one solved by centralized control, and found a good performance of the proposed control method.

Network constrained transactive control for electric vehicles integration

Electric vehicles (EVs) are commonly recognized as smart grid assets in addition to their environmental benefits. However, uncoordinated charging or sole cost minimization based charging of electric vehicles may bring undesirable peak demands and voltage violations in the distribution system. This paper applies the transactive control concept to integrate electric vehicles into the power distribution system with the purpose of minimizing the charging cost of electric vehicles as well as preventing grid congestions and voltage violations. A hierarchical EV management system is proposed where three actors are considered: distribution system operator (DSO), fleet operators and EV owners. In the lower level of the hierarchy, the fleet operator centrally manages the charging schedule of electric vehicles; in the upper level of the hierarchy, the DSO uses transactive control technique to coordinate the aggregated charging behavior of fleet operators. Detailed models are presented to illustrate the operation of the hierarchical EV management system. In the end, simulations are presented to show the effectiveness of the proposed solutions.

Identification of requirements for distribution management systems in the smart grid context

The integration of significant volumes of distributed and renewable energy resources directly connected to the distribution network raises new requirement to maintain and operate the power system in secure state. Thus the Distribution Management System (DMS) needs to be updated and integrated with new functionality to provide effective support for the operators. The DMS is a control center solution that provides the needed functionality for the management of medium and low voltage distribution networks. This paper aims to provide an overview of the main functions present in todays DMS platforms and to identify the new requirements to better serve in a smart grid context.

Voltage control for unbalanced low voltage grids using a decoupled-phase on-load tap-changer transformer and photovoltaic inverters

This paper presents modeling and analysis of the potential benefits of joint actions of a MV/LV three-phase power distribution transformer with independent on-load tap-changer control on each phase and photovoltaic inverters provided with reactive power control capability, in terms of accommodating more renewable generations in the LV grid. The potential benefits are investigated in terms of voltage unbalance reduction and local voltage regulation. 24-hours root-mean-square dynamics simulation studies have been carried out with time-step of 1 second using 10-mins resolution consumption and production profiles. A totally passive real Danish low voltage distribution network is used for the grid topology as well as for the characterization of loads profiles, while the production ones are empirically defined under assumptions in scenarios with different level of photovoltaic penetration and grade of unbalance.

Novel migration operators of biogeography-based optimization and Markov analysis

Biogeography-based optimization (BBO) is a nature-inspired optimization algorithm and has been developed in both theory and practice. In canonical BBO, migration operator is crucial to affect algorithm’s performance. In migration operator, a good solution has a large probability to be selected as an immigrant, while a poor solution has a large probability to be selected as an emigrant. The features in an emigrant will be completely replaced by the features in the corresponding immigrant. Hence, the migration operator in canonical BBO causes a significant deterioration of population diversity, and therefore, the algorithm’s performance worsens. In this paper, we propose three novel migration operators to enhance the exploration ability of BBO. To present a mathematical proof, Markov analysis is conducted to confirm the advantages of the proposed migration operators over existing ones. In addition, a number of benchmark tests are carried out to empirically assess the performance of the proposed migration operators, on both low-dimensional and high-dimensional numerical optimization problems. The comparison results demonstrate that the proposed migration operators are feasible and effective to enhance BBO’s performance.