Active network management(ANM)of electricity distribution networks include many complex stochastic sequential optimization problems.These problems need to be solved for integrating renewable energies and distributed s...Active network management(ANM)of electricity distribution networks include many complex stochastic sequential optimization problems.These problems need to be solved for integrating renewable energies and distributed storage into future electrical grids.In this work,we introduce Gym-ANM,a framework for designing reinforcement learning(RL)environments that model ANM tasks in electricity distribution networks.These environments provide new playgrounds for RL research in the management of electricity networks that do not require an extensive knowledge of the underlying dynamics of such systems.Along with this work,we are releasing an implementation of an introductory toy-environment,ANM6-Easy,designed to emphasize common challenges in ANM.We also show that state-of-the-art RL algorithms can already achieve good performance on ANM6-Easy when compared against a model predictive control(MPC)approach.Finally,we provide guidelines to create new Gym-ANM environments differing in terms of(a)the distribution network topology and param-eters,(b)the observation space,(c)the modeling of the stochastic processes present in the system,and(d)a set of hyperparameters influencing the reward signal.Gym-ANM can be downloaded at https://github.com/robinhenr y/gym-anm.展开更多
The approach to planning,design and operation of distribution networks have significantly changed due to the proliferation of distributed energy resources(DERs)together with load growth,energy storage technology advan...The approach to planning,design and operation of distribution networks have significantly changed due to the proliferation of distributed energy resources(DERs)together with load growth,energy storage technology advancements and increased consumer expectations.Planning of active distribution systems(ADS)has been a very hot topic in the 21st Century.A large number of studies have been done on ADS planning.This paper reviews the state of the art of current ADS planning.Firstly,the influences of DERs on the ADS planning are addressed.Secondly,the characteristics and objectives of ADS planning are summarized.Then,up to date planning model and some related research are highlighted in different areas such as forecasting load and distributed generation,mathematical model of ADS planning and solution algorithms.Finally,the paper explores some directions of future research on ADS planning including planning collaboratively with all elements combined in ADS,taking into account of joint planning in secondary system,coordinating goals among different layers,integrating detailed operation simulations and regular performance based reviews into planning,and developing advanced planning tools.展开更多
文摘Active network management(ANM)of electricity distribution networks include many complex stochastic sequential optimization problems.These problems need to be solved for integrating renewable energies and distributed storage into future electrical grids.In this work,we introduce Gym-ANM,a framework for designing reinforcement learning(RL)environments that model ANM tasks in electricity distribution networks.These environments provide new playgrounds for RL research in the management of electricity networks that do not require an extensive knowledge of the underlying dynamics of such systems.Along with this work,we are releasing an implementation of an introductory toy-environment,ANM6-Easy,designed to emphasize common challenges in ANM.We also show that state-of-the-art RL algorithms can already achieve good performance on ANM6-Easy when compared against a model predictive control(MPC)approach.Finally,we provide guidelines to create new Gym-ANM environments differing in terms of(a)the distribution network topology and param-eters,(b)the observation space,(c)the modeling of the stochastic processes present in the system,and(d)a set of hyperparameters influencing the reward signal.Gym-ANM can be downloaded at https://github.com/robinhenr y/gym-anm.
基金This work was supported by National High Technology Research and Development Program of China under Grant 2014AA051901(Key Technology Research and Demonstration for Active Distribution Grid).
文摘The approach to planning,design and operation of distribution networks have significantly changed due to the proliferation of distributed energy resources(DERs)together with load growth,energy storage technology advancements and increased consumer expectations.Planning of active distribution systems(ADS)has been a very hot topic in the 21st Century.A large number of studies have been done on ADS planning.This paper reviews the state of the art of current ADS planning.Firstly,the influences of DERs on the ADS planning are addressed.Secondly,the characteristics and objectives of ADS planning are summarized.Then,up to date planning model and some related research are highlighted in different areas such as forecasting load and distributed generation,mathematical model of ADS planning and solution algorithms.Finally,the paper explores some directions of future research on ADS planning including planning collaboratively with all elements combined in ADS,taking into account of joint planning in secondary system,coordinating goals among different layers,integrating detailed operation simulations and regular performance based reviews into planning,and developing advanced planning tools.
