CN115001972B - Distributed energy management method, device, computer equipment and storage medium - Google Patents
Distributed energy management method, device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention relates to a distributed energy management method, a distributed energy management device, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring the current running state of a virtual power plant communication system and the total energy consumption of the current system corresponding to the current running state; determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum; adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state; the obtained distributed energy is managed based on the total energy consumption of the target system, the energy is managed on the basis of guaranteeing the energy efficiency maximization of the virtual power plant communication system, the hybrid energy supply of the virtual power plant communication system is realized, and the energy utilization rate is improved.
Description
Technical Field
The embodiment of the invention relates to the field of distributed energy, in particular to a distributed energy management method, a distributed energy management device, computer equipment and a storage medium.
Background
In recent years, the power generation rate of clean energy in China is continuously increased, and the development and utilization scale of renewable resources is in the forefront of the world. The renewable energy source mainly comprises wind power generation, photovoltaic power generation, biomass power generation and the like, and the renewable energy source has dispersibility in geographical distribution, and the power generation output has the characteristics of randomness, volatility, intermittence and the like, so that how to access and manage the distributed renewable energy source is a problem which needs to be solved currently.
At present, the distributed energy is mainly accessed and managed in several modes, namely an active power distribution system, a micro-grid, a dynamic electricity price, a virtual power plant and the like. Because distributed energy sources in virtual power plants often have a large number, distributed geographical locations, and heterogeneous networks, establishing communication connections for these distributed energy sources would be a primary task of the virtual power plant communication system. On this basis, in order to better support efficient operation of the virtual power plant, the virtual power plant needs to apply a coordinated control technology and an intelligent metering technology, and this results in that there are a plurality of different types of services in the virtual power plant, which are all transmitted through the information communication system, and different services have different requirements on the communication system, which further puts higher requirements on the information communication technology in the virtual power plant.
At present, for the communication access of large-scale distributed energy sources, an optical fiber connection mode is often adopted to ensure low time delay and high reliability, and for the communication access of a large number of small-scale and scattered distributed energy sources, a wireless connection mode is often only adopted, and the commonly adopted wireless connection mode has 2G, 3G, wi-Fi, bluetooth, zigBee and other technologies.
Firstly, establishing a mixed energy supply C-RAN mathematical model combining energy cooperation; establishing an objective function and constraint conditions of a long-term energy efficiency optimization problem; based on the ideas of Lyapunov equation and penalty function, the system long-term energy efficiency optimization problem is converted into a single-time slot optimization problem; the method solves the single time slot optimization problem after conversion by adopting a joint resource allocation optimization algorithm, but does not provide a mechanism for optimizing and scheduling communication resources of the 5G base station so as to achieve the purposes of reducing the high-efficiency allocation of the energy consumption of the 5G base station to the baseband processing resources and reducing the idle waste of the communication resources.
The existing access and management method of the distributed energy sources comprises the following steps: the system comprises a communication module, a situation awareness module, an edge calculation module, a next-stage resource regulation and control command generation module and an execution result summarization module, and can realize efficient supervision of resources and safety protection of data, so that the virtual power plant system has the characteristics of high efficiency, prejudgment, safety, reality, controllability and the like. However, in order to better support the efficient operation of the virtual power plant on the basis, the virtual power plant also needs to apply a coordinated control technology and an intelligent metering technology, and further, higher requirements are put on the information communication technology in the virtual power plant.
Disclosure of Invention
In view of the above, in order to solve the above technical problems or some of the technical problems, embodiments of the present invention provide a distributed energy management method, apparatus, computer device, and storage medium.
In a first aspect, an embodiment of the present invention provides a distributed energy management method, including:
acquiring the current running state of a virtual power plant communication system and the total energy consumption of the current system corresponding to the current running state;
determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum;
Adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state;
and managing the acquired distributed energy based on the total energy consumption of the target system.
In one possible embodiment, the method further comprises:
determining a reward expected value corresponding to other running states based on the current running state and the total energy consumption of the current system;
and taking the running state with the maximum rewarding expected value as the target running state of the virtual power plant communication system.
In one possible embodiment, the method further comprises:
acquiring the first total energy consumption of a baseband processing unit pool of the virtual power plant communication system and the second total energy consumption of all radio frequency equipment in the target running state in unit time;
a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
In one possible embodiment, the method further comprises:
acquiring the data throughput of a baseband processing unit pool of the virtual power plant communication system in the target running state in unit time;
The first total energy consumption is determined based on the data throughput.
In one possible embodiment, the method further comprises:
acquiring signal transmitting power provided by all radio frequency equipment for a corresponding received signal strength indicator in unit time;
the second total energy consumption is determined based on the signal transmit power.
In one possible embodiment, the method further comprises:
acquiring the collection quantity of distributed energy sources of the virtual power plant communication system and the current energy reserve quantity of all radio frequency equipment;
and managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
In one possible embodiment, the method further comprises:
if the sum of the current energy reserve and the collection amount of the distributed energy is smaller than the total energy consumption of the target system, acquiring a target number of energy sources from a preset energy storage device for the normal operation of the virtual power plant communication system;
and if the sum of the current energy reserve and the collection amount of the distributed energy sources is greater than the total energy consumption of the target system, storing surplus energy sources in an energy storage device.
In a second aspect, an embodiment of the present invention provides a distributed energy management apparatus, including:
The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the current running state of a virtual power plant communication system and the current system total energy consumption corresponding to the current running state;
a determining module, configured to determine a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, where the total system energy consumption of the virtual power plant communication system in the target operating state is minimal;
the adjusting module is used for adjusting the current running state of the virtual power plant communication system to the target running state and determining the total target system energy consumption of the virtual power plant communication system based on the target running state;
and the management module is used for managing the acquired distributed energy based on the total energy consumption of the target system.
In a possible implementation manner, the determining module is further configured to determine a desired value of rewards corresponding to other operation states based on the current operation state and the current total system energy consumption; and taking the running state with the maximum rewarding expected value as the target running state of the virtual power plant communication system.
In a possible implementation manner, the determining module is further configured to obtain a first total energy consumption of a baseband processing unit pool of the virtual power plant communication system in the target operating state in a unit time and a second total energy consumption of all radio frequency devices; a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
In a possible implementation manner, the determining module is further configured to obtain a data throughput of a baseband processing unit pool of the virtual power plant communication system in the target operating state in a unit time; the first total energy consumption is determined based on the data throughput.
In a possible implementation manner, the determining module is further configured to obtain signal transmission power provided by all radio frequency devices for the corresponding received signal strength indicator in a unit time; the second total energy consumption is determined based on the signal transmit power.
In a possible implementation manner, the management module is further configured to obtain a collection amount of distributed energy sources of the virtual power plant communication system and a current energy reserve amount of all radio frequency devices; and managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
In one possible implementation manner, the management module is further configured to obtain a target number of energy sources from a preset energy storage device for the virtual power plant communication system to operate normally if the sum of the current energy reserve amount and the collection amount of the distributed energy sources is less than the total energy consumption of the target system; and if the sum of the current energy reserve and the collection amount of the distributed energy sources is greater than the total energy consumption of the target system, storing surplus energy sources in an energy storage device.
In a third aspect, an embodiment of the present invention provides a computer apparatus, including: the distributed energy management system comprises a processor and a memory, wherein the processor is used for executing a distributed energy management program stored in the memory so as to realize the distributed energy management method in the first aspect.
In a fourth aspect, an embodiment of the present invention provides a storage medium, including: the storage medium stores one or more programs executable by one or more processors to implement the distributed energy management method described in the first aspect above.
According to the distributed energy management scheme provided by the embodiment of the invention, the current running state of the virtual power plant communication system and the current system total energy consumption corresponding to the current running state are obtained; determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum; adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state; based on the total energy consumption of the target system, the obtained distributed energy is managed, compared with the problem of idle energy waste caused by the access and management modes of the distributed energy in the prior art, the energy is managed on the basis of guaranteeing the energy efficiency maximization of the virtual power plant communication system, the hybrid energy supply of the virtual power plant communication system is realized, and the energy utilization rate is improved.
Drawings
Fig. 1 is a schematic diagram of a 5G hybrid power plant communication system configured for C-RAN networking according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a distributed energy management method according to an embodiment of the present invention;
FIG. 3 is a flow chart of another method for distributed energy management according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an A3C algorithm according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a distributed energy management device according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
For the purpose of facilitating an understanding of the embodiments of the present invention, reference will now be made to the following description of specific embodiments, taken in conjunction with the accompanying drawings, which are not intended to limit the embodiments of the invention.
The virtual power plant technology can integrate big data, cloud computing, blockchain, artificial intelligence and advanced information communication technology, aggregate, optimize and control distributed energy, energy storage devices, controllable loads and demand response resources, realize integrated regulation of source network and load storage, participate in peak regulation and frequency modulation of a power grid and electric power market transaction, and realize bilateral regulation of a power generation side and a power utilization side. Compared with other distributed energy management modes, the virtual power plant can overcome the constraint of the distributed energy in technical and commercial application, fully utilize the technical complementary advantages among various distributed energy sources and exert the scale benefit of the distributed energy. Virtual power plants allow for geographical dispersion of participants and heterogeneity of network structures, consistent with current state of development of distributed energy.
Fig. 1 is a schematic diagram of a 5G hybrid power plant communication system of a C-RAN network, where the virtual power plant communication system is a 5G communication system of the C-RAN network, as shown in fig. 1, and includes a plurality of radio frequency devices (RRHs), where the RRHs are as close to a distributed energy source as possible in a geographic location, so that not only can the communication access quality of the distributed energy source be improved, but also the energy consumption of the communication system can be reduced, and the communication cost is reduced; a plurality of received signal strength indicators (UEs), each RRH transmitting data by establishing a communication connection with the UE; a plurality of baseband processing units (BBUs) form a baseband processing unit Pool (BBU Pool), and the RRH and the BBU Pool are both provided with a renewable energy collection device and an energy storage device so as to realize hybrid energy supply to the communication nodes and reduce energy use of a power grid.
Fig. 2 is a schematic flow chart of a distributed energy management method according to an embodiment of the present invention, as shown in fig. 2, where the method specifically includes:
s21, acquiring the current running state of the virtual power plant communication system and the current system total energy consumption corresponding to the current running state.
In the embodiment of the invention, the current running state of the communication system of the virtual power plant at least comprises: the baseband resource allocation state, the communication connection and transmission power allocation state between all RRHs and the UE in the BBU Pool, and the SINR value of the received signal of the UE, wherein the larger the allocated transmission power is, the better the signal is, the higher the corresponding energy consumption is, and the SINR value represents the ratio of the intensity of the useful signal received by the UE to the intensity of the received interference signal and can be used as a reference index for measuring the communication quality.
And acquiring the running state of the virtual power plant communication system and the corresponding total energy consumption of the current system under the current running state.
S22, determining a target operation state of the virtual power plant communication system based on the current operation state and the current system total energy consumption, wherein the system total energy consumption of the virtual power plant communication system in the target operation state is minimum.
In order to ensure that the total energy consumption of the system in the current environment is minimum, an A3C algorithm can be adopted to optimize the allocation of baseband processing resources and radio frequency resources of RRH in BBU Pool, the A3C algorithm is an actor-critic algorithm in reinforcement learning, and the algorithm combines the advantages of value-based deep reinforcement learning and strategy-based deep reinforcement learning respectively and has better applicability to discrete or continuous problems.
Further, an ideal target operation state of the virtual power plant communication system in the current environment is calculated by adopting an A3C algorithm, and the total energy consumption of the virtual power plant communication system in the target operation state is minimum. The method for determining the target operating state is specifically described in the corresponding embodiment of fig. 3, and is not described in detail here.
S23, adjusting the current operation state of the virtual power plant communication system to be the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state.
After the target running state is determined, the current running state of the virtual power plant communication system is adjusted to be the target running state, and the total target system energy consumption of the virtual power plant communication system in the target running state is acquired again according to the adjusted target running state.
S24, managing the obtained distributed energy based on the total energy consumption of the target system.
And managing the distributed energy acquired by the virtual power plant communication system based on the acquired total energy consumption of the target system.
Specifically, whether surplus energy exists or not is determined according to the collection amount of the distributed energy sources and the total energy consumption of the target system, and management is conducted on the surplus energy sources. When no energy is surplus, energy is distributed according to actual conditions, and normal communication of each node in the communication system is ensured.
According to the distributed energy management method provided by the embodiment of the invention, the current running state of the virtual power plant communication system and the current system total energy consumption corresponding to the current running state are obtained; determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum; adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state; based on the total energy consumption of the target system, the obtained distributed energy is managed, compared with the problem of idle energy waste caused by the access and management modes of the distributed energy in the prior art, the energy is managed on the basis of guaranteeing the energy efficiency maximization of the virtual power plant communication system, the hybrid energy supply of the virtual power plant communication system is realized, and the energy utilization rate is improved.
Fig. 3 is a flow chart of another distributed energy management method according to an embodiment of the present invention, as shown in fig. 3, where the method specifically includes:
s31, determining the expected rewards value corresponding to other running states based on the current running state and the total energy consumption of the current system.
S32, taking the running state with the maximum expected value of the rewards as the target running state of the virtual power plant communication system.
In the embodiment of the present invention, it is assumed that in the communication system of the present virtual power plant, i= {1,2,... The energy consumption of the BBU mainly comprises two parts, namely static energy consumption and dynamic energy consumption. Static energy consumption is the basic energy consumption of the BBU when it is in an active state, which is typically fixed. The dynamic energy consumption is positively correlated with the baseband processing rate, i.e., the higher the communication load of the BBU, the higher the dynamic energy consumption of the BBU. The energy consumption of the ith BBU in the system at time slot t is P i BBU (t), static energy consumption may be expressed as P i S (t), dynamic energy consumption may be expressed as P i D (t)，P i D (t) data throughput r with the ith BBU in time slot t i (t) positive correlation, alpha i Is a coefficient. The energy consumption of the BBU can be expressed as formula (1), formula (2).
P i D (t)＝α i r i (t) (1)
P i BBU (t)＝P i D (t)+P i S (t) (2)
Assuming that in the network there are k= {1,2,.. jk (t)，s jk (t) =1 indicates that the jth RRH establishes a communication connection with the kth UE in the time slot t. Suppose that the jth RRH provides a signal transmit power P for the kth UE at time slot t jk (t), the energy consumption of the jth RRH in the time slot t can be expressed as formula (3).
The embodiment of the invention adopts the SINR value as a reference index for measuring the communication quality, wherein the SINR value represents the ratio of the intensity of the received useful signal to the intensity of the received interference signal. The SINR value at the kth UE can be expressed as equation (4), g jk For the channel attenuation between the jth RRH and kth UE, σ represents the white gaussian noise in the environment.
And summing the energy consumption of each time slot of the ith BBU to obtain the total energy consumption of the ith BBU. Similarly, the energy consumption of each time slot of the jth RRH is summed to obtain the total energy consumption of the jth RRH, which is shown in the formula (5) and the formula (6), respectively.
The total energy consumption of the communication system is shown in a formula (7), and the total energy consumption of the communication system can be obtained by summing the energy consumption of all BBUs and the energy consumption of all RRHs in the system.
The data throughput of the jth RRH is shown in equation (8),r k and (t) is the data throughput of the kth UE in the time slot t. The data throughput of the ith BBU is shown as formula (9), s ij (t) represents a connection relationship between the ith BBU and the jth RRH. The throughput of all BBUs in the system in each time slot is summed to obtain the communication data throughput of the system, as shown in formula (10).
Constraint (11) indicates that the signal reception strength at each UE satisfies a minimum threshold ω min . Constraint (12) indicates that the SINR value of each UE needs to meet a threshold to ensure communication quality. Constraint (13) and constraint (14) represent that the power requirements of the BBU and RRH meet the constraint of maximum power of the hardware device.
Equation (15) is an optimization objective for energy consumption of the communication system, i.e., maximization of energy efficiency.
γ jk (t)≥φ min (12)
Further, in order to ensure that the total energy consumption of the system in the current environment is minimum, an action prediction model can be trained in advance, the model mainly adopts an A3C algorithm to optimize the allocation of baseband processing resources and radio frequency resources of RRH in BBU Pool, the structure of the A3C algorithm is shown in fig. 4, the A3C algorithm contains n working threads in total, and each working thread has the same network structure. The working threads independently run and update the parameters of the neural network to the public neural network, and the working threads do not interfere with each other so as to realize interaction with the environment. The Actor-Critic algorithm combines a cost function-based method and a policy-based method, and a policy gradient method is used in the Actor network, while a cost function-based method is used in the Critic network. The cost function-based approach differs from the cost function-based approach in that it does not require calculation of the value of each action to get a policy, but rather a gradient ascent in the direction of expected revenue maximization to find the optimal solution. Thus, in the iterative process of the algorithm, the goal is to maximize the mathematical expectation of its individual actions, rather than for a particular action. In the embodiment of the invention, the action can represent the running state of the virtual power plant, and the mathematical expected expression of the action rewards is shown in a formula (16).
Wherein X is i Is all possible values of action X, P i Is each action X i The corresponding probability. The prize expectation can be considered as all X' s i And P i Is a weighted average of (c).
The state value function VF(s) may be defined iteratively by the formula (17), in particular, VF(s) defines the return expectations obtainable in the current state s, i.e., the sum of the rewards r obtained in the current state transition and the rewards value expectations obtainable in the next state s'. Eta(s) is the probability of selecting an arbitrary action a in the state s, gamma epsilon [0,1] is a discount factor, and the value is usually 0.99.
VF(s)＝E (η(s)) [r+γVF(s')] (17)
The state-action value function may be expressed as equation (18) referring to the sum of the subsequent cumulative rewards available for taking action a in the current state s, r being the current action's reward value, and VF (s') being the reward value expectations for all possible subsequent actions in the current state.
QF(s,a)＝r+γVF(s') (18)
The dominance function, which can evaluate the dominance of action a over the average in state s to increase the probability of that action occurring, is an important strategy in strategy-based deep reinforcement learning, can be expressed as equation (19).
AF(s,a)＝QF(s,a)-VF(s) (19)
And in each training period, acquiring a baseband resource allocation state in BBU Pool, a communication connection and transmission power allocation state between RRH and UE, an SINR value of a received signal of the UE and the total energy consumption of the communication system in the current state. The rewards are calculated from the actions and then action decisions are made based on the current state s. The state space, action space and rewards function of the A3C algorithm are defined as follows:
State space: the state space mainly comprises a baseband processing resource allocation state in the BBU Pool, a communication connection relation and transmission power allocation state between RRH and UE, an SINR value of a signal received at the UE and total energy consumption of the communication system in the current state, wherein the baseband processing resource allocation state can be the quantity of BBUs which are started, load data of the BBUs and the like.
Action space: the action space may schedule allocation of baseband processing resources in the BBU Pool and connection relationship between RRH and UE and size of transmission power. The minimum granularity of RRH transmit power adjustment may be set to 0.01w to reduce the search space of the algorithm.
Bonus function: the reward function employed in the embodiments of the present invention is shown in equation (20) and represents the energy efficiency of the communication system. r is (r) total Is the total data throughput of the system, EC total Is the total energy consumption of all communication nodes of the system. Prize valueThe larger this represents the higher the energy efficiency of the communication system.
S33, adjusting the current running state of the virtual power plant communication system to be the target running state.
After the target running state corresponding to the minimum total system energy consumption of the virtual power plant communication system is determined, the current running state of the virtual power plant communication system is adjusted to be the target running state, and allocation of baseband processing resources in BBU Pool, connection relation between RRH and UE, transmission power and the like can be scheduled.
S34, acquiring the first total energy consumption of the baseband processing unit pool of the virtual power plant communication system in the target running state in unit time and the second total energy consumption of all the radio frequency equipment.
Under the target running state, acquiring the data throughput of a baseband processing unit Pool (BBU Pool) of the virtual power plant communication system in unit time, and determining the first total energy consumption of the baseband processing unit Pool based on the data throughput and the formula (1) and the formula (2).
Correspondingly, in the target operation state, the signal transmitting power provided by all radio frequency devices (RRH) for the corresponding received signal strength indicator (UE) in unit time is obtained, and the second total energy consumption of all radio frequency devices can be determined based on the signal transmitting power and the above formula (3).
S35, determining target system total energy consumption of the virtual power plant communication system based on the first total energy consumption and the second total energy consumption.
The first total energy consumption and the second total energy consumption are summed, and a target system total energy consumption of the virtual power plant communication system can be determined.
S36, acquiring the collection quantity of distributed energy sources of the virtual power plant communication system and the current energy reserve quantity of all the radio frequency equipment.
In the embodiment of the invention, the renewable energy collection device equipped with the communication node mainly aims at solar energy and solar energy The collection of wind energy, BBU Pool can be regarded as a whole, the collection amount of renewable energy sources of the jth RRH in time slot t can be expressed as a formula (21),for solar energy collection, +.>For wind energy collection capacity->Represents the renewable energy input by BBU Pool to the jth RRH at time slot t,/H>Representing the renewable energy output by the jth RRH to the BBU Pool at time slot t. Equation (22) and equation (23) show the renewable energy collection amount of the BBU Pool in time slot t, the renewable energy sharing considers both the part output from the BBU Pool to the RRH and the part input from the RRH to the BBU Pool, and on the basis, the consideration of the energy sharing loss is further added, the energy loss is positively correlated with the physical distance between the RRH and the BBU Pool, β is the coefficient of energy loss, and dis (j) is the physical distance between the jth RRH and the BBU Pool.
RE BBUPool (t)＝RE solar (t)+RE wind (t)+RE share (t) (23)
The total energy remaining at time t by the energy storage device of the jth RRH can be expressed as formula (24),for initial energy of the energy storage device, based on this, for eachAnd summing the energy consumption of each time slot and the renewable energy collection quantity to obtain the residual total energy. Similarly, the total energy remaining in the energy storage device of the BBU Pool can be obtained as shown in formula (25).
Constraint (26) and constraint (27) indicate that the energy stored by the energy storage devices configured by the RRH and BBU Pool cannot exceed a maximum capacity and cannot be negative. Equation (28) is an optimization objective for renewable energy scheduling, minimizing transmission loss during renewable energy sharing to ensure that as much renewable energy is collected as possible for the energy supply of the communication node.
And S37, managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
In the virtual power plant communication system, a BBU Pool and an RRH are provided with a renewable energy collection device and an energy storage device. The total energy which can be reserved by the energy storage device is limited and cannot exceed the design maximum capacity, so that idle waste of energy is avoided due to insufficient or surplus renewable energy sources of part of communication nodes, and the energy sharing between the RRH and the BBU Pool can be allowed, and the utilization rate of the renewable energy sources can be improved. In this process, the energy loss mainly includes two aspects, the first aspect is the transmission loss in the energy sharing process, and the second aspect is that surplus energy caused by the fact that the energy storage device has reached the maximum capacity cannot be stored in time, and the part of energy can be sold through a power grid.
When renewable energy collected by the RRH at a time slot t is insufficient, firstly energy is obtained from an energy storage device equipped by the RRH, secondly energy is obtained from other reachable nodes through an energy sharing mechanism, and if the energy consumption of the RRH still cannot be met, the rest required energy is obtained from a power grid. When surplus exists in renewable energy collected by the RRH in a time slot t, firstly, the surplus energy is considered to be stored in an energy storage device of the RRH, if the energy storage device is full, the surplus energy is transmitted to RRH with other energy shortage through an energy sharing mechanism, and if the surplus still exists in the renewable energy, the surplus energy is sold to a power grid.
Aiming at how to manage surplus energy and how to determine the processing mode of the surplus energy, the embodiment of the invention can use a method of lasting DQN based on a value function for solving. With respect to the conventional DQN algorithm, the forcing DQN is optimized for the structure of the neural network, separating the action cost function Q into a state cost function V(s) that can be determined from the state s alone and a dominance function a (s, a) that is determined from the action a. The state-cost function V(s) is a mathematical expectation of all action values in state s, and the dominance function a (s, a) represents the deviation of action a from all possible action value mathematical expectations in state s. In the final output layer, V(s) and a (s, a) are added to obtain Q (s, a), specifically, Q (s, a) represents the value of the action a in the state s, and the actions a, Q (s, a) when Q (s, a) is selected to take the maximum value each time are shown in the formula (29).
Q(s,a)＝V(s)+A(s,a) (29)
The state space s defined by the embodiment of the invention mainly comprises the current reserve energy of each communication node, the renewable energy collection quantity and the energy consumption of the communication system. The action space can schedule renewable energy sharing between the BBU Pool and each RRH, and purchase and sell electricity from the power grid by the communication node.
The reward function can be expressed as formula (30), which is a negative value of the sum of transmission losses during renewable energy sharing, and when the sum of energy transmission losses takes a minimum value, the reward function obtains a maximum value, and the renewable energy utilization rate of the system is the maximum.
According to the distributed energy management method provided by the embodiment of the invention, the current running state of the virtual power plant communication system and the current system total energy consumption corresponding to the current running state are obtained; determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum; adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state; the obtained distributed energy is managed based on the total energy consumption of the target system, the energy is managed on the basis of guaranteeing the energy efficiency maximization of the virtual power plant communication system, the hybrid energy supply of the virtual power plant communication system is realized, and the energy utilization rate is improved.
Fig. 5 is a schematic structural diagram of a distributed energy management device according to an embodiment of the present invention, which specifically includes:
an obtaining module 501, configured to obtain a current operation state of a communication system of a virtual power plant and a current system total energy consumption corresponding to the current operation state;
A determining module 502, configured to determine a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, where the total system energy consumption of the virtual power plant communication system in the target operating state is minimum;
an adjustment module 503, configured to adjust a current operating state of the virtual power plant communication system to the target operating state, and determine a target total system energy consumption of the virtual power plant communication system based on the target operating state;
and the management module 504 is configured to manage the obtained distributed energy based on the total energy consumption of the target system.
In a possible implementation manner, the determining module 502 is specifically configured to determine, based on the current operating state and the current total system energy consumption, a desired value of the prize corresponding to the other operating state; and taking the running state with the maximum rewarding expected value as the target running state of the virtual power plant communication system.
In a possible implementation manner, the determining module 502 is further configured to obtain a first total energy consumption of a baseband processing unit pool of the virtual power plant communication system in the target operating state and a second total energy consumption of all radio frequency devices in a unit time; a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
In a possible implementation manner, the determining module 502 is further configured to obtain a data throughput of a baseband processing unit pool of the virtual power plant communication system in the target operating state in a unit time; the first total energy consumption is determined based on the data throughput.
In a possible implementation manner, the determining module 502 is further configured to obtain signal transmission power provided by all radio frequency devices for the corresponding received signal strength indicator in a unit time; the second total energy consumption is determined based on the signal transmit power.
In one possible implementation, the management module 504 is specifically configured to obtain a collection amount of distributed energy of the virtual power plant communication system and a current energy reserve amount of all radio frequency devices; and managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
In a possible implementation manner, the management module 504 is further configured to obtain a target amount of energy from a preset energy storage device for the virtual power plant communication system to operate normally if the sum of the current energy reserve amount and the collection amount of the distributed energy is less than the total energy consumption of the target system; and if the sum of the current energy reserve and the collection amount of the distributed energy sources is greater than the total energy consumption of the target system, storing surplus energy sources in an energy storage device.
The distributed energy management device provided in this embodiment may be a distributed energy management device as shown in fig. 5, and may perform all steps of the distributed energy management method as shown in fig. 2-3, so as to achieve the technical effects of the distributed energy management method as shown in fig. 2-3, and the detailed description will be omitted herein for brevity.
Fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present invention, and a computer device 600 shown in fig. 6 includes: at least one processor 601, memory 602, at least one network interface 604, and other user interfaces 603. The various components in computer device 600 are coupled together by a bus system 605. It is understood that the bus system 605 is used to enable connected communications between these components. The bus system 605 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration the various buses are labeled as bus system 605 in fig. 6.
The user interface 603 may include, among other things, a display, a keyboard, or a pointing device (e.g., a mouse, a trackball, a touch pad, or a touch screen, etc.).
It is to be appreciated that the memory 602 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (Double Data Rate SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and Direct memory bus RAM (DRRAM). The memory 602 described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some implementations, the memory 602 stores the following elements, executable units or data structures, or a subset thereof, or an extended set thereof: an operating system 6021 and application programs 6022.
The operating system 6021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 6022 includes various application programs such as a Media Player (Media Player), a Browser (Browser), and the like for realizing various application services. The program for implementing the method of the embodiment of the present invention may be included in the application 6022.
In the embodiment of the present invention, the processor 601 is configured to execute the method steps provided by the method embodiments by calling a program or an instruction stored in the memory 602, specifically, a program or an instruction stored in the application 6022, for example, including:
acquiring the current running state of a virtual power plant communication system and the total energy consumption of the current system corresponding to the current running state; determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum; adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state; and managing the acquired distributed energy based on the total energy consumption of the target system.
In one possible implementation, determining a reward expectation value corresponding to other operating states based on the current operating state and the current system total energy consumption; and taking the running state with the maximum rewarding expected value as the target running state of the virtual power plant communication system.
In one possible implementation manner, a first total energy consumption of a baseband processing unit pool of the virtual power plant communication system in the target running state and a second total energy consumption of all radio frequency devices in a unit time are obtained; a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
In one possible implementation, the data throughput of the baseband processing unit pool of the virtual power plant communication system in the target running state in unit time is obtained; the first total energy consumption is determined based on the data throughput.
In one possible implementation manner, the signal transmitting power provided by all radio frequency devices for the corresponding received signal strength indicators in a unit time is obtained; the second total energy consumption is determined based on the signal transmit power.
In one possible implementation, the collection amount of distributed energy sources of the virtual power plant communication system and the current energy reserve amount of all radio frequency devices are obtained; and managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
In one possible implementation manner, if the sum of the current energy reserve and the collection amount of the distributed energy sources is smaller than the total energy consumption of the target system, a target number of energy sources are obtained from a preset energy storage device for the normal operation of the virtual power plant communication system; and if the sum of the current energy reserve and the collection amount of the distributed energy sources is greater than the total energy consumption of the target system, storing surplus energy sources in an energy storage device.
The method disclosed in the above embodiment of the present invention may be applied to the processor 601 or implemented by the processor 601. The processor 601 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 601 or instructions in the form of software. The processor 601 may be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software elements in a decoding processor. The software elements may be located in a random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 602, and the processor 601 reads information in the memory 602 and performs the steps of the above method in combination with its hardware.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For a hardware implementation, the processing units may be implemented within one or more application specific integrated circuits (Application Specific Integrated Circuits, ASIC), digital signal processors (Digital Signal Processing, DSP), digital signal processing devices (dspev, DSPD), programmable logic devices (Programmable Logic Device, PLD), field programmable gate arrays (Field-Programmable Gate Array, FPGA), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented by means of units that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
The computer device provided in this embodiment may be a computer device as shown in fig. 6, and may perform all the steps of the distributed energy management method shown in fig. 2-3, so as to achieve the technical effects of the distributed energy management method shown in fig. 2-3, and the detailed description will be omitted herein for brevity.
The embodiment of the invention also provides a storage medium (computer readable storage medium). The storage medium here stores one or more programs. Wherein the storage medium may comprise volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid state disk; the memory may also comprise a combination of the above types of memories.
When the one or more programs in the storage medium are executable by the one or more processors, the distributed energy management method executed on the computer device side is implemented.
The processor is used for executing the distributed energy management program stored in the memory to realize the following steps of the distributed energy management method executed on the computer equipment side:
acquiring the current running state of a virtual power plant communication system and the total energy consumption of the current system corresponding to the current running state; determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum; adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state; and managing the acquired distributed energy based on the total energy consumption of the target system.
In one possible implementation, determining a reward expectation value corresponding to other operating states based on the current operating state and the current system total energy consumption; and taking the running state with the maximum rewarding expected value as the target running state of the virtual power plant communication system.
In one possible implementation manner, a first total energy consumption of a baseband processing unit pool of the virtual power plant communication system in the target running state and a second total energy consumption of all radio frequency devices in a unit time are obtained; a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
In one possible implementation, the data throughput of the baseband processing unit pool of the virtual power plant communication system in the target running state in unit time is obtained; the first total energy consumption is determined based on the data throughput.
In one possible implementation manner, the signal transmitting power provided by all radio frequency devices for the corresponding received signal strength indicators in a unit time is obtained; the second total energy consumption is determined based on the signal transmit power.
In one possible implementation, the collection amount of distributed energy sources of the virtual power plant communication system and the current energy reserve amount of all radio frequency devices are obtained; and managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
In one possible implementation manner, if the sum of the current energy reserve and the collection amount of the distributed energy sources is smaller than the total energy consumption of the target system, a target number of energy sources are obtained from a preset energy storage device for the normal operation of the virtual power plant communication system; and if the sum of the current energy reserve and the collection amount of the distributed energy sources is greater than the total energy consumption of the target system, storing surplus energy sources in an energy storage device.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of function in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (9)
1. A distributed energy management method, comprising:
acquiring the current running state of a virtual power plant communication system and the total energy consumption of the current system corresponding to the current running state;
determining a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, wherein the total system energy consumption of the virtual power plant communication system in the target operating state is minimum;
Adjusting the current operation state of the virtual power plant communication system to the target operation state, and determining the total target system energy consumption of the virtual power plant communication system based on the target operation state;
managing the obtained distributed energy based on the total energy consumption of the target system;
the determining the total target system energy consumption of the virtual power plant communication system based on the target operating state includes:
acquiring the first total energy consumption of a baseband processing unit pool of the virtual power plant communication system and the second total energy consumption of all radio frequency equipment in the target running state in unit time;
a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
2. The method of claim 1, wherein the determining the target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption comprises:
determining a reward expected value corresponding to other running states based on the current running state and the total energy consumption of the current system;
and taking the running state with the maximum rewarding expected value as the target running state of the virtual power plant communication system.
3. The method according to claim 1, wherein said obtaining a first total energy consumption of a pool of baseband processing units of the virtual power plant communication system in said target operating state for a unit time comprises:
acquiring the data throughput of a baseband processing unit pool of the virtual power plant communication system in the target running state in unit time;
the first total energy consumption is determined based on the data throughput.
4. The method of claim 1, wherein the obtaining the second total energy consumption of all radio frequency devices in a unit time comprises:
acquiring signal transmitting power provided by all radio frequency equipment for a corresponding received signal strength indicator in unit time;
the second total energy consumption is determined based on the signal transmit power.
5. The method of claim 1, wherein the managing the acquired distributed energy based on the target system total energy consumption comprises:
acquiring the collection quantity of distributed energy sources of the virtual power plant communication system and the current energy reserve quantity of all radio frequency equipment;
and managing the acquired distributed energy based on the current energy reserve and the total energy consumption of the target system.
6. The method of claim 5, wherein the managing the acquired distributed energy based on the current energy reserve and the target system total energy consumption comprises:
if the sum of the current energy reserve and the collection amount of the distributed energy is smaller than the total energy consumption of the target system, acquiring a target number of energy sources from a preset energy storage device for the normal operation of the virtual power plant communication system;
and if the sum of the current energy reserve and the collection amount of the distributed energy sources is greater than the total energy consumption of the target system, storing surplus energy sources in an energy storage device.
7. A distributed energy management apparatus, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the current running state of a virtual power plant communication system and the current system total energy consumption corresponding to the current running state;
a determining module, configured to determine a target operating state of the virtual power plant communication system based on the current operating state and the current total system energy consumption, where the total system energy consumption of the virtual power plant communication system in the target operating state is minimal;
the adjusting module is used for adjusting the current running state of the virtual power plant communication system to the target running state and determining the total target system energy consumption of the virtual power plant communication system based on the target running state;
The management module is used for managing the acquired distributed energy based on the total energy consumption of the target system;
the adjusting module is further used for acquiring the first total energy consumption of the baseband processing unit pool of the virtual power plant communication system in the target running state in unit time and the second total energy consumption of all radio frequency equipment; a target system total energy consumption of the virtual power plant communication system is determined based on the first total energy consumption and the second total energy consumption.
8. A computer device, comprising: a processor and a memory for executing a distributed energy management program stored in the memory to implement the distributed energy management method of any one of claims 1 to 6.
9. A storage medium storing one or more programs executable by one or more processors to implement the distributed energy management method of any of claims 1-6.
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