CN113890024A - 一种非侵入式负荷智能分解和优化控制方法 - Google Patents
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Abstract
一种非侵入式负荷智能分解和优化控制方法,旨在解决如何实现在总线上测量用电器用电数据以及进行控制的技术问题。该方法包括:测量用户端用电数据和环境参数,利用无线通讯方式传输数据并处理数据,利用滑动窗口截取功率、功率因数、环境参数并进行标准化;输入训练好的带有Attention算法的LSTM神经网络分解出各用电器功率和开关状态,并根据环境参数等确定是否需要施加控制,通过继电器对用电器进行开关控制。本发明使用总线功率、功率因数的时间序列作为主要数据,综合考虑环境因素对负荷情况的影响,对复杂的总线用电数据进行特征提取和分解,从而实现一对多的测量,既降低了传感器的数量,也能获得相对精确的测量结果。
Description
技术领域:
本发明涉及能源动力系统中的用电监测及分析方法,特别涉及一种非侵入式负荷智能分解和优化控制方法,属于能源动力工程领域。
背景技术:
面对用电负荷不确定和供电电力不确定这样一个双重不确定性的复杂问题,智能电网的实现需要多层级技术:高度的信息集中技术、高效灵活的调度控制技术等,而这些技术的一个应用前提是对用电负荷数据的获取。例如,除了使用传统的发电端和输电端调峰手段,也可以调节用户端的用电,在识别出用户端的用电情况后,为用户提供用高峰期电建议,将一些非必要的高功率用电器安排到用电和电价低谷期。通过合理安排用户端不同用电器的使用时间,达到既能降低电网运行压力,也提高用户用电经济性的效果。然而,这一切都只有基于精确到用电器的负荷测量技术才能实现。只有获取用电器这一层级的信息,才能合理地规划用户侧用电安排以削峰填谷,从而降低电力负荷需求、稳定电网运行,达到智能电网要求。
现行的负荷测量技术(即传统电表)只能读取用电总量,显然难以满足上述要求。现已有通过传感器与用电设备一对一监测的形式测量用户端用电情况的方式,即侵入式监测,能够得到准确而详细的用电数据的技术。但这种监测方式需要传感器的数量堆积才能够获得用户端所有用电器的详细测量结果,若在学校、工厂等用电器数量庞大的场合采用这种形式,需要很高的安装和维护成本。不少文献对非侵入式负荷监测进行了研究,如“非侵入式电力负荷分解方法、装置、设备及介质”(CN 113177299 A)提出了一种非侵入式负荷监测装置和基于状态转换事件的CUSUM事件转换算法,可以更准确的检测出单一设备和多设备的状态转换事件。“一种基于非侵入式注意力预处理过程与BiLSTM模型的预测方法”(CN 113177666 A),采用深度学习方法,考虑时间序列的输入,并采取了一种注意力预处理过程,部分加强了对时间序列的处理能力。但这些方法对于历史数据和环境参数的特征提取仍不充分,不能很好适应快速变化的负荷,且仅包含测量功能,测量后无法进一步控制用电设备。
发明内容
针对现有技术中存在的问题和缺陷,本发明的目的是提供一种非侵入式负荷智能分解和优化控制方法,使其仅通过测量总线数据和部分环境参数即可识别监测各用电器负荷成分,实现一对多的测量,并适应负荷快速变化的情况,获得更高的测量精度;同时降低传感器的数量,达到进一步降低成本的目的。
本发明的技术方案如下:
一种非侵入式负荷智能分解与优化控制方法,其特征在于该方法包含以下步骤:
S1:以采样频率f采集如下数据:用电表采集用户所有用电器总线功率P和总线功率因数用湿度传感器采集环境湿度H;用温度传感器采集环境温度T;用光照强度传感器采集环境光照强度I;所述的所有用电器包括用于调节环境参数的用电器和与环境参数无关的用电器;
S3:将步骤S2所述窗口中的数据输入到预训练的带有Attention算法的LSTM网络,对总线功率、总线功率因数和环境参数进行特征提取和分解,得到所有用电器的开关状态及功率;
S4:对所有用电器开关状态及功率进行优化控制,并根据环境参数确定是否需要施加控制,若需要优化控制,则通过关闭或开启调节环境参数的用电器,使得环境参数维持在正常范围内。
进一步地,所述调节环境参数的用电器包括空调设备、照明设备以及加湿设备。
进一步地,所述优化控制包括以下几方面:
1)安全监测:设定安全阈值,根据得到的所有用电器功率,自动关闭用电器,以满足安全控制目标,具体控制逻辑为:若Pt-1≥P0,则令st=-1;若Pt-1<P0,则令st=st-1,其中,st表示t时刻用电器开关状态,st=1表示用电器开启,st=-1表示用电器关闭,P0为安全阈值,Pt-1为(t-1)时刻用电器的功率;
2)湿度控制:根据得到的加湿设备开关状态和当前环境湿度,自动开启或关闭加湿设备,以满足湿度控制目标;具体控制逻辑为:
式中,At表示t时刻加湿设备的开关状态,At=1时代表开启,At=-1时代表关闭,H代表当前的环境湿度,H1和H2表示设置的湿度上限和下限;若At=At-1,则不进行控制,否则改变加湿器开关状态;
3)温度控制:根据得到的空调设备开关状态和当前环境温度,自动开启或关闭空调设备,以满足温度控制目标;具体控制逻辑为:
其中,ACt表示t时刻空调设备的开关状态,ACt=1时代表开启,ACt=-1时代表关闭,T代表当前的环境温度,T1和T2分别表示设置的温度上限和下限;若ACt=ACt-1,则不进行控制,否则改变空调设备的开关状态;
4)照明控制:根据得到的照明设备开关状态和当前环境光照强度,自动开启或关闭照明设备,以满足照明控制目标;具体控制逻辑为:
其中,Lt表示t时刻照明设备的开关状态,Lt=1时代表开启,Lt=-1时代表关闭,I代表当前的环境光照强度,I1和I2分别表示设置的光照强度上限和下限;若Lt=Lt-1,则不进行控制,否则改变照明设备开关状态;
5)用电时段控制:若位于用电高峰时段,则调整高功率用电器的用电时段,断开不必要高功率用电器;当位于用电低谷时段,则自动重新开启所述高功率用电器。
本发明的上述技术方案中,所述对总线功率、总线功率因数和环境参数进行特征提取和分解的方法为:
2)将输入数据送到非侵入式负荷智能分解模型中,模型包括:LSTM编码器、LSTM解码器、Attention算法和全连接层,具体过程为:
i)将输入数据送到LSTM编码器后,利用Attention算法对LSTM单元的隐藏层和输出进行权重计算得到Ci,其公式为:
Ci=∑tai,tyt (1)
ai,t=exp(ei,t)/∑t′exp(ei,t′) (2)
其中,Ci为经过Attention算法计算后输入LSTM解码器的张量,ai,t为不同长短时记忆模型神经网络编码器单元输出对于不同LSTM解码器单元输入的权重,yt为LSTM编码器不同单元的输出,W为可训练权重,hi为LSTM解码器隐藏层;ei,t为中间参数;
ii)将Attention算法得到的Ci输入LSTM解码器,然后将LSTM解码器最后一个时间步的隐藏层输入全连接层,获得所有用电器功率和开关状态。
本发明具有以下优点及突出性的技术效果:①本发明所述方法采集总线用电数据,兼顾环境参数的影响,通过基于深度学习的非侵入式负荷监测NILM(Non-IntrusiveLoad Monitoring)方法,对复杂的总线用电数据进行特征提取和分解,分析得到具体各负荷运行状态,从而实现一对多的测量,既降低了传感器的数量从而降低了成本,也能获得相对精确的测量结果。②相比于现有非侵入式负荷分解方法,该方法利用Attention机制对时间序列进行处理,能够综合提取一段时间的特征,并计算不同时间的权重,因而能够获得更高的精度,并且在负荷变化较大较快的情况下拥有更好的分解性能。③综合考虑了环境参数内包含的用电规律和信息,进一步提高了准确率;同时该方法集成了测量和控制两种功能,能够完整满足节能和电网调控用户端用电的需求,更具有应用价值。
附图说明
图1为本发明中提供的非侵入式负荷智能分解与优化控制装置的电路示意图。
图2本发明所提供的非侵入式负荷智能分解与优化控制方法的流程框图。
图3为本发明所用Attention方法的原理示意图。
图4为实施例中用电器总线功率曲线。
图5为实施例中利用总线功率分解出的冰箱功率。
图6为实施例中利用总线功率分解出的洗衣机功率。
具体实施方式
以下结合附图和实施例对本发明的原理和技术方案做进一步的描述。
本发明提供的一种非侵入式负荷智能分解和优化控制方法,该方法包括如下步骤:
S1:以采样频率f采集如下数据:用电表采集用户所有用电器总线功率P和总线功率因数用湿度传感器采集环境湿度H;用温度传感器采集环境温度T;用光照强度传感器采集环境光照强度I;所述的所有用电器包括用于调节环境参数的用电器和与环境参数无关的用电器;所述调节环境参数的用电器包括空调设备、照明设备以及加湿设备。
其中x即为标准化后的数据,X为数据,Xmean和Xstd分别代表数据的平均值和标准差;
S3:将步骤S2所述窗口中的数据输入到预训练的带有Attention算法的LSTM网络,对总线功率、总线功率因数和环境参数进行特征提取和分解,得到所有用电器的开关状态及功率;所述对总线功率、总线功率因数和环境参数进行特征提取和分解的方法为:
2)将输入数据送到非侵入式负荷智能分解模型中,模型包括:LSTM编码器、LSTM解码器、Attention算法和全连接层,具体过程为:
i)将输入数据送到LSTM编码器后,利用Attention算法对LSTM单元的隐藏层和输出进行权重计算得到Ci,其公式为:
Ci=∑tai,tyt (1)
ai,t=exp(ei,t)/∑t′exp(ei,t′) (2)
其中,Ci为经过Attention算法计算后输入LSTM解码器的张量,ai,t为不同长短时记忆模型神经网络编码器单元输出对于不同LSTM解码器单元输入的权重,yt为LSTM编码器不同单元的输出,W为可训练权重,hi为LSTM解码器隐藏层,ei,t为中间参数;
ii)将Attention算法得到的Ci输入LSTM解码器,然后将LSTM解码器最后一个时间步的隐藏层输入全连接层,获得所有用电器功率和开关状态;
S4:对所有用电器开关状态及功率进行优化控制,并根据环境参数确定是否需要施加控制,若需要优化控制,则通过关闭或开启调节环境参数的用电器,使得环境参数维持在正常范围内。具体优化控制方法包括:
1)安全监测:设定安全阈值,根据得到的所有用电器功率,自动关闭用电器,以满足安全控制目标,具体控制逻辑为:若Pt-1≥P0,则令st=-1;若Pt-1<P0,则令st=st-1,其中,st表示t时刻用电器开关状态,st=1表示用电器开启,st=-1表示用电器关闭,P0为安全阈值,Pt-1为(t-1)时刻用电器的功率;
2)湿度控制:根据得到的加湿设备开关状态和当前环境湿度,自动开启或关闭加湿设备,以满足湿度控制目标;具体控制逻辑为:
式中,At表示t时刻加湿设备的开关状态,At=1时代表开启,At=-1时代表关闭,H代表当前的环境湿度,H1和H2表示设置的湿度上限和下限;若At=At-1,则不进行控制,否则改变加湿器开关状态;
3)温度控制:根据得到的空调设备开关状态和当前环境温度,自动开启或关闭空调设备,以满足温度控制目标;具体控制逻辑为:
其中,ACt表示t时刻空调设备的开关状态,ACt=1时代表开启,ACt=-1时代表关闭,T代表当前的环境温度,T1和T2分别表示设置的温度上限和下限;若ACt=ACt-1,则不进行控制,否则改变空调设备的开关状态;
4)照明控制:根据得到的照明设备开关状态和当前环境光照强度,自动开启或关闭照明设备,以满足照明控制目标;具体控制逻辑为:
其中,Lt表示t时刻照明设备的开关状态,Lt=1时代表开启,Lt=-1时代表关闭,I代表当前的环境光照强度,I1和I2分别表示设置的光照强度上限和下限;若Lt=Lt-1,则不进行控制,否则改变照明设备开关状态;
5)用电时段控制:若位于用电高峰时段,则调整高功率用电器的用电时段,断开不必要高功率用电器;当位于用电低谷时段,则自动重新开启所述高功率用电器。
实施例:本实施例应用于家庭内,所有用电器包括洗衣机、冰箱、烧水壶、电视、微波炉、加湿器、电灯、电动汽车和空调,其中照明设备为电灯、加湿设备为加湿器、空调设备为空调用于调节环境参数。具体的,该方法由非侵入式负荷智能分解和优化控制装置实现。该装置主要包含电表模块、继电器模块、无线通讯模块等(如图1所示)。由于需要测量总线用电数据,电表模块可接入总线进行测量;配置多路继电器,可分别控制各个用电器支路以实现控制功能。两者均采用485通讯方式,与上位机进行通讯。环境温度、湿度、光照强度由独立的传感器测量。在不方便进行有线部署的位置,配置了无线通讯模块以TCP或消息队列方式与数据中心进行数据和指令的传输。所有通讯设备都通过一个220V交流电转12V直流电的变压器进行供电。电表模块测量总线功率和总线功率因数后将数据传递给无线通讯模块,再由其传输给计算机;在计算机中进行数据处理和负荷分解。控制指令可由该计算机传输至无线通讯模块后,再由其传输给继电器,以控制各路用电器的开关。通过预先采集总线数据、环境参数和所有用电器的功率和开关状态,可获得训练数据。按照如图2所示的流程具体完成S1-S4的方法为:
S1:在用户侧以采样频率1Hz采集如下数据并将数据传输至计算机以便进行数据处理:用电表模块采集用电器总线功率P和总线功率因数用湿度传感器采集环境湿度H;用温度传感器采集环境温度T;用光照强度传感器采集环境光照强度I;
S2:窗口长度设定为40,得到形状为(样本数,40,5)的数据,根据公式对其进行标准化;
S3:将S2所述窗口中的数据输入带有Attention算法的LSTM神经网络进行特征提取和分解,得到所有用电器各时刻的开关状态及功率。其方法为:按步骤构建两个网络分别用于输出所有用电器功率和开关状态,其中Attention算法的结构如图3所示;根据用电器个数,将LSTM编码器、LSTM解码器隐藏层维数设置为16,全连接层维数设置为9,输出开关状态的神经网络将最后一个全连接层的激活函数设置为sigmoid函数,而输出功率的神经网络,则将最后一个全连接层的激活函数设置为线性函数;使用采集到的训练数据进行训练;训练完成后,给定一个形状为(40,5)的输入,则输出开关状态的网络能够输出9个[0,1]范围的数作为所有用电器开启的概率γi,然后设置阈值,若γi>0.5,则t时刻i用电器开启,用si,t=1表示,若γi≤0.5,t时刻i用电器关闭,用si,t=-1表示;而输出功率的神经网络可直接输出所有用电器的功率;
运用这种模型进行计算,在开关状态判断上可达到95%以上的准确率,在功率上的分解效果也较好,图4显示了一段时间的总线功率曲线,图5、图6显示其分解出的冰箱和洗衣机功率曲线,此时其余用电器实际和分解得到的功率均为零。可以用损失函数(LossFunction)来衡量训练模型的输出ypredict与真值ytrue的精度差距。常用的两种损失函数如下:
均方差损失函数(Mean Squared Error Loss):
平均绝对误差损失(Mean Absolute Error Loss):
对比最常见的卷积神经网络,采用的LSTM网络和LSTM+Attention网络的损失结果如下表1所示,由此可见,引入Attention机制对提高模型表现是有帮助的。
表1不同网络结构性能对比
S4:对所有用电器开关状态及功率进行优化控制,并根据环境参数确定是否需要施加控制,若需要优化控制,则以无线方式传递指令至非侵入式负荷智能分解和优化控制装置的无线通讯模块,继而通过485将指令传输至控制各个支路的继电器,远程控制关闭或开启可调节环境参数的用电器,使得环境参数维持在正常范围内;优化控制包括:
1)安全监测:设定安全阈值1500W,具体控制逻辑为:若Pt-1≥1500W,则令st=-1;若Pt-1<1500W,则令st=st-1;
2)湿度控制:设置湿度上限和下限分别为70%和40%,具体控制逻辑为:
3)温度控制:设置温度上限和下限分别为35℃和25℃,具体控制逻辑为:
4)照明控制:设置光照强度上线和下限分别为700lx和400lx,具体控制逻辑为:
5)用电时段控制:若位于17:00–21:00用电高峰时段,且检测到电动汽车正在充电,则自动断开充电,并于22:00-次日4:00重新开始充电。
Claims (4)
1.一种非侵入式负荷智能分解与优化控制方法,其特征在于该方法包含以下步骤:
S1:以采样频率f采集如下数据:用电表采集用户所有用电器总线功率P和总线功率因数用湿度传感器采集环境湿度H;用温度传感器采集环境温度T;用光照强度传感器采集环境光照强度I;所述的所有用电器包括用于调节环境参数的用电器和与环境参数无关的用电器;
S3:将步骤S2所述窗口中的数据输入到预训练的带有Attention算法的LSTM网络,对总线功率、总线功率因数和环境参数进行特征提取和分解,得到所有用电器的开关状态及功率;
S4:对所有用电器开关状态及功率进行优化控制,并根据环境参数确定是否需要施加控制,若需要优化控制,则通过关闭或开启调节环境参数的用电器,使得环境参数维持在正常范围内。
2.如权利要求1所述的一种非侵入式负荷智能分解与优化控制方法,其特征在于:所述调节环境参数的用电器包括空调设备、照明设备以及加湿设备。
3.如权利要求1或2所述的一种非侵入式负荷智能分解与优化控制方法,其特征在于,步骤S4中所述优化控制包括:
1)安全监测:设定安全阈值,根据得到的所有用电器功率,自动关闭用电器,以满足安全控制目标,具体控制逻辑为:若Pt-1≥P0,则令st=-1;若Pt-1<P0,则令st=st-1,其中,st表示t时刻用电器开关状态,st=1表示用电器开启,st=-1表示用电器关闭,P0为安全阈值,Pt-1为(t-1)时刻用电器的功率;
2)湿度控制:根据得到的加湿设备开关状态和当前环境湿度,自动开启或关闭加湿设备,以满足湿度控制目标;具体控制逻辑为:
式中,At表示t时刻加湿设备的开关状态,At=1时代表开启,At=-1时代表关闭,H代表当前的环境湿度,H1和H2分别表示设置的湿度上限和下限;若At=At-1,则不进行控制,否则改变加湿器开关状态;
3)温度控制:根据得到的空调设备开关状态和当前环境温度,自动开启或关闭空调设备,以满足温度控制目标;具体控制逻辑为:
其中,ACt表示t时刻空调设备的开关状态,ACt=1时代表开启,ACt=-1时代表关闭,T代表当前的环境温度,T1和T2分别表示设置的温度上限和下限;若ACt=ACt-1,则不进行控制,否则改变空调设备的开关状态;
4)照明控制:根据得到的照明设备开关状态和当前环境光照强度,自动开启或关闭照明设备,以满足照明控制目标;具体控制逻辑为:
其中,Lt表示t时刻照明设备的开关状态,Lt=1时代表开启,Lt=-1时代表关闭,I代表当前的环境光照强度,I1和I2分别表示设置的光照强度上限和下限;若Lt=Lt-1,则不进行控制,否则改变照明设备开关状态;
5)用电时段控制:若位于用电高峰时段,则调整高功率用电器的用电时段,断开不必要高功率用电器;当位于用电低谷时段,则自动重新开启所述高功率用电器。
4.如权利要求1所述的一种非侵入式负荷智能分解与优化控制方法,其特征在于:步骤S3中所述对总线功率、总线功率因数和环境参数进行特征提取和分解的方法为:
2)将输入数据送到非侵入式负荷智能分解模型中,该模型包括:LSTM编码器、LSTM解码器、Attention算法和全连接层,具体过程为:
i)将输入数据送到LSTM编码器后,利用Attention算法对LSTM单元的隐藏层和输出进行权重计算得到Ci,其公式为:
Ci=∑tai,tyt (1)
ai,t=exp(ei,t)/∑t′exp(ei,t′) (2)
其中,Ci为经过Attention算法计算后输入LSTM解码器的张量,ai,t为不同长短时记忆模型神经网络编码器单元输出对于不同LSTM解码器单元输入的权重,yt为LSTM编码器不同单元的输出,W为可训练权重,hi为LSTM解码器隐藏层,ei,t为中间参数;
ii)将Attention算法得到的Ci输入LSTM解码器,然后将LSTM解码器最后一个时间步的隐藏层输入全连接层,获得所有用电器功率和开关状态。
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014075581A1 (zh) * | 2012-11-16 | 2014-05-22 | 天津大学 | 非侵入式电力负荷监测与分解的电流模式匹配方法 |
US20200161867A1 (en) * | 2018-11-15 | 2020-05-21 | Hefei University Of Technology | Method, system and storage medium for load dispatch optimization for residential microgrid |
CN111751650A (zh) * | 2020-07-06 | 2020-10-09 | 重庆大学 | 非侵入式家庭用电设备在线监测系统与故障辨识方法 |
CN111753968A (zh) * | 2020-07-07 | 2020-10-09 | 苏州联电能源发展有限公司 | 非侵入式负荷监测智能电表和电量分解方法 |
CN113177666A (zh) * | 2021-05-21 | 2021-07-27 | 同济大学 | 一种基于非侵入式注意力预处理过程与BiLSTM模型的预测方法 |
-
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- 2021-09-30 CN CN202111157317.2A patent/CN113890024B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014075581A1 (zh) * | 2012-11-16 | 2014-05-22 | 天津大学 | 非侵入式电力负荷监测与分解的电流模式匹配方法 |
US20200161867A1 (en) * | 2018-11-15 | 2020-05-21 | Hefei University Of Technology | Method, system and storage medium for load dispatch optimization for residential microgrid |
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