feat(零碳): 长庆演示系统新增功能

1.修改第三方日累计数据推送表表结构,增加日累计储能放电量字段,同时修改代码对应实体及mapper文件,修改相关接口增加储能日累计放电量接收逻辑;
2.修改首页井场收益分析模块接口,修改获取储能累计放电量逻辑;
3.设计并创建井口日用电趋势表,生成对应实体类及mapper文件;
4.统计分析模块,新增本月累计节电经济效益查询接口,添加线上接口文档并完成接口冒烟测试;
5.统计分析模块,新增本月累计减碳量查询接口,添加线上接口文档并完成接口冒烟测试;
6.统计分析模块,新增光伏发电趋势查询接口,添加线上接口文档并完成接口冒烟测试;
7.统计分析模块,新增月度总览查询接口,添加线上接口文档并完成接口冒烟测试;

BREAKING CHANGE: 无

Closes 无

[skip ci]

C12-prediction/pps-core-prediction/src/main/java/pps/core/prediction/mapper/ThirdActivePowerViewMapper.java

@@ -49,4 +49,12 @@ public interface ThirdActivePowerViewMapper {
      * @return {@link List }<{@link ThirdActivePowerView }>
      */
     List<ThirdActivePowerView> selectAvgPhotovoltaicPower(ThirdActivePowerView record);
+
+    /**
+     * 获得15分钟平均功率
+     *
+     * @param record 记录
+     * @return {@link List }<{@link ThirdActivePowerView }>
+     */
+    List<ThirdActivePowerView> selectAvgPower15(ThirdActivePowerView record);
 }

C12-prediction/pps-core-prediction/src/main/java/pps/core/prediction/service/PlantPredictedPowerShortTermService.java

 package pps.core.prediction.service;
 
+import cn.hutool.core.collection.CollUtil;
+import cn.hutool.core.date.DateField;
+import cn.hutool.core.date.DateTime;
+import cn.hutool.core.date.DateUtil;
+import cn.hutool.core.util.ObjectUtil;
+import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
 import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
+import pps.core.common.constant.BusinessConstant;
+import pps.core.prediction.entity.ConfigShowEnt;
 import pps.core.prediction.entity.PlantPredictedPowerShortTermEnt;
+import pps.core.prediction.entity.ThirdActivePowerView;
+import pps.core.prediction.mapper.ConfigShowMapper;
 import pps.core.prediction.mapper.PlantPredictedPowerShortTermMapper;
+import pps.core.prediction.mapper.ThirdActivePowerViewMapper;
+import pps.core.prediction.service.data.plant_predicted_power_data.GetPredictedPowerOutput;
 import pps.core.prediction.service.data.plant_predicted_power_mid_term.GetPlantPredictedPowerMidTermOutput;
 import pps.core.prediction.service.data.plant_predicted_power_short_term.GetPlantPredictedPowerShortTermInput;
 import xstartup.annotation.XService;
@@ -14,10 +26,17 @@ import xstartup.base.util.XStringUtils;
 import xstartup.data.XListResult;
 import xstartup.feature.api.annotation.XApiGet;
 
-import java.util.Date;
-import java.util.List;
+import java.math.BigDecimal;
+import java.util.*;
+import java.util.stream.Collectors;
 
 
+/**
+ * 短期功率预测
+ *
+ * @author ZWT
+ * @date 2024/06/06
+ */
 @XService
 @XText("电站预测功率短期72小时数据")
 public class PlantPredictedPowerShortTermService {
@@ -33,14 +52,87 @@ public class PlantPredictedPowerShortTermService {
         return XListResult.success(outputs);
     }
 
+    /**
+     * 一天功率预测
+     *
+     * @param context 上下文
+     * @param input   输入
+     * @return {@link XListResult }<{@link GetPredictedPowerOutput }>
+     */
     @XApiGet
     @XText("根据电站预测1天的预测数据")
-    public XListResult<GetPlantPredictedPowerMidTermOutput> getOnePlantPredictedPowerShortTermList(XContext context, GetPlantPredictedPowerShortTermInput input) {
+    public XListResult<GetPredictedPowerOutput> getOnePlantPredictedPowerShortTermList(XContext context, GetPlantPredictedPowerShortTermInput input) {
+        //判断是否需要启用演示配置
+        DateTime date = DateUtil.date();
+        DateTime inputTime = DateUtil.parse(input.getStartTime(), BusinessConstant.DATE_FORMAT_DAY);
+        ConfigShowMapper configMapper = context.getBean(ConfigShowMapper.class);
+        ConfigShowEnt configShowEnt = configMapper.selectOne(new LambdaQueryWrapper<ConfigShowEnt>()
+                .last("LIMIT 1"));
+        Date showTime;
+        DateTime day;
+        int betweenDay;
+        if (ObjectUtil.isAllNotEmpty(configShowEnt, configShowEnt.getChoiceDate(), configShowEnt.getChoiceDate())) {
+            DateTime choiceDate = DateUtil.date(configShowEnt.getChoiceDate());
+            day = configShowEnt.getIsEnable().equals(0) ? choiceDate : inputTime;
+            showTime = DateUtil.parse(day.toString(BusinessConstant.DATE_FORMAT_DAY) + " " + date.toString(BusinessConstant.TIME_FORMAT));
+            //计算偏移
+            betweenDay = (int) DateUtil.betweenDay(inputTime, day, false);
+            if (DateUtil.compare(day, inputTime) > 0) {
+                betweenDay = -betweenDay;
+            }
+        } else {
+            day = inputTime;
+            showTime = date;
+            betweenDay = 0;
+        }
+        DateTime beginTime = DateUtil.offsetMinute(day, -1);
+        DateTime endTime = DateUtil.offsetDay(day, 1);
+        //查一天预测
         PlantPredictedPowerShortTermMapper mapper = context.getBean(PlantPredictedPowerShortTermMapper.class);
-        QueryWrapper<PlantPredictedPowerShortTermEnt> queryWrapper = setQueryWrapper(input.getPlantId(), input.getStartTime(), 1);
-        List<PlantPredictedPowerShortTermEnt> list = mapper.selectList(queryWrapper);
-        List<GetPlantPredictedPowerMidTermOutput> outputs = XCopyUtils.copyNewList(list, GetPlantPredictedPowerMidTermOutput.class);
-        ThirdActivePowerServiceHelper.getActivePower(context, outputs, input.getPlantId(), null);
+        List<PlantPredictedPowerShortTermEnt> predictedList = mapper.selectList(new LambdaQueryWrapper<PlantPredictedPowerShortTermEnt>()
+                .eq(PlantPredictedPowerShortTermEnt::getPlantId, input.getPlantId())
+                .between(PlantPredictedPowerShortTermEnt::getDataDate, beginTime, endTime)
+                .orderByAsc(PlantPredictedPowerShortTermEnt::getDataDate)
+        );
+        Map<DateTime, BigDecimal> predictedMap;
+        if (CollUtil.isNotEmpty(predictedList)) {
+            predictedMap = predictedList.stream()
+                    .collect(Collectors.toMap(x -> DateUtil.parse(x.getDataDate()), PlantPredictedPowerShortTermEnt::getPredictPower));
+        } else {
+            predictedMap = Collections.emptyMap();
+        }
+        //查实际功率
+        ThirdActivePowerViewMapper powerMapper = context.getBean(ThirdActivePowerViewMapper.class);
+        List<ThirdActivePowerView> powerList = powerMapper.selectAvgPower15(ThirdActivePowerView.builder()
+                .stationId(input.getPlantId())
+                .startTime(beginTime)
+                .endTime(showTime)
+                .build());
+        Map<Date, BigDecimal> powerMap;
+        if (CollUtil.isNotEmpty(powerList)) {
+            powerMap = powerList.stream()
+                    .collect(Collectors.toMap(ThirdActivePowerView::getInputTime, ThirdActivePowerView::getPhotovoltaicPower));
+        } else {
+            powerMap = Collections.emptyMap();
+        }
+        //取时间范围
+        List<DateTime> rangeToList = DateUtil.rangeToList(day, endTime, DateField.MINUTE, 15);
+        GetPredictedPowerOutput output;
+        List<GetPredictedPowerOutput> outputs = new ArrayList<>(rangeToList.size());
+        for (DateTime dateTime : rangeToList) {
+            output = new GetPredictedPowerOutput();
+            //匹配预测发电量
+            output.setPredictPower(predictedMap.getOrDefault(dateTime, BigDecimal.ZERO));
+            //匹配实际发电量
+            output.setPower(powerMap.getOrDefault(dateTime, BigDecimal.ZERO));
+            //时间偏移
+            if (betweenDay != 0) {
+                output.setDataDate(DateUtil.offsetDay(dateTime, betweenDay));
+            } else {
+                output.setDataDate(dateTime);
+            }
+            outputs.add(output);
+        }
         return XListResult.success(outputs);
     }
 

C12-prediction/pps-core-prediction/src/main/java/pps/core/prediction/service/data/plant_predicted_power_data/GetPredictedPowerOutput.java

+package pps.core.prediction.service.data.plant_predicted_power_data;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+import xstartup.annotation.XText;
+
+import java.math.BigDecimal;
+import java.util.Date;
+
+/**
+ * 光伏预测
+ *
+ * @author ZWT
+ * @date 2024/06/06 15:42
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+@Builder
+public class GetPredictedPowerOutput {
+    @XText("日期")
+    private Date dataDate;
+
+    @XText("实际功率")
+    private BigDecimal power;
+
+    @XText("预测功率")
+    private BigDecimal predictPower;
+}

C12-prediction/pps-core-prediction/src/main/java/pps/core/prediction/service/data/plant_predicted_power_mid_term/GetPlantPredictedPowerMidTermOutput.java

@@ -2,14 +2,26 @@ package pps.core.prediction.service.data.plant_predicted_power_mid_term;
 
 import com.baomidou.mybatisplus.annotation.IdType;
 import com.baomidou.mybatisplus.annotation.TableId;
+import lombok.AllArgsConstructor;
+import lombok.Builder;
 import lombok.Data;
+import lombok.NoArgsConstructor;
 import xstartup.annotation.XText;
 
 import java.io.Serializable;
 import java.math.BigDecimal;
 import java.util.Date;
 
+/**
+ * 获取电厂预测功率中期输出
+ *
+ * @author ZWT
+ * @date 2024/06/06
+ */
 @Data
+@NoArgsConstructor
+@AllArgsConstructor
+@Builder
 public class GetPlantPredictedPowerMidTermOutput implements Serializable {
     @TableId(type = IdType.AUTO)
     private Integer id;
@@ -28,5 +40,4 @@ public class GetPlantPredictedPowerMidTermOutput implements Serializable {
 
     @XText("创建时间")
     private Date createTime;
-
 }

C12-prediction/pps-core-prediction/src/main/resources/mybatis/mapper/pps/core/prediction/ThirdActivePowerViewMapper.xml

@@ -9,7 +9,7 @@
         <result column="photovoltaic_power" property="photovoltaicPower" jdbcType="DECIMAL"/>
         <result column="meter_power" property="meterPower" jdbcType="DECIMAL"/>
         <result column="system_source" property="systemSource" jdbcType="VARCHAR"/>
-        <result column="input_time" property="inputTime" jdbcType="DATE"/>
+        <result column="input_time" property="inputTime" jdbcType="VARCHAR"/>
     </resultMap>
     <sql id="Base_Column_List">
         id
@@ -132,4 +132,33 @@
         ORDER BY g.station_name,
                  g.create_time
     </select>
+
+    <select id="selectAvgPower15" parameterType="pps.core.prediction.entity.ThirdActivePowerView"
+            resultMap="BaseResultMap">
+        SELECT IFNULL(AVG(z.photovoltaic_power), 0) AS photovoltaic_power,
+        z.input_time
+        FROM (SELECT photovoltaic_power,
+        CASE
+
+        WHEN MINUTE ( input_time) IN ( 10, 40 ) THEN
+        DATE_SUB( input_time, INTERVAL + 10 MINUTE )
+        WHEN MINUTE ( input_time ) IN ( 20, 50 ) THEN
+        DATE_SUB( input_time, INTERVAL + 5 MINUTE ) ELSE input_time
+        END input_time
+        FROM
+        third_active_power
+        WHERE
+        station_id = #{stationId}
+        AND input_time &gt;= #{startTime}
+        <if test="endTime != null">
+            AND input_time &lt;= #{endTime}
+        </if>
+        ORDER BY
+        input_time ASC
+        ) z
+        GROUP BY
+        z.input_time
+        ORDER BY
+        z.input_time
+    </select>
 </mapper>
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