feat(吉林演示): 松原

1.开发中间库表结构及数据导出功能,检查中间库表结构是否有变动,同时获取最新数据,验证数据是否更新;
2.创建场站每日信息统计记录表,新建场站日信息数据采集汇总定时任务,整理汇总场站纬度每日数据,完成功能验证;
3.针对吉林提供的统计数据,对吉林首页部分功能修改;
4.针对中间库每日井口数据统计表结构变动,修改井口日统计定时任务数据处理逻辑,完成功能验证;
5.修改日发电量统计定时任务,排查数据丢失问题,完成功能验证;
6.修改场站每日信息汇总统计定时任务,增加统计每日光伏发电量逻辑,修改表结构及数据结构和业务处理逻辑,完成功能验证;
7.修改吉林首页线路详情接口,区分部署环境,增加吉林个性化数据处理逻辑,完成接口冒烟测试;
8.修改实际发电功率统计定时任务,排查数据丢失问题,完成功能验证;
9.修改实际发电量统计定时任务,排查数据丢失问题,完成功能验证;
10.修改吉林首页井场效果评价数据统计接口,区分部署环境,增加吉林个性化数据处理逻辑,完成接口冒烟测试;
11.能耗分析页面开发吉林个性化功能,完成电量统计接口开发,编辑线上接口文档并生成接口用例,完成接口冒烟测试;
12.能耗分析页面开发吉林个性化功能,完成发电量统计接口开发,编辑线上接口文档并生成接口用例,完成接口冒烟测试;
13.能耗分析页面开发吉林个性化功能,完成用电量统计接口开发,编辑线上接口文档并生成接口用例,完成接口冒烟测试;
14.能耗分析页面开发吉林个性化功能,完成峰谷能耗对比分析接口开发,编辑线上接口文档并生成接口用例,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/service/EnergyConsumptionAnalysisService.java

@@ -127,6 +127,83 @@ public class EnergyConsumptionAnalysisService {
         return XListResult.success(this.getStatisticsList(context, input, true));
     }
 
+    /**
+     * 峰谷能耗对比分析
+     *
+     * @param context 上下文
+     * @param input   输入
+     * @return {@link XListResult }<{@link GetEnergyComparisonAnalysisOutput }>
+     */
+    @XText("能耗分析--峰谷能耗对比分析")
+    @XApiPost
+    public XListResult<GetEnergyComparisonAnalysisOutput> feeStatisticsList(XContext context, GetStatisticsInput input) {
+        //日期初始化
+        input.getBetweenDate();
+        Date beginTime = input.getBeginTime();
+        Date endTime = input.getEndTime();
+        //查组织机构下所有线路
+        Set<String> lineNameSet = this.getLineNameSet(context, input.getOuId());
+        boolean yearFlag = input.getDateType().equals(3);
+        //统计
+        List<StationDailyProductionSituationEnt> list = context.getBean(StationDailyProductionSituationMapper.class).selectList(new QueryWrapper<StationDailyProductionSituationEnt>()
+                .select("IFNULL( SUM( electricity_charge_city ), 0 ) AS electricity_charge_city",
+                        "IFNULL( SUM( electricity_consumption_vh ), 0 ) AS electricity_consumption_vh",
+                        "IFNULL( SUM( electricity_consumption_np ), 0 ) AS electricity_consumption_np",
+                        "IFNULL( SUM( electricity_consumption_hh ), 0 ) AS electricity_consumption_hh",
+                        "IFNULL( SUM( electricity_consumption_ph ), 0 ) AS electricity_consumption_ph",
+                        yearFlag ? "DATE_FORMAT( data_date, '%Y-%m-01' ) AS data_date" : "data_date")
+                .lambda()
+                .between(StationDailyProductionSituationEnt::getDataDate, beginTime, endTime)
+                .in(StationDailyProductionSituationEnt::getStationName, lineNameSet)
+                .last(yearFlag ? "GROUP BY DATE_FORMAT( data_date, '%Y-%m-01')" : "GROUP BY data_date")
+        );
+        Map<Date, StationDailyProductionSituationEnt> collect;
+        if (CollUtil.isEmpty(list)) {
+            collect = Collections.emptyMap();
+        } else {
+            collect = list.stream()
+                    .collect(Collectors.toMap(StationDailyProductionSituationEnt::getDataDate, Function.identity()));
+        }
+        //封装数据
+        DateTime now = DateUtil.date();
+        List<DateTime> rangeToList = DateUtil.rangeToList(beginTime, endTime, yearFlag ? DateField.MONTH : DateField.DAY_OF_YEAR);
+        List<GetEnergyComparisonAnalysisOutput> outputs = new ArrayList<>(rangeToList.size());
+        StationDailyProductionSituationEnt dailyEnt;
+        BigDecimal electricityFees;
+        BigDecimal valleyElectricPower;
+        BigDecimal ordinaryElectricPower;
+        BigDecimal highElectricPower;
+        BigDecimal peakElectricPower;
+        for (DateTime dateTime : rangeToList) {
+            if (DateUtil.compare(dateTime, now) > 0) {
+                break;
+            }
+            if (collect.containsKey(dateTime)) {
+                dailyEnt = collect.get(dateTime);
+                electricityFees = dailyEnt.getElectricityChargeCity();
+                valleyElectricPower = dailyEnt.getElectricityConsumptionVh();
+                ordinaryElectricPower = dailyEnt.getElectricityConsumptionNp();
+                highElectricPower = dailyEnt.getElectricityConsumptionHh();
+                peakElectricPower = dailyEnt.getElectricityConsumptionPh();
+            } else {
+                electricityFees = BigDecimal.ZERO;
+                valleyElectricPower = BigDecimal.ZERO;
+                ordinaryElectricPower = BigDecimal.ZERO;
+                highElectricPower = BigDecimal.ZERO;
+                peakElectricPower = BigDecimal.ZERO;
+            }
+            outputs.add(GetEnergyComparisonAnalysisOutput.builder()
+                    .electricityFees(electricityFees)
+                    .valleyElectricPower(valleyElectricPower)
+                    .ordinaryElectricPower(ordinaryElectricPower)
+                    .highElectricPower(highElectricPower)
+                    .peakElectricPower(peakElectricPower)
+                    .dateFormat(yearFlag ? dateTime.toString("yyyy-MM") : dateTime.toDateStr())
+                    .build());
+        }
+        return XListResult.success(outputs);
+    }
+
     /**
      * 获取统计列表
      *
@@ -177,6 +254,7 @@ public class EnergyConsumptionAnalysisService {
                 output.setCurrentPeriodGenerate(currentMap.getOrDefault(dateTime, BigDecimal.ZERO));
                 output.setLastPeriodGenerate(lastMap.getOrDefault(dateTime, BigDecimal.ZERO));
             }
+            output.setDateStr(yearFlag ? dateTime.toString("yyyy-MM") : dateTime.toDateStr());
             outputs.add(output);
         }
         return outputs;