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@@ -245,4 +245,263 @@ public class ForecastReportController {
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}
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return R.ok(resultMap);
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}
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+
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+ @GetMapping(value = {"/exportDataEvent/{ycDate}/{cdqDate}/{sjDate}/{agcDate}","/exportDataEvent/{ycDate}/{cdqDate}/{sjDate}/{agcDate}" })
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+ public void exportDataEvent(
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+ @PathVariable("ycDate") Long ycDate,
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+ @PathVariable("cdqDate") Long cdqDate,
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+ @PathVariable("sjDate") Long sjDate,
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+ @PathVariable("agcDate") Long agcDate,
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+ HttpServletResponse response) {
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+
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+ SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd");
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+ String fileName = "预测报表"+simpleDateFormat.format(new Date())+".xlsx";
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+ response.setContentType("application/x-msdownload;charset=utf-8");
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+
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+ try (Workbook workbook = new XSSFWorkbook();ServletOutputStream out = response.getOutputStream()){
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+ response.setHeader("Content-disposition", "attachment; filename=" + URLEncoder.encode(fileName, "UTF-8"));
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+ Date ycStartTime = new Date(ycDate+1000*60*15);
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+ Date ycEndTime = new Date(ycDate+1000*60*1440);
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+ // 获取场站短期实时
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+ QueryWrapper<ForecastPowerShortTerm> queryWrapper = new QueryWrapper<>();
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+ queryWrapper.between("forecast_time", ycStartTime, ycEndTime);
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+ List<ForecastPowerShortTerm> forecastPowerShortTermList = forecastPowerShortTermService.list(queryWrapper);
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+ // 按照场站编号进行分组
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+ Map<String, List<ForecastPowerShortTerm>> stListByStationCodeMap = forecastPowerShortTermList.stream().collect(Collectors.groupingBy(r -> r.getStationCode()));
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+
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+ // 获取nwp实时
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+ QueryWrapper<Nwp> nwpWrapper = new QueryWrapper<>();
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+ nwpWrapper.between("pre_time", ycStartTime, ycEndTime);
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+ List<Nwp> nwpList = nwpService.list(nwpWrapper);
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+ // 按照场站编号进行分组
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+ Map<String, List<Nwp>> nwpListByStationCodeMap = nwpList.stream().collect(Collectors.groupingBy(r -> r.getStationCode()));
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+
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+ // 获取场站超短期实时
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+ Date cdqStartTime = new Date(cdqDate+1000*60*15);
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+ Date cdqEndTime = new Date(cdqDate+1000*60*1440);
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+ QueryWrapper<ForecastPowerUltraShortTerm> cdqWrapper = new QueryWrapper<>();
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+ cdqWrapper.between("forecast_time", cdqStartTime, cdqEndTime);
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+ List<ForecastPowerUltraShortTerm> cdqList = forecastPowerUltraShortTermService.list(cdqWrapper);
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+ // 按照场站编号进行分组
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+ Map<String, List<ForecastPowerUltraShortTerm>> cdqListByStationCodeMap = cdqList.stream().collect(Collectors.groupingBy(r -> r.getStationCode()));
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+
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+ // 获取场站实际功率
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+ Date sjStartTime = new Date(sjDate+1000*60*15);
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+ Date sjEndTime = new Date(sjDate+1000*60*1440);
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+ QueryWrapper<PowerStationStatusData> sjWrapper = new QueryWrapper<>();
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+ sjWrapper.between("time", sjStartTime, sjEndTime);
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+ List<PowerStationStatusData> sjList = powerStationStatusDataService.list(sjWrapper);
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+ // 按照场站编号进行分组
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+ Map<String, List<PowerStationStatusData>> sjListByStationCodeMap = sjList.stream().collect(Collectors.groupingBy(r -> r.getStationCode()));
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+
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+ // 获取agc
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+ Date agcStartTime = new Date(agcDate+1000*60*15);
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+ Date agcEndTime = new Date(agcDate+1000*60*1440);
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+ QueryWrapper<GridApCommandValue> agcWrapper = new QueryWrapper<>();
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+ agcWrapper.between("time", agcStartTime, agcEndTime);
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+ List<GridApCommandValue> agcList = gridApCommandValueService.list(agcWrapper);
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+ // 按照场站编号进行分组
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+ Map<String, List<GridApCommandValue>> agcListByStationCodeMap = agcList.stream().collect(Collectors.groupingBy(r -> r.getStationId()));
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+
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+ List<ElectricField> list = electricFieldService.list();
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+ list.sort((o1, o2) -> o1.getName().compareTo(o2.getName()));
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+ Long momentTime = 15 * 60 * 1000L;
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+ for (int i=0;i<list.size();i++) {
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+ ElectricField electricField = list.get(i);
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+ Sheet sheet = workbook.createSheet(electricField.getName());
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+ // 创建样式 - 水平垂直居中，带边框
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+ CellStyle centerStyle = workbook.createCellStyle();
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+ centerStyle.setAlignment(HorizontalAlignment.CENTER);
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+ centerStyle.setVerticalAlignment(VerticalAlignment.CENTER);
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+ centerStyle.setBorderTop(BorderStyle.THIN);
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+ centerStyle.setBorderBottom(BorderStyle.THIN);
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+ centerStyle.setBorderLeft(BorderStyle.THIN);
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+ centerStyle.setBorderRight(BorderStyle.THIN);
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+ // 创建表头
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+ List<String> headList = new ArrayList<>();
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+ headList.add("时间");
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+ headList.add("风速");
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+ headList.add("短期功率预测");
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+ headList.add("超短期功率预测");
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+ headList.add("实际发电");
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+ headList.add("AGC指令");
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+
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+ // 提取短期map
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+ Map<String, ForecastPowerShortTerm> stListByTimeMap = new HashMap<>();
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+ if (stListByStationCodeMap.get(electricField.getStationCode())!=null){
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+ List<ForecastPowerShortTerm> forecastPowerShortTerms = stListByStationCodeMap.get(electricField.getStationCode());
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+ stListByTimeMap = forecastPowerShortTerms.stream()
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+ .filter(forecast -> electricField.getBelongForecastManufactor().equals(forecast.getForecastManufactor()))
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+ .collect(Collectors.toMap(
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+ myObject -> DateUtil.format(myObject.getForecastTime(),"HH:mm"), // keyMapper，将Date转换为long
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+ myObject -> myObject, // valueMapper，保持原对象
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+ (existing, replacement) -> existing // mergeFunction，处理重复key的情况，这里简单地保留现有的value
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+ ));
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+ }
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+ // 提取nwp风速
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+ Map<String, Nwp> nwpListByTimeMap = new HashMap<>();
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+ if (nwpListByStationCodeMap.get(electricField.getStationCode())!=null){
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+ List<Nwp> forecastPowerShortTerms = nwpListByStationCodeMap.get(electricField.getStationCode());
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+ nwpListByTimeMap = forecastPowerShortTerms.stream()
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+ .filter(forecast -> "SYJY".equals(forecast.getForecastManufactor()))
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+ .collect(Collectors.toMap(
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+ myObject -> DateUtil.format(myObject.getPreTime(),"HH:mm"), // keyMapper，将Date转换为long
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+ myObject -> myObject, // valueMapper，保持原对象
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+ (existing, replacement) -> existing // mergeFunction，处理重复key的情况，这里简单地保留现有的value
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+ ));
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+ }
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+ // 获取nwp轮毂高度
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+ int nwpHubHeight = Integer.parseInt(sysParameterService.getSysParameterAndStationCode("NWP_HubHeight", "100", electricField.getStationCode()));
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+ // 提取超短期map
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+ Map<String, ForecastPowerUltraShortTerm> cdqListByTimeMap = new HashMap<>();
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+ if (cdqListByStationCodeMap.get(electricField.getStationCode())!=null){
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+ List<ForecastPowerUltraShortTerm> cdqTerms = cdqListByStationCodeMap.get(electricField.getStationCode());
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+ cdqListByTimeMap = cdqTerms.stream()
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+ .filter(forecast -> electricField.getBelongForecastManufactor().equals(forecast.getForecastManufactor()))
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+ .collect(Collectors.toMap(
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+ myObject -> DateUtil.format(myObject.getForecastTime(),"HH:mm"), // keyMapper，将Date转换为long
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+ myObject -> myObject, // valueMapper，保持原对象
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+ (existing, replacement) -> existing // mergeFunction，处理重复key的情况，这里简单地保留现有的value
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+ ));
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+ }
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+ // 提取实际功率
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+ Map<String, PowerStationStatusData> sjListByTimeMap = new HashMap<>();
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+ if (sjListByStationCodeMap.get(electricField.getStationCode())!=null){
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+ List<PowerStationStatusData> sjTerms = sjListByStationCodeMap.get(electricField.getStationCode());
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+ sjListByTimeMap = sjTerms.stream()
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+ .filter(forecast -> electricField.getStationCode().equals(forecast.getStationCode()))
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+ .collect(Collectors.toMap(
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+ myObject -> DateUtil.format(new Date(myObject.getTime().toInstant(ZoneOffset.of("+8")).toEpochMilli()),"HH:mm"), // keyMapper，将Date转换为long
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+ myObject -> myObject, // valueMapper，保持原对象
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+ (existing, replacement) -> existing // mergeFunction，处理重复key的情况，这里简单地保留现有的value
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+ ));
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+ }
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+ // 提取agc
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+ Map<String, GridApCommandValue> agcListByTimeMap = new HashMap<>();
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+ if (agcListByStationCodeMap.get(electricField.getStationCode())!=null){
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+ List<GridApCommandValue> agcTerms = agcListByStationCodeMap.get(electricField.getStationCode());
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+ agcListByTimeMap = agcTerms.stream()
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+ .filter(forecast -> electricField.getStationCode().equals(forecast.getStationId()))
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+ .collect(Collectors.toMap(
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+ myObject -> DateUtil.format(myObject.getTime(),"HH:mm"), // keyMapper，将Date转换为long
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+ myObject -> myObject, // valueMapper，保持原对象
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+ (existing, replacement) -> existing // mergeFunction，处理重复key的情况，这里简单地保留现有的value
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+ ));
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+ }
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+ List<ForecastReportDto> forecastReportDtoList = new ArrayList<>();
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+ for (Long tempTime = ycStartTime.getTime(); tempTime <= ycEndTime.getTime(); tempTime = tempTime + momentTime) {
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+ ForecastReportDto forecastReportDto = new ForecastReportDto();
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+ String timeStr = DateUtil.format(new Date(tempTime),"HH:mm");
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+ if (timeStr.equals("00:00")){
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+ forecastReportDto.setTime("24:00");
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+ }
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+ else{
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+ forecastReportDto.setTime(timeStr);
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+ }
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+ // 短期
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+ if (stListByTimeMap.get(timeStr)!=null){
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+ ForecastPowerShortTerm forecastPowerShortTerm = stListByTimeMap.get(timeStr);
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+ forecastReportDto.setShortTerm(forecastPowerShortTerm.getFpValue());
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+ }
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+ // 超短期
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+ if (cdqListByTimeMap.get(timeStr)!=null){
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+ ForecastPowerUltraShortTerm forecastPowerUltraShortTerm = cdqListByTimeMap.get(timeStr);
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+ forecastReportDto.setUltraShortTerm(forecastPowerUltraShortTerm.getFpValue());
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+ }
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+ // 实际功率
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+ if (sjListByTimeMap.get(timeStr)!=null){
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+ PowerStationStatusData powerStationStatusData = sjListByTimeMap.get(timeStr);
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+ forecastReportDto.setActualPower(powerStationStatusData.getRealValue());
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+ }
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+ // agc
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+ if (agcListByTimeMap.get(timeStr)!=null){
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+ GridApCommandValue gridApCommandValue = agcListByTimeMap.get(timeStr);
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+ forecastReportDto.setAgc(gridApCommandValue.getCommandValue());
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+ }
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+ // nwp轮毂风速
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+ if (nwpListByTimeMap.get(timeStr)!=null){
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+ Nwp nwp = nwpListByTimeMap.get(timeStr);
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+ // 获取nwp轮毂风速
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+ if (nwpHubHeight==170){
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+ forecastReportDto.setWindSpeed(nwp.getWs170());
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+ }
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+ else if (nwpHubHeight==150){
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+ forecastReportDto.setWindSpeed(nwp.getWs150());
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+ }
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+ else if (nwpHubHeight==140){
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+ forecastReportDto.setWindSpeed(nwp.getWs140());
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+ }
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+ else if (nwpHubHeight==130){
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+ forecastReportDto.setWindSpeed(nwp.getWs130());
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+ }
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+ else if (nwpHubHeight==120){
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+ forecastReportDto.setWindSpeed(nwp.getWs120());
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+ }
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+ else if (nwpHubHeight==110){
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+ forecastReportDto.setWindSpeed(nwp.getWs110());
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+ }
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+ else if (nwpHubHeight==100){
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+ forecastReportDto.setWindSpeed(nwp.getWs100());
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+ }
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+ else if (nwpHubHeight==90){
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+ forecastReportDto.setWindSpeed(nwp.getWs90());
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+ }
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+ else if (nwpHubHeight==80){
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+ forecastReportDto.setWindSpeed(nwp.getWs80());
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+ }
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+ else if (nwpHubHeight==70){
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+ forecastReportDto.setWindSpeed(nwp.getWs70());
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+ }
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+ else if (nwpHubHeight==50){
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+ forecastReportDto.setWindSpeed(nwp.getWs50());
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+ }
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+ else if (nwpHubHeight==30){
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+ forecastReportDto.setWindSpeed(nwp.getWs30());
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+ }
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+ else if (nwpHubHeight==10){
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+ forecastReportDto.setWindSpeed(nwp.getWs10());
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+ }
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+
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+ }
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+ forecastReportDtoList.add(forecastReportDto);
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+ }
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+
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+ // 第一行 - 主表头
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+ Row headerRow = sheet.createRow(0);
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+ for (int p = 0; p < headList.size(); p++) {
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+ Cell cell = headerRow.createCell(p);
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+ cell.setCellValue(headList.get(p));
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+ cell.setCellStyle(centerStyle);
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+ }
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+ for (int k=0;k<forecastReportDtoList.size();k++){
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+ ForecastReportDto forecastReportDto = forecastReportDtoList.get(k);
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+
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+ Row row = sheet.createRow(k + 1);
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+ Cell cell0 = row.createCell(0);
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+ cell0.setCellValue(forecastReportDto.getTime());
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+ cell0.setCellStyle(centerStyle);
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+ Cell cell1 = row.createCell(1);
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+ cell1.setCellValue(forecastReportDto.getWindSpeed()==null?"":forecastReportDto.getWindSpeed().toString());
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+ cell1.setCellStyle(centerStyle);
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+ Cell cell2 = row.createCell(2);
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+ cell2.setCellValue(forecastReportDto.getShortTerm()==null?"":forecastReportDto.getShortTerm().toString());
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+ cell2.setCellStyle(centerStyle);
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+ Cell cell3 = row.createCell(3);
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+ cell3.setCellValue(forecastReportDto.getUltraShortTerm()==null?"":forecastReportDto.getUltraShortTerm().toString());
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+ cell3.setCellStyle(centerStyle);
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+ Cell cell4 = row.createCell(4);
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+ cell4.setCellValue(forecastReportDto.getActualPower()==null?"":forecastReportDto.getActualPower().toString());
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+ cell4.setCellStyle(centerStyle);
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+ Cell cell5 = row.createCell(5);
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+ cell5.setCellValue(forecastReportDto.getAgc()==null?"":forecastReportDto.getAgc().toString());
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+ cell5.setCellStyle(centerStyle);
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+ }
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+ }
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+ // 写入输出流
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+ workbook.write(out);
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+ out.flush();
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+ } catch (Exception e) {
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+ e.printStackTrace();
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+ }
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+ }
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}
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xusl