Through to row 101

apps/map/models.py

@@ -138,31 +138,47 @@ class CaseStudy(models.Model):
         ('WB',     _('World Bank')),
     )
 
+    GENERATION_TYPE_CHOICES = (
+        ('POW', _('Power')),
+        ('HOT', _('Heat/Cool')),
+        ('CHP', _('Combined Heat/Cool and Power (CHP)')),
+    )
+
     GENERATION_TECHNOLOGY_CHOICES = (
-        (_('Wind energy'), (
-            ('SSWE', _('Small-scale (less than 500kW)')),
-            ('LSWE', _('Large-scale (more than 500kW)'))
-        )),
-        (_('Photovoltaic electricity'), (
-            ('SSPV', _('Small-scale (less than 500kW)')),
-            ('LSPV', _('Large-scale (more than 500kW)'))
-        )),
-        (_('Hydroelectric'), (
-            ('SHYD', _('Small-scale (less than 1MW)')),
-            ('MHYD', _('Medium-scale (between 1-20MW)')),
-            ('LHYD', _('Large-scale (more than 20MW - often not considered renewable)')),
-        )),
-        ('STHE', _('Solar thermal electricity (e.g using parabolic reflectors)')),
+        ('BIO', _('Bio-energy')),
         ('GEOT', _('Geothermal electricity')),
-        ('BIOG', _('Biogas turbine')),
-        ('OTHB', _('Other biomass (including liquid/solid biofuel)')),
+        (_('Hydro'), (
+            ('uHYD', _('Micro hydro (<100kW)')),
+            ('SHYD', _('Small-scale hydro (<1MW)')),
+            ('MHYD', _('Medium-scale hydro (1-30MW)')),
+            ('LHYD', _('Large-scale hydro (>30MW - often not considered renewable)')),
+        )),
+        (_('Marine'), (
+            ('WAVE', _('Wave')),
+            ('TSTR', _('Tidal stream')),
+            ('TBAR', _('Tidal barrage/lagoon')),
+            ('TOTH', _('Other')),
+        )),
+        (_('Solar'), (
+            ('SSPV', _('Small-scale photovoltaic (<500kW)')),
+            ('LSPV', _('Large-scale photovoltaic (>500kW)')),
+            ( 'CSP', _('Concentrated solar power (CSP)')),
+            ('PARA', _('Parabolic trough (open or enclosed)')),
+            ('FRES', _('Fresnel reflector')),
+            ('STIR', _('Dish Stirling')),
+        )),
+        (_('Wind'), (
+            ('SSWE', _('Small-scale wind (<500kW)')),
+            ('LSWE', _('Large-scale wind (>500kW)'))
+        )),
         ('OTHR', _('Other (tidal, wave etc)'))
     )
 
     POWER_TECHNOLOGY_CHOICES = (
-        ('PT', _('Power transmission (grid lines, substations etc)')),
-        ('ES', _('Energy storage (pumped storage, compressed air, battery systems etc')),
-        ('OT', _('Others'))
+        ('PT', _('Electrical power transmission')),
+        ('ES', _('Energy storage')),
+        ('HN', _('Heat networks')),
+        ('OT', _('Other')),
     )
 
     TYPE_OF_EXTRACTION_CHOICES = (
@@ -556,8 +572,15 @@ class CaseStudy(models.Model):
     # Second Screen - Technical and economic analysis
     ##
 
-    # 2.1 - Renewable Energy Generation
-    # 2.1.1
+    ## Energy generation project
+
+    generation_type = models.CharField(
+        verbose_name=_('What is being generated?'),
+        max_length=4,
+        choices=GENERATION_TYPE_CHOICES,
+        blank=True
+    )
+
     generation_technology = models.CharField(
         verbose_name=_("Generation technology"),
         help_text=_("Select the type of renewable energy generation that most applies to this case study."),
@@ -566,20 +589,32 @@ class CaseStudy(models.Model):
         blank=True
     )
 
-    # 2.1.1.12
-    # Should be filled in if 2.1.1 was answered as biogas or biomass.
-    biomass_detail = models.CharField(
-        verbose_name=_("Description of feedstock"),
-        help_text=_("If you selected biogas or biomass, please describe the feedstock (where the fuel came from e.g. \
-                   corn, algae, anaerobic digestion, commercial waste etc)"),
+    generation_technology_other = models.CharField(
+        verbose_name=_("Further details"),
+        help_text=_("If you selected other, or if you would like to further define what you have chosen, \
+                    please specify the generation technology further.  For example, if you chose solar PV \
+                    it is most likely to be a crystalline silicon type, but maybe it is not."),
         max_length=200,
         blank=True
     )
 
-    # 2.1.1.14
-    generation_technology_other = models.CharField(
-        verbose_name=_("Other generation type"),
-        help_text=_("If you selected other, please specify the generation technology (e.g. tidal, wave etc)"),
+    # Should be filled in if generation_technology was answered as bio-energy
+    biomass_detail = models.CharField(
+        verbose_name=_("Bio-energy feedstock"),
+        help_text=_("<div class='text-muted'>\
+                    <p>Please describe the source of the fuel and how it is processed/used. \
+                    Please consider:\
+                    <ul>\
+                    <li>where the fuel came from e.g. corn, forestry, algae, commercial food waste, \
+                    landfill gas, sewage, livestock farm, etc. \
+                    <li>how it is processed e.g. direct-fired, co-firing with other renewable input, \
+                    gasification, bacterial decomposition (anaerobic digestion, AD), pyrolysis, \
+                    small/modular, artificial photosynthesis, fuel cell, etc. \
+                    </ul>\
+                    \
+                    <p>We do not expect users to know this information, but if you do \
+                    it may be useful to give a fuller picture.\
+                    </div>"),
         max_length=200,
         blank=True
     )
@@ -595,8 +630,8 @@ class CaseStudy(models.Model):
     # 2.1.3
     # TODO: Auto-completion based on previous entries so we can query case-studies with the same answer.
     generation_equipment_supplier = models.TextField(
-        verbose_name=_("Generation equipment supplier"),
-        help_text=_("Enter the supplier of the generation equipment. (E.g. Siemens)"),
+        verbose_name=_("Generation equipment supplier(s)"),
+        help_text=_("Enter the supplier of the generation equipment. (E.g. Siemens Gamesa, GE, Alstom, Vestas, Hanwha Q CELLS, Mitsubishi, First Solar, Jinko Solar, Trina Solar, Suzlon Energy, Statkraft, Shanghai Electric, Ballard Power Systems, Panasonic, etc.)"),
         blank=True
     )
 
@@ -619,7 +654,6 @@ class CaseStudy(models.Model):
     # 2.2.1
     power_technology = models.CharField(
         verbose_name=_("Power technology"),
-        help_text=_("Select the related energy technology."),
         max_length=2,
         choices=POWER_TECHNOLOGY_CHOICES,
         blank=True
@@ -628,7 +662,7 @@ class CaseStudy(models.Model):
     # 2.2.1.4
     power_technology_other = models.CharField(
         verbose_name=_("Other power technology"),
-        help_text=_("If you answered 'others', please specify the power technologies."),
+        help_text=_("Please specify the power technology."),
         max_length=128,
         blank=True
     )