diff --git a/RELEASE_NOTES.md b/RELEASE_NOTES.md
index f8640ca..55bd53f 100644
--- a/RELEASE_NOTES.md
+++ b/RELEASE_NOTES.md
@@ -9,6 +9,8 @@
 
 ## New Features
 
+* Adds new method `receive_aggregated_data` to receive microgrid component data
+  aggregated by user-defined formulae.
 
 ## Bug Fixes
 
diff --git a/src/frequenz/client/reporting/_client.py b/src/frequenz/client/reporting/_client.py
index 270e641..a90ca3c 100644
--- a/src/frequenz/client/reporting/_client.py
+++ b/src/frequenz/client/reporting/_client.py
@@ -15,10 +15,19 @@
 from frequenz.api.common.v1.microgrid.microgrid_pb2 import (
     MicrogridComponentIDs as PBMicrogridComponentIDs,
 )
+from frequenz.api.reporting.v1.reporting_pb2 import (
+    AggregationConfig as PBAggregationConfig,
+)
 from frequenz.api.reporting.v1.reporting_pb2 import IncludeOptions as PBIncludeOptions
 from frequenz.api.reporting.v1.reporting_pb2 import (
     MetricConnections as PBMetricConnections,
 )
+from frequenz.api.reporting.v1.reporting_pb2 import (
+    ReceiveAggregatedMicrogridComponentsDataStreamRequest as PBAggregatedStreamRequest,
+)
+from frequenz.api.reporting.v1.reporting_pb2 import (
+    ReceiveAggregatedMicrogridComponentsDataStreamResponse as PBAggregatedStreamResponse,
+)
 from frequenz.api.reporting.v1.reporting_pb2 import (
     ReceiveMicrogridComponentsDataStreamRequest as PBReceiveMicrogridComponentsDataStreamRequest,
 )
@@ -145,6 +154,24 @@ def __iter__(self) -> Iterator[MetricSample]:
                         )
 
 
+@dataclass(frozen=True)
+class AggregatedMetric:
+    """An aggregated metric sample returned by the Reporting service."""
+
+    _data_pb: PBAggregatedStreamResponse
+    """The underlying protobuf message."""
+
+    def sample(self) -> MetricSample:
+        """Return the aggregated metric sample."""
+        return MetricSample(
+            timestamp=self._data_pb.sample.sampled_at.ToDatetime(),
+            microgrid_id=self._data_pb.aggregation_config.microgrid_id,
+            component_id=self._data_pb.aggregation_config.aggregation_formula,
+            metric=self._data_pb.aggregation_config.metric,
+            value=self._data_pb.sample.sample.value,
+        )
+
+
 class ReportingApiClient(BaseApiClient[ReportingStub]):
     """A client for the Reporting service."""
 
@@ -353,3 +380,78 @@ def dt2ts(dt: datetime) -> PBTimestamp:
         except grpcaio.AioRpcError as e:
             print(f"RPC failed: {e}")
             return
+
+    async def receive_aggregated_data(
+        self,
+        *,
+        microgrid_id: int,
+        metric: Metric,
+        aggregation_formula: str,
+        start: datetime | None,
+        end: datetime | None,
+        resampling_period: timedelta,
+    ) -> AsyncIterator[MetricSample]:
+        """Iterate over aggregated data for a single metric.
+
+        For now this only supports a single metric and aggregation formula.
+
+        Args:
+            microgrid_id: The microgrid ID.
+            metric: The metric name.
+            aggregation_formula: The aggregation formula.
+            start: start datetime, if None, the earliest available data will be used
+            end: end datetime, if None starts streaming indefinitely from start
+            resampling_period: The period for resampling the data.
+
+        Yields:
+            An iterator over the aggregated metric samples.
+
+        Raises:
+            ValueError: If the resampling_period is not provided.
+        """
+        if not resampling_period:
+            raise ValueError("resampling_period must be provided")
+
+        aggregation_config = PBAggregationConfig(
+            microgrid_id=microgrid_id,
+            metric=metric.to_proto(),
+            aggregation_formula=aggregation_formula,
+        )
+
+        def dt2ts(dt: datetime) -> PBTimestamp:
+            ts = PBTimestamp()
+            ts.FromDatetime(dt)
+            return ts
+
+        time_filter = PBTimeFilter(
+            start=dt2ts(start) if start else None,
+            end=dt2ts(end) if end else None,
+        )
+
+        stream_filter = PBAggregatedStreamRequest.AggregationStreamFilter(
+            time_filter=time_filter,
+            resampling_options=PBResamplingOptions(
+                resolution=round(resampling_period.total_seconds())
+            ),
+        )
+
+        request = PBAggregatedStreamRequest(
+            aggregation_configs=[aggregation_config],
+            filter=stream_filter,
+        )
+
+        try:
+            stream = cast(
+                AsyncIterator[PBAggregatedStreamResponse],
+                self.stub.ReceiveAggregatedMicrogridComponentsDataStream(
+                    request, metadata=self._metadata
+                ),
+            )
+            async for response in stream:
+                if not response:
+                    break
+                yield AggregatedMetric(response).sample()
+
+        except grpcaio.AioRpcError as e:
+            print(f"RPC failed: {e}")
+            return