A planning and optimization technique that determines the optimal locations (siting) and capacities (sizing) of distributed generation and storage units across a distribution network to satisfy technical constraints (voltage limits, thermal ratings, protection), economic objectives (investment and operating cost) and grid‑integration goals (hosting capacity, reliability, congestion relief).

Principle

Locational placement and capacity of DER change local injections, affecting node voltages, line loadings, losses and hosting capacity; optimal siting and sizing therefore require solving a constrained, often time‑coupled optimization that balances electrical feasibility, temporal supply–demand profiles and economic criteria.

Demonstration

Illustrative planning study — Situation: A residential feeder faces peak overloads and voltage rise during midday with growing rooftop PV adoption. Recognition: Simulation identifies nodes where injections cause voltage violations. Action: An optimization selects a mix of distributed storage sited at specific nodes and curtailed PV capacities to minimize upgrade costs while keeping voltages within limits across daily profiles. Consequence: Network upgrades are deferred and peak overloads mitigated while customer energy services are maintained.

Misapplication

Sizing DER solely by instantaneous peak or by single‑snapshot analysis without accounting for temporal generation/load profiles, network impedance or protection settings; the semantic error is treating siting and sizing as independent scalar decisions rather than a temporally constrained, locational optimization.

Consequence

Correct siting and sizing can reduce the need for network reinforcement, improve reliability and integrate renewables more effectively; incorrect choices can create reverse power flow, overvoltages, protection miscoordination, or economically inefficient investments.

Reversal

When DER are centrally aggregated and controlled as a virtual power plant with system‑level dispatch, purely local siting and sizing solutions can be suboptimal compared with centrally coordinated procurement or market mechanisms that internalize system constraints.

Boundary

Clearly within: distribution‑scale decisions identifying node locations and rated capacities for PV, batteries, small CHP, and controllable loads. Boundary case: coordinated multi‑feeder siting that interacts with substation limits. Clearly outside: transmission‑scale generator siting, or purely market investment decisions that ignore network constraints.

Semantic Tension

Local Technical Optimization ↔ Customer/Market Economics — a technically optimal siting may conflict with individual customer economics or commercial deployment preferences; resolving this tension requires regulatory or market instruments.

Synthesis

Siting and sizing is a constrained locational optimization that must integrate temporal generation/load dynamics, electrical network effects and economic objectives; treating it as a single‑snapshot or device‑centric problem risks damaging technical and economic outcomes.