Low-Carbon Planning of Active Distribution Networks Considering Demand Response and Electricity-Carbon Trading

Abstract

: This paper proposes a low-carbon planning method for active distribution networks (ADNs) that coordinates demand response (DR), battery energy storage system (BESS) planning, and electricity–carbon trading (ECT). A multi-period BESS model is developed for siting, sizing, and state-of-charge operation, while DR is modeled via a time-of-use tariff and price-elasticity matrix to shift flexible demand across peak, flat, and valley periods. A dynamic grid-purchased carbon emission factor is introduced into the ECT cost formulation and carbon emission objective, forming a constrained three-objective optimization model that minimizes annual comprehensive cost, voltage deviation, and purchased carbon emissions. The constrained two-archive evolutionary algorithm (C-TAEA) is applied to obtain the Pareto solution set, and a compromise solution is selected via the analytic hierarchy process. Case studies are performed on the IEEE 33-bus system using four weighted typical seasonal days from Kunming, China to represent annual operation. For the selected solution, voltage deviation decreases by 40.22% (from 0.020774 to 0.012418 p.u.), annual network loss reduces by 25.25% (from 306.94 to 229.44 MWh), daily load fluctuation drops by 16.22% (from 9.3479 to 7.8320 MW/day), and wind-PV curtailment falls from 1.31 to 0 MWh/year. Notably, annual grid-purchased carbon emissions decrease from 12,295.95 to 6014.19 tCO 2 /year with a reduction rate of 51.09%. These results verify that coordinated DR and BESS operation can simultaneously improve voltage quality, reduce network losses, smooth load profiles, enhance renewable accommodation, and achieve significant decarbonization under the ECT mechanism.