IES configuration method considering peak‐valley differences of tie lines and operation costs of power grids

Abstract

The peak-valley difference of power grid will be enlarged significantly with the increasing number of integrated energy systems (IESs) connecting to power grids, which may cause a high operation cost and voltage violations. This study proposes an IES configuration method considering the peak-valley difference of the tie line between IES and power grid. An optimal configuration model of IES is established, which takes the sum of the annual operating cost of the power grid and annual cost of IES as objectives, while the tie line transmission power between IES and power grid are considered as constraints. The elite energy reserve genetic algorithm and branch and bound method are used to solve the proposed model, while the optimal power flow is used to calculate the grid operation cost under a given transmission power of the tie line. The simulation results of an improved IEEE30 node system verify the validity of the proposed method.

Comprehensive configuration strategy of energy storage allocation and line upgrading for distribution networks considering a high proportion of integrated photovoltaics

“…When planning a distribution network, the energy storage of the distribution network and the various upgrading costs of each distribution line are shown in Table 1. In the distribution network, the peak-valley difference rate of the high-voltage inlet line of transformer stations is 33% [7]; the peak, flat and valley electricity prices for power purchased from the distribution network to the utility power grid are 1.3458, 0.9003 and 0.4748 yuan/kWh respectively [18].…”

“…In terms of the load side, considering the response of the demand side and user satisfaction, Sheng et al [6] propose a multi time scale scheduling method to alleviate the power fluctuation and line overload caused by a high proportion of distribution generations (DGs). Considering the peak load regulation cost of a power system, Zhang et al [7] propose a configuration method of integrating an energy system on the load side to limit the excessive peakvalley difference. However, Sheng and Zhang [6,7] did not consider the economic feasibility of a large amount of energy storage, the demand response to incentives and the investment in communication channel construction in rural areas.…”

“…Considering the peak load regulation cost of a power system, Zhang et al [7] propose a configuration method of integrating an energy system on the load side to limit the excessive peakvalley difference. However, Sheng and Zhang [6,7] did not consider the economic feasibility of a large amount of energy storage, the demand response to incentives and the investment in communication channel construction in rural areas. In terms of the power supply side, considering the peak load regulation requirements of multiple provinces, Shen et al [8] propose a combined power generation scheduling method of hydrothermal systems, which can determine the power generation of hydropower stations and thermal storage power stations.…”

“…[7] propose a configuration method of integrating an energy system on the load side to limit the excessive peak‐valley difference. However, Sheng and Zhang [6, 7] did not consider the economic feasibility of a large amount of energy storage, the demand response to incentives and the investment in communication channel construction in rural areas. In terms of the power supply side, considering the peak load regulation requirements of multiple provinces, Shen et al.…”

Optimal Capacity Allocation of Energy Storage in Distribution Networks Considering Active/Reactive Coordination

“…In order to mitigate the negative impacts rendered by the integration of DG without unnecessary DG power curtailment and load shedding, energy storage systems (ESSs) have been identified [3]. With proper planning and management, the ESSs also can offer diverse applications in DNs, including (i) peak shifting and load leveling [4,5], (ii) renewable power output smoothing and time shifting [6], (iii) frequency modulation [7], (iv) dynamic reactive power compensation and voltage regulation [8], (v) grid expansion and upgrade deferral [9], (vi) network congestion management [10], (vii) network reconfiguration/islanding [11,12], (viii) black start and reserve [13], etc. Among various means of energy storage technologies, battery has been selected as the energy storage unit in this study due to the technology maturity and applicability.…”