Recent advances in renewable energy technologies and changes in the electric utility infrastructures have increased the interest of the power utilities in utilisation of distributed generation (DG) resources to generate electricity. The recent trends in the development and utilisation of DG resources for power generation application are subject to the deregulation of the electric power sector and technical constraints to extend distribution and transmission networks to some areas. The electric power system planners, regulators and the policy makers have derived many benefits from integration of DG units into the distribution networks. These benefits depend on the characteristics of DG units such as photovoltaic (PV), wind system and reciprocating engines, characteristics of the loads, local renewable resources and network configuration. This study comprehensively reviews various research works on the technical, environmental and economic benefits of renewable DG integration such as line-loss reduction, reliability improvement, economic benefits and environmental pollution optimisation. These benefits can be optimised if all the renewable DG units are optimally sized, located and configured. This study also reviews the current status of renewable DG technologies based on different characteristics and the operational issues of integration of renewable DG into the electric power systems.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rpg.2015.0378

Integration of renewable distributed generators into the distribution system: a review

http://users.ntua.gr/pgeorgil/Files/J78.pdf

A review of power distribution planning in the modern power systems era: Models, methods and future research

Safely achieving the goals of the Paris Climate Agreement requires a worldwide transformation to carbon-neutral societies within the next 30 y. Accelerated technological progress and policy implementations are required to deliver emissions reductions at rates sufficiently fast to avoid crossing dangerous tipping points in the Earth's climate system. Here, we discuss and evaluate the potential of social tipping interventions (STIs) that can activate contagious processes of rapidly spreading technologies, behaviors, social norms, and structural reorganization within their functional domains that we refer to as social tipping elements (STEs). STEs are subdomains of the planetary socioeconomic system where the required disruptive change may take place and lead to a sufficiently fast reduction in anthropogenic greenhouse gas emissions. The results are based on online expert elicitation, a subsequent expert workshop, and a literature review. The STIs that could trigger the tipping of STE subsystems include 1) removing fossil-fuel subsidies and incentivizing decentralized energy generation (STE1, energy production and storage systems), 2) building carbon-neutral cities (STE2, human settlements), 3) divesting from assets linked to fossil fuels (STE3, financial markets), 4) revealing the moral implications of fossil fuels (STE4, norms and value systems), 5) strengthening climate education and engagement (STE5, education system), and 6) disclosing information on greenhouse gas emissions (STE6, information feedbacks). Our research reveals important areas of focus for larger-scale empirical and modeling efforts to better understand the potentials of harnessing social tipping dynamics for climate change mitigation.

https://www.pnas.org/content/pnas/117/5/2354.full.pdf

Social tipping dynamics for stabilizing Earth's climate by 2050.

Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming

Concerns over climate change (global warming) are driving innovation for stabilizing and reducing greenhouse gas (GHG) emissions. Technologies like carbon capture and storage (CCS) as well as renewable energy sources including wind and solar have been increasingly used and integrated into existing energy systems. The global installed renewable energy capacity booms, but many problems regarding grid integration appears due to the variability and uncertainty in the output of renewable energy generation. Therefore, large amount of curtailed electric energy (CEE) exists, which means some of the renewable energy generation must be wasted to keep real-time balance between load and generation in power system. In this paper, the definition of CEE is introduced, and the main causes for CEE are discussed. Then, the worldwide CEE is estimated, especially in China. Moreover, to evaluate the utilization priority of various generation resources, the potential of reducing fossil fuel consumption, GHG emissions and air pollutants as well as the potential of capturing CO2 with CEE are analyzed. Possible CEE reduction strategies are also presented.

Comprehensive review of renewable energy curtailment and avoidance: A specific example in China

This study presents an integrated methodology that considers renewable distributed generation (RDG) and demand responses (DR) as options for planning distribution systems in a transition towards low-carbon sustainability. It is assumed that demand responsiveness is enabled by real-time pricing (RTP), and the problem has been formulated as a dynamic two-stage model. It co-optimizes the allocation of renewables [including wind and solar photovoltaic (PV)], non-renewable DG units (gas turbines) and smart metering (SM) simultaneously with network reinforcement for minimizing the total economic and carbon-emission costs over planning horizons. The behavior compliance to RTP is described through a nodal-based DR model, in which the fading effect attended during the load recovery is highlighted. Besides, uncertainties associated with renewable energy generation and price-responsiveness of customers are also taken into account and represented by multiple probabilistic scenarios. The proposed methodology is implemented by employing an efficient hybrid algorithm and applied to a typical distribution test system. The results demonstrate the effectiveness in improving the efficiency of RDG operations and mitigating CO2 footprint of distribution systems, when compared with the conventional planning paradigms.

Integrated Planning for Transition to Low-Carbon Distribution System With Renewable Energy Generation and Demand Response

Enhancing distribution system resilience against extreme weather events: Concept review, algorithm summary, and future vision

Currently the development of large scale electric vehicles have become governments' focus of attention. Based on the research of charging and discharging power models, the paper puts forward the island formation strategy and establishes the distribution system reliability model with the electric vehicles. The Monte Carlo time sequential simulation is used to evaluate the effects of different vehicle types, locations and penetration on the reliability of IEEE-RBTS Bus6 system. The conclusion could be used as references to the electric vehicle development.

Analyzing the impacts of electric vehicle charging on distribution system reliability

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and CO2 emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

With the wide application of gas turbine and power-to-gas (P2G) equipment, the electricity network and natural gas network are coupled more tightly. With the continuous improvement of new energy penetration, the variables are needed to be investigated in the coupled system considering random fluctuations emerge. In this paper, the probabilistic energy flow model of the integrated electricity-gas energy system (IEGES) with wind power is established. Considering the influence of various uncertain factors, the distribution of state variables are obtained by using the cumulant method and Gram-Chailier expansion. The validity of the proposed model and the cumulant method are verified by the analytic results of the case. In the IEGES, P2G technology can promote the consumption of wind power from grid by conversing it to natural gas stored in the gas network. So, P2G technology reduces the impact of wind power integration on power system security.

Bo Zeng

Papers

Integrated Planning for Transition to Low-Carbon Distribution System With Renewable Energy Generation and Demand Response

Enhancing distribution system resilience against extreme weather events: Concept review, algorithm summary, and future vision

Analyzing the impacts of electric vehicle charging on distribution system reliability

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

Analysis of probabilistic energy flow for integrated electricity-gas energy system with P2G based on cumulant method