Search

With the proliferation of natural gas combined cycle units, the modern energy infrastructure has evolved into a coupled electricity and natural gas system, which often encompasses multiple large-scale and geographically-diverse energy areas. The similarity in electricity and natural gas consumption profiles in coupled systems gives rise to critical mandates for the coordinated optimization of electricity and natural gas operation. This paper presents a decentralized optimization framework, which considers wind energy and power-to-gas (P2G) technologies in the operation of integrated multi-area electricity and natural gas transmission system (IEGTS). First, a comprehensive optimal dispatch model is established for the multi-area IEGTS in a centralized manner where bi-directional flows of electricity and natural gas among multi-areas are optimized considering the stochastic nature of wind energy. In particular, a linearized transient-state gas flow model under mild assumptions is proposed to represent the dynamic characteristics of the natural gas sector. The centralized optimization problem is decomposed into a set of computationally-tractable subproblems that are solved independently in individual areas. The alternating direction multiplier method is employed to achieve a rapidly convergent solution while preserving the privacy of operation data shared among participating areas. Finally, case studies are carried out on two multi-area IEGTS with multiple wind generation scenarios which demonstrate the computational performance of the proposed method with P2G facilities operating in variable conditions. [ABSTRACT FROM AUTHOR]

This paper focuses on transactive energy management in local energy communities and proposes a coalitional game model which considers the presence and utilization of flexible loads and the power output uncertainties from renewable energy sources. The superadditivity and balancedness of the proposed game model are proved rigorously by demonstrating that a nucleolus-based solution leads to a stable and fair payoff distribution scheme for all players. More specifically, the objective function is proved concave with its analytical expression, derived through an approximated piecewise linear function. The proposed allocation of realized payoffs is then proved to converge consistently to a nucleolus-based solution. It is demonstrated by numerical simulations that the grand coalition effectively increases the global payoff and the proposed allocation scheme contributes to peak shaving and valley filling in the overall load profile. [ABSTRACT FROM AUTHOR]

A key feature of electricity generation in a distribution network is manifested by renewable generation with zero marginal cost. Existing market mechanisms are likely to fail in supporting such decentralized transactions while providing a reasonable price signal to compensate for the investment cost of renewable generators. Given this background, this paper first describes an average pricing market (APM) mechanism for pricing zero marginal cost renewable generation outputs in the distribution network. Then, a decentralized formulation of the APM mechanism is derived using the alternating direction method of multipliers (ADMM). Convergence of the decentralized mechanism can be guaranteed under some mild conditions for parameter setting. Finally, case studies are carried out to demonstrate the presented market mechanism. Simulation results show that the problem of always bidding a zero price by renewable generators in some existing markets can be avoided. The presented method also provides a solution for organizing decentralized electricity transactions in the distribution network and can converge to similar results with those obtained by the centralized one, with a relative error less than 5%. [ABSTRACT FROM AUTHOR]

A key feature of an electricity distribution market is that it may be dominated by renewable generation with zero marginal cost. Existing market mechanisms are likely to fail in this context since it cannot generate a reasonable price signal to compensate for the investment cost of renewable generators. Given this background, a double-sided auction market mechanism is presented for pricing the zero marginal cost renewable generation in the distribution system. Honesty is proved to be a dominant strategy for participants, which would enable the proposed mechanism to develop into a set-and-forget bidding market. The proposed market mechanism is also shown to be compatible with the nodal pricing system. Finally, case studies are carried out, and the results show that under the proposed market mechanism, the problem of always bidding a zero price by renewable generators in some existing markets can be avoided. Even when only renewable generation units with zero marginal costs participate in the bidding, the proposed mechanism can still produce a reasonable market clearing price. When adopting the average pricing market mechanism, merits of nodal pricing can still be retained and contribute to the enhancement of the operating efficiency of the distribution network. [ABSTRACT FROM AUTHOR]

With the ever-increasing penetration level of renewable generation sources, a modern power system is facing more inevitable uncertainties that could lead to weakly damped oscillations. Detecting coherency among synchronous generators is one of the key steps of situational awareness for a given power system with a very high level of renewable penetration. In this paper, a wide-area measurement system (WAMS) based coherency detection algorithm employing the kernel principal component analysis (KPCA) and clustering analysis based on affinity propagation (AP) is proposed for a power system with extensive penetration of renewable generation sources. First, several trajectory similarity indexes are presented for determining the similarity between the trajectories of any two generators in the center of inertia coordinate. Second, a KPCA-based method is presented to integrate the trajectory similarity indexes for addressing the correlations among multiple indexes. Next, the AP-based clustering analysis method is utilized to detect the coherency among synchronous generators without the need of prespecifying the number of clusters. Finally, Southern China power system and a part of northern China power system with Zhangbei wind farms included, both with very high levels of renewable generation penetration, are utilized to demonstrate the proposed WAMS-based coherency detection methodology, and the application to actual Guangdong power system in south China to verify the applicability and practicality. [ABSTRACT FROM AUTHOR]

Presenta a discussion on the paper, "Gas-Electricity Coordination in Competitive Markets Under Renewable Energy Uncertainty." [ABSTRACT FROM PUBLISHER]