Abstract
This paper presents the strategic proposition for a micro virtual power plant ( $\mu $ VPP) to participate in the distribution level energy-reserve pool managed by a distribution system operator. A chance-constrained two-stage stochastic formulation is proposed to derive the bidding strategy for $\mu $ VPP maximizing its daily profit. The stochastic nature of renewable generation and load profile of the $\mu $ VPP is captured by the Monte Carlo method. The security of supply is guaranteed by controlling the loss of load probability, which is modeled as chance constraint. The numerical tests are performed on $\mu $ VPPs with different penetration levels of distributed energy resource (DER) and renewable energy source (RES), where the impact of the DER and RES indexes and the impact of uncertainty levels are demonstrated. Also, the advantages of chance-constrained formulation as the means of risk-hedging are addressed. Finally, the impact of rival $\mu $ VPPs on the bidding behaviors and the impact of carbon taxes on the profit are analyzed.
Highlights
T HE duel challenges of making the transition to a low carbon economy while securing energy supplies led to a £32 billion plan to rewire Britain over a time span of two decades, announced by the Office of Gas and Electricity Markets (OFGEM) in 2010 [1]
This paper presents the strategic proposition for a micro virtual power plant (μ Virtual Power Plant (VPP)) to participate in the distribution level energy-reserve pool managed by a distribution system operator
The numerical tests are performed on μ VPPs with different penetration levels of distributed energy resource (DER) and renewable energy source (RES), where the impact of the DER and RES indexes and the impact of uncertainty levels are demonstrated
Summary
T HE duel challenges of making the transition to a low carbon economy while securing energy supplies led to a £32 billion plan to rewire Britain over a time span of two decades, announced by the Office of Gas and Electricity Markets (OFGEM) in 2010 [1]. CHANCE-CONSTRAINED TWO-STAGE STOCHASTIC μVPP BIDDING STRATEGY FORMULATION The uncertain components in the μVPP include wind power output, load level, RT energy price and RT call up signals for reserve offers. Equation (32) is the chance constraint for LOLP if upward reserve offer is called up to produce In this case the power flows from the μVPP to the distribution pool and the upward reserve capacity will be deducted from the upward spinning reserves. Additional decision variables include: 1) the upward change PEs,+t (kW) or downward change PEs,−t (kW) to the DA energy bid/offer in scenario s during period t; 2) the change to the ith scheduled generator output power PGs,ie,nt (kW) in scenario s during period t; 3) the actual wind power usage PWs,t,A (kW) in scenario s during period t according to the RT wind power production and 4) the load loss PLs,otss (kW) in scenario s during period t. It is solved concurrently with stateof-the-art solvers such as CPLEX
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