Yes, there are many ways to solve this recurrence. The method that you found uses generating functions and is towards the sophisticated end. Here are three others.
(1) Guess and prove. Calculate the first few terms of the sequence:
$$\begin{array}{r|rr}n&1&2&3&4&5&6\\
T(n)&1&3&7&15&31&63
\end{array}$$
The numbers in the bottom row should look familiar: they’re one less than consecutive powers of $2$. Thus, you might at this point guess that in general $T(n)=2^n-1$. Of course, now you have to prove your guess. This typically requires a proof by induction. Getting the induction off the ground (i.e., checking the base case) is easy: $T(1)=1=2^1-1$. Now you need to show that if $T(n)=2^n-1$ is true when $n=k$, it’s also true when $n=k+1$.
Assume as your induction hypothesis that $T(k)=2^k-1$ for some $k\ge 1$. By the definition of $T$ you know that $T(k+1)=2T(k)+1$. Your induction hypothesis tells you that $T(k)=2^k-1$, so $T(k+1)=2(2^k-1)-1=2\cdot2^k-2+1=2^{k+1}-1$, which is exactly what we wanted. It follows by induction that $T(n)=2^n-1$ for all $n\ge 1$.
Added: It isn’t always so easy to guess the right formula. As Gadi A reminds me, there is a wonderful tool available to help with this, the On-Line Encyclopedia of Integer Sequences, known as OEIS. If you search it for a sequence containing $\langle 1,3,7,15,31,63\rangle$, you’ll get 29 matches, of which the first, A000225, turns out to be the right one for this problem. From the COMMENTS section of the entry:
Also solutions (with minimum number of moves) for the problem of Benares Temple, i.e. three diamond needles with n discs ordered by decreasing size on the first needle to place in the same order on the third one, without ever moving more than one disc at a time and without ever placing one disc at the top of a smaller one.
(2) Unwind the recurrence. Imagine that $n$ is a fairly large number, and start calculating $T(n)$ in terms of earlier and earlier terms of the sequence until you spot a pattern:
$$\begin{align*}
T(n)&=2T(n-1)+1\\
&=2\big(2T(n-2)+1\big)+1\\
&=2^2T(n-2)+2+1\\
&=2^2\big(2T(n-3)+1\big)+2+1\\
&=2^3T(n-3)+2^2+2+1\\
&\qquad\qquad\qquad\vdots\\
&=2^kT(n-k)+2^{k-1}+2^{k-2}+\dots+2+1\tag{1}\\
&=2^kT(n-k)+\sum_{i=0}^{k-1}2^k\;.\tag{2}
\end{align*}$$
Now plug $k=n-1$ into $(2)$ to get $$\begin{align*}T(n)&=2^{n-1}T(1)+\sum_{i=0}^{n-2}2^i\\
&=2^{n-1}+\big(2^{n-1}-1\big)\\
&=2^n-1\;,
\end{align*}$$
where I used the formula for the sum of a geometric series to evaluate the summation.
If you use this approach, you should then go on to prove the formula by induction, just as in the previous method, because the formula in $(1)$ was a guess $-$ a very solid guess, but still a guess requiring proof.
Another point to notice here is that the last step would have been very slightly easier if we’d backtracked the sequence by calculating $T(0)$ from $T(1)$: $T(0)=\frac12\big(T(1)-1\big)=0$. Then we could have substituted $k=n$ into $(2)$ to get the desired result directly.
(3) Turning the non-homogeneous recurrence into a homogeneous one by a change of variable. Let $S(n)=T(n)+d$ for some as yet unknown $d$. Then $T(n)=S(n)-d$, and the recurrence can be rewritten as
$$\begin{align*}
S(n)-d&=\begin{cases}2\big(S(n-1)-d\big)+1,&\text{if }n>1\\
1-d,&\text{if }n=1
\end{cases}\\\\
&=\begin{cases}
2S(n-1)-2d+1,&\text{if }n>1\\
1-d,&\text{if }n=1\;.
\end{cases}
\end{align*}$$
Move the constants to the righthand side in the recurrence: $$S(n)=2S(n-1)-d+1\;.$$ Thus, if we set $d=1$, we get rid of the constant term: $$S(n)=2S(n-1)\;.$$ This is just exponential growth: $S(n)$ doubles with each increase of $1$ in $n$. And $$S(1)=T(1)+d=1+1=2=2^1\;,$$ so it’s very easy to see that $S(n)=2^n$ for every $n\ge 1$. Finally, $T(n)=S(n)-d=2^n-1$.
For your second question, I could cook up other examples, but the Tower of Hanoi problem is by far the best known satisfying this recurrence.
Other answers build a summation and it isn't necessary. Here is a solution exclusively using the repertoire method and in the same spirit as 1.18 in the book
Let
$$g(n)=A(n)α+B(n)γ+C(n)β_0+D(n)β_1 $$
Recall that $(\alpha, \gamma, \beta_0, \beta_1) \to (\alpha, 0, \beta_0, \beta_1)$ for $n = (b_mb_{m−1}...b_1b_0)_2$ is the radix changing solution
$$A(n)α+C(n)β_0+D(n)β_1=(αβ_{b_{m−1}}...β_{b_1}β_{b_0})_3 \tag{1}$$
Let $(\alpha, \gamma, \beta_0, \beta_1) \to (0, 0, 0, 1)$. Then
$$D(n) = (β_{b_{m−1}}...β_{b_1}β_{b_0})_3 = (b_{m−1}...b_1b_0)_3 \tag{2}$$
Think of $\beta_0 = 0$ and $\beta_1= 1$ as a function from radix-2 to radix-3, changing every power and preserving the coefficients.
Let $(\alpha, \gamma, \beta_0, \beta_1) \to (1, 0, 0, 0)$. Then
$$ A(n) = (100...0)_3 = 3^m \tag{3}$$
Given the identity derived from $g(n)=n$, we can solve $$ A(n)−B(n)+D(n)=n$$ for $\gamma B(n)$. Thus plugging $$ \gamma B(n) = \gamma A(n) + \gamma D(n) - \gamma n$$ into (1),
$$ A(n)α+ \gamma B(n)+ C(n)β_0+D(n)β_1=(αβ_{b_{m−1}}...β_{b_1}β_{b_0})_3 + \gamma A(n) + \gamma D(n) - \gamma n $$
Finally, for $n = (b_mb_{m−1}...b_1b_0)_2$, we can plug in (3) and (2),
$$ g(n) = (αβ_{b_{m−1}}...β_{b_1}β_{b_0})_3 + \gamma(1b_{m−1}...b_1b_0)_3 - \gamma (b_mb_{m−1}...b_1b_0)_2 $$
Best Answer
You are basically assuming that $\,T_n\,$ has the form $\,T_n = \alpha \cdot 2^n+\alpha\,$, but that's not the case. It is easy to verify that your end result $\,T_n = -2^{n+1}-2\,$ does not satisfy the original recurrence $\,T_{n}=2 \cdot T_{n-1}+2\,$, and that's because of the (wrong) assumption you made in the beginning.
You could solve it this way by starting with a slightly more general $\,A_n = \alpha \cdot \,2^n + \beta\,$. Then, eliminating $\,2^n\,$ between two consecutive relations, you get $\,A_n=2 \cdot A_{n-1}-\beta\,$. This matches the original recurrence $\,T_{n}=2 \cdot T_{n-1}+2\,$ iff $\,\beta=-2\,$, then $\,A_0=0\,$ implies $\,\alpha=1\,$, so in the end the solution is $\,T_n = 2^n-2\,$.
The more direct way to solve it is add $\,2\,$ on both sides and rewrite it as $\,T_n+2 = 2 \cdot \left(T_{n-1}+2\right)\,$, which indicates that $\,T_n+2\,$ is a geometric progression with common ratio $\,2\,$.